feat(bump version):

build(deps-dev): bump mkdocstrings from 0.28.1 to 0.28.2

.gitattributes

@@ -0,0 +1,3 @@
+*.js linguist-detectable=false
+*.html linguist-detectable=false
+*.py linguist-detectable=true

.gitignore

@@ -16,3 +16,4 @@ garak_rest.json
 inv/
 scripts/
 docx/
+agentic_security.toml

.pre-commit-config.yaml

@@ -46,20 +46,23 @@ repos:
     -   id: trailing-whitespace
         types: [python]
     -   id: end-of-file-fixer
-        types: [python]
+        types: [file]
+        files: \.(py|js|vue)$
 
-  - repo: https://github.com/executablebooks/mdformat
-    rev: 0.7.17
-    hooks:
-      - id: mdformat
-        name: mdformat
-        entry: mdformat .
-        language_version: python3.11
 
-  # - repo: https://github.com/hadialqattan/pycln
-  #   rev: v2.4.0
+  # - repo: https://github.com/executablebooks/mdformat
+  #   rev: 0.7.22
   #   hooks:
-  #     - id: pycln
+  #     - id: mdformat
+  #       name: mdformat
+  #       entry: mdformat .
+  #       language_version: python3.11
+  #       files: "docs/.*\\.md$"
+
+  - repo: https://github.com/hadialqattan/pycln
+    rev: v2.5.0
+    hooks:
+      - id: pycln
 
   - repo: https://github.com/isidentical/teyit
     rev: 0.4.3
@@ -79,8 +82,8 @@ repos:
     rev: v2.2.6
     hooks:
     -   id: codespell
-        exclude: '^(third_party/)|(poetry.lock)'
+        exclude: '^(third_party/)|(poetry.lock)|(ui/package-lock.json)|(agentic_security/static/.*)'
         args:
         # if you've got a short variable name that's getting flagged, add it here
-        - -L bu,ro,te,ue,alo,hda,ois,nam,nams,ned,som,parm,setts,inout,warmup,bumb,nd,sie
+        - -L bu,ro,te,ue,alo,hda,ois,nam,nams,ned,som,parm,setts,inout,warmup,bumb,nd,sie,vEw
         - --builtins clear,rare,informal,usage,code,names,en-GB_to_en-US

Readme.md

@@ -1,37 +1,54 @@
 <p align="center">
-
-<h1 align="center">Agentic Security</h1>
-
-<p align="center">
-    The open-source Agentic LLM Vulnerability Scanner
-    <br />
-    <br />
+  <h1 align="center">Agentic Security</h1>
+  <p align="center">
+    An open-source vulnerability scanner for Agent Workflows and Large Language Models (LLMs)<br />
+    Protecting AI systems from jailbreaks, fuzzing, and multimodal attacks.<br />
+    <a href="https://agentic-security.vercel.app">Explore the docs »</a> ·
+    <a href="https://github.com/msoedov/agentic_security/issues">Report a Bug »</a>
+  </p>
 </p>
 
 <p align="center">
   <a href="https://github.com/msoedov/agentic_security/commits/main">
-    <img alt="GitHub Last Commit" src="https://img.shields.io/github/last-commit/msoedov/agentic_security?style=for-the-badge&logo=git&labelColor=000000&logoColor=FFFFFF&label=Last Commit&color=6A35FF" />
+    <img alt="GitHub Last Commit" src="https://img.shields.io/github/last-commit/msoedov/agentic_security?style=for-the-badge&logo=git&labelColor=000000&color=6A35FF" />
   </a>
   <a href="https://github.com/msoedov/agentic_security">
-    <img alt="GitHub Repo Size" src="https://img.shields.io/github/repo-size/msoedov/agentic_security?style=for-the-badge&logo=database&labelColor=000000&logoColor=FFFFFF&label=Repo Size&color=yellow" />
-  </a>
+    <img alt="GitHub Repo Size" src="https://img.shields.io/github/repo-size/msoedov/agentic_security?style=for-the-badge&logo=database&labelColor=000000&color=yellow" />
   </a>
   <a href="https://github.com/msoedov/agentic_security/blob/master/LICENSE">
-    <img alt="GitHub License" src="https://img.shields.io/github/license/msoedov/agentic_security?style=for-the-badge&logo=codeigniter&labelColor=000000&logoColor=FFFFFF&label=License&color=FFCC19" />
+    <img alt="GitHub License" src="https://img.shields.io/github/license/msoedov/agentic_security?style=for-the-badge&logo=codeigniter&labelColor=000000&color=FFCC19" />
+  </a>
+  <a href="https://pypi.org/project/agentic-security/">
+    <img alt="PyPI Version" src="https://img.shields.io/pypi/v/agentic-security?style=for-the-badge&logo=pypi&labelColor=000000&color=00CCFF" />
+  </a>
+  <a href="https://discord.gg/stw3DfZQ">
+    <img alt="Join Discord" src="https://img.shields.io/badge/Discord-Join%20Us-black?style=for-the-badge&logo=discord&labelColor=000000&color=DD55FF" />
   </a>
-  <a href="https://discord.com/channels/1340010688764051499/1340010689309315247"><img alt="Join the community" src="https://img.shields.io/badge/Join%20the%20community-black.svg?style=for-the-badge&logo=lightning&labelColor=000000&logoColor=FFFFFF&label=&color=DD55FF&logoWidth=20" /></a>
-
 </p>
 
+
 ## Features
 
-- Multi modal attacks and vulnerability scanners🛠️
-- Multi-Step/multi-round Jailbreaks 🌀
-- Comprehensive fuzzing for any LLMs 🧪
-- LLM API integration and stress testing 🛠️
-- RL based attacks 📡
 
-Note: Please be aware that Agentic Security is designed as a safety scanner tool and not a foolproof solution. It cannot guarantee complete protection against all possible threats.
+Agentic Security equips you with powerful tools to safeguard LLMs against emerging threats. Here's what you can do:
+
+- **Multimodal Attacks** 🖼️🎙️
+  Probe vulnerabilities across text, images, and audio inputs to ensure your LLM is robust against diverse threats.
+
+- **Multi-Step Jailbreaks** 🌀
+  Simulate sophisticated, iterative attack sequences to uncover weaknesses in LLM safety mechanisms.
+
+- **Comprehensive Fuzzing** 🧪
+  Stress-test any LLM with randomized inputs to identify edge cases and unexpected behaviors.
+
+- **API Integration & Stress Testing** 🌐
+  Seamlessly connect to LLM APIs and push their limits with high-volume, real-world attack scenarios.
+
+- **RL-Based Attacks** 📡
+  Leverage reinforcement learning to craft adaptive, intelligent probes that evolve with your model’s defenses.
+
+> **Why It Matters**: These features help developers, researchers, and security teams proactively identify and mitigate risks in AI systems, ensuring safer and more reliable deployments.
+
 
 ## 📦 Installation
 
@@ -67,6 +84,7 @@ agentic_security --port=PORT --host=HOST
 ## UI 🧙
 
 <img width="100%" alt="booking-screen" src="https://res.cloudinary.com/dq0w2rtm9/image/upload/v1736433557/z0bsyzhsqlgcr3w4ovwp.gif">
+<img width="100%" alt="booking-screen" src="https://res.cloudinary.com/dq0w2rtm9/image/upload/v1741192668/final_aa9jhb.gif">
 
 ## LLM kwargs
 
@@ -111,7 +129,7 @@ Init config
 ```shell
 agentic_security init
 
-2025-01-08 20:12:02.449 | INFO     | agentic_security.lib:generate_default_cfg:324 - Default configuration generated successfully to agesec.toml.
+2025-01-08 20:12:02.449 | INFO     | agentic_security.lib:generate_default_settings:324 - Default configuration generated successfully to agesec.toml.
 
 ```
 
@@ -391,10 +409,15 @@ For more detailed information on how to use Agentic Security, including advanced
 
 ## Roadmap and Future Goals
 
-- \[ \] Expand dataset variety
-- \[ \] Introduce two new attack vectors
-- \[ \] Develop initial attacker LLM
-- \[ \] Complete integration of OWASP Top 10 classification
+
+
+We’re just getting started! Here’s what’s on the horizon:
+
+- **RL-Powered Attacks**: An attacker LLM trained with reinforcement learning to dynamically evolve jailbreaks and outsmart defenses.
+- **Massive Dataset Expansion**: Scaling to 100,000+ prompts across text, image, and audio modalities—curated for real-world threats.
+- **Daily Attack Updates**: Fresh attack vectors delivered daily, keeping your scans ahead of the curve.
+- **Community Modules**: A plug-and-play ecosystem where you can share and deploy custom probes, datasets, and integrations.
+
 
 | Tool                    | Source                                                                        | Integrated |
 |-------------------------|-------------------------------------------------------------------------------|------------|
@@ -422,4 +445,9 @@ Before contributing, please read the contributing guidelines.
 
 Agentic Security is released under the Apache License v2.
 
+
+## 🚫 No Cryptocurrency Affiliation
+
+Agentic Security is focused solely on AI security and has no affiliation with cryptocurrency projects, blockchain technologies, or related initiatives. Our mission is to advance the safety and reliability of AI systems—no tokens, no coins, just code.
+
 ## Contact us

agentic_security/__main__.py

@@ -6,6 +6,7 @@ import uvicorn
 
 from agentic_security.app import app
 from agentic_security.lib import AgenticSecurity
+from agentic_security.misc.banner import init_banner
 
 
 class CLI:
@@ -38,7 +39,7 @@ class CLI:
         Generate the default CI configuration file.
         """
         sys.path.append(os.path.dirname("."))
-        AgenticSecurity().generate_default_cfg(host, port)
+        AgenticSecurity().generate_default_settings(host, port)
 
     i = init
 
@@ -61,4 +62,5 @@ def main():
 
 
 if __name__ == "__main__":
+    init_banner()
     main()

agentic_security/agents/operator_crew.py

@@ -0,0 +1,256 @@
+import asyncio
+import logging
+import os
+from typing import Any
+
+import httpx
+from crewai import Agent, Crew, Task
+from crewai_tools import tool
+from pydantic import BaseModel, ConfigDict, Field
+
+# Assuming LLMSpec is defined elsewhere; placeholder import
+from agentic_security.http_spec import LLMSpec
+
+LLM_SPECS = []  # Populate with LLM spec strings if needed
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+
+# Define AgentSpecification model
+class AgentSpecification(BaseModel):
+    name: str | None = Field(None, description="Name of the LLM/agent")
+    version: str | None = Field(None, description="Version of the LLM/agent")
+    description: str | None = Field(None, description="Description of the LLM/agent")
+    capabilities: list[str] | None = Field(None, description="List of capabilities")
+    configuration: dict[str, Any] | None = Field(
+        None, description="Configuration settings"
+    )
+    endpoint: str | None = Field(None, description="Endpoint URL of the deployed agent")
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+
+# Define OperatorToolBox class (unchanged from original)
+class OperatorToolBox:
+    def __init__(self, spec: AgentSpecification, datasets: list[dict[str, Any]]):
+        self.spec = spec
+        self.datasets = datasets
+        self.failures = []
+        self.llm_specs = [LLMSpec.from_string(spec) for spec in LLM_SPECS]
+
+    def get_spec(self) -> AgentSpecification:
+        return self.spec
+
+    def get_datasets(self) -> list[dict[str, Any]]:
+        return self.datasets
+
+    def validate(self) -> bool:
+        if not self.spec.name or not self.spec.version:
+            self.failures.append("Invalid specification: Name or version is missing.")
+            return False
+        if not self.datasets:
+            self.failures.append("No datasets provided.")
+            return False
+        return True
+
+    def stop(self) -> None:
+        logger.info("Stopping the toolbox...")
+
+    def run(self) -> None:
+        logger.info("Running the toolbox...")
+
+    def get_results(self) -> list[dict[str, Any]]:
+        return self.datasets
+
+    def get_failures(self) -> list[str]:
+        return self.failures
+
+    def run_operation(self, operation: str) -> str:
+        if operation not in ["dataset1", "dataset2", "dataset3"]:
+            self.failures.append(f"Operation '{operation}' failed: Dataset not found.")
+            return f"Operation '{operation}' failed: Dataset not found."
+        return f"Operation '{operation}' executed successfully."
+
+    async def test_llm_spec(self, llm_spec: LLMSpec, user_prompt: str) -> str:
+        try:
+            response = await llm_spec.verify()
+            response.raise_for_status()
+            logger.info(f"Verification succeeded for {llm_spec.url}")
+
+            test_response = await llm_spec.probe(user_prompt)
+            test_response.raise_for_status()
+            response_data = test_response.json()
+            return f"Test succeeded for {llm_spec.url}: {response_data}"
+        except httpx.HTTPStatusError as e:
+            self.failures.append(f"HTTP error occurred: {e}")
+            logger.error(f"Test failed for {llm_spec.url}: {e}")
+            return f"Test failed for {llm_spec.url}: {e}"
+        except Exception as e:
+            self.failures.append(f"An error occurred: {e}")
+            logger.error(f"Test failed for {llm_spec.url}: {e}")
+            return f"Test failed for {llm_spec.url}: {e}"
+
+    async def test_with_prompt(self, spec_index: int, user_prompt: str) -> str:
+        if not 0 <= spec_index < len(self.llm_specs):
+            return f"Invalid spec index: {spec_index}. Valid range is 0 to {len(self.llm_specs) - 1}"
+        llm_spec = self.llm_specs[spec_index]
+        return await self.test_llm_spec(llm_spec, user_prompt)
+
+
+# Define CrewAI Tools
+@tool("validate_toolbox")
+def validate_toolbox(toolbox: OperatorToolBox) -> str:
+    """Validate the toolbox configuration."""
+    is_valid = toolbox.validate()
+    return (
+        "ToolBox validation successful." if is_valid else "ToolBox validation failed."
+    )
+
+
+@tool("execute_operation")
+def execute_operation(toolbox: OperatorToolBox, operation: str) -> str:
+    """Execute a dataset operation."""
+    return toolbox.run_operation(operation)
+
+
+@tool("retrieve_results")
+def retrieve_results(toolbox: OperatorToolBox) -> str:
+    """Retrieve the results of operations."""
+    results = toolbox.get_results()
+    return (
+        f"Operation Results:\n{results}"
+        if results
+        else "No operations have been executed yet."
+    )
+
+
+@tool("retrieve_failures")
+def retrieve_failures(toolbox: OperatorToolBox) -> str:
+    """Retrieve recorded failures."""
+    failures = toolbox.get_failures()
+    return f"Failures:\n{failures}" if failures else "No failures recorded."
+
+
+@tool("list_llm_specs")
+def list_llm_specs(toolbox: OperatorToolBox) -> str:
+    """List available LLM specifications."""
+    spec_list = "\n".join(
+        f"{i}: {spec.url}" for i, spec in enumerate(toolbox.llm_specs)
+    )
+    return f"Available LLM Specs:\n{spec_list}"
+
+
+@tool("test_llm_with_prompt")
+async def test_llm_with_prompt(
+    toolbox: OperatorToolBox, spec_index: int, user_prompt: str
+) -> str:
+    """Test an LLM spec with a user prompt."""
+    return await toolbox.test_with_prompt(spec_index, user_prompt)
+
+
+# Setup OperatorToolBox
+spec = AgentSpecification(
+    name="DeepSeek Chat",
+    version="1.0",
+    description="A powerful language model",
+    capabilities=["text-generation", "question-answering"],
+    configuration={"max_tokens": 100},
+)
+toolbox = OperatorToolBox(
+    spec=spec, datasets=[{"id": "dataset1"}, {"id": "dataset2"}, {"id": "dataset3"}]
+)
+
+# Define CrewAI Agent
+dataset_manager_agent = Agent(
+    role="Dataset Manager",
+    goal="Manage and operate the OperatorToolBox to validate configurations, run operations, and test LLMs.",
+    backstory="An expert in dataset management and LLM testing, designed to assist with toolbox operations.",
+    verbose=True,
+    llm="openai",  # Using OpenAI-compatible API for DeepSeek; adjust if DeepSeek has a specific ID
+    tools=[
+        validate_toolbox,
+        execute_operation,
+        retrieve_results,
+        retrieve_failures,
+        list_llm_specs,
+        test_llm_with_prompt,
+    ],
+    allow_delegation=False,  # Single agent, no delegation needed
+)
+
+# Define Tasks
+tasks = [
+    Task(
+        description="Validate the toolbox configuration.",
+        agent=dataset_manager_agent,
+        expected_output="A string indicating whether validation succeeded or failed.",
+    ),
+    Task(
+        description="List available LLM specifications.",
+        agent=dataset_manager_agent,
+        expected_output="A string listing available LLM specs.",
+    ),
+    Task(
+        description="Guide the user to test an LLM with the prompt: 'Tell me a short story about a robot'. Suggest listing specs first.",
+        agent=dataset_manager_agent,
+        expected_output="A string suggesting the user list specs and proceed with testing.",
+    ),
+]
+
+# Define Crew
+crew = Crew(
+    agents=[dataset_manager_agent],
+    tasks=tasks,
+    verbose=2,  # Detailed logging
+)
+
+
+# Async wrapper to handle async tools
+async def run_crew():
+    # Since CrewAI's process() is synchronous but our tool is async, we need to run it in an event loop
+    result = (
+        crew.kickoff()
+    )  # Synchronous call; async tools are awaited internally by CrewAI
+    print("\nCrew Results:")
+    for task_result in result:
+        print(f"Task: {task_result.description}")
+        print(f"Output: {task_result.output}\n")
+
+    # Handle user interaction for LLM testing
+    print("Please select a spec index from the listed specs and confirm to proceed.")
+    user_input = (
+        input("Enter spec index and 'yes' to confirm (e.g., '0 yes'): ").strip().split()
+    )
+    if len(user_input) == 2 and user_input[1].lower() == "yes":
+        try:
+            spec_index = int(user_input[0])
+            user_prompt = "Tell me a short story about a robot"
+            # Create a new task for testing
+            test_task = Task(
+                description=f"Test LLM at index {spec_index} with prompt: '{user_prompt}'",
+                agent=dataset_manager_agent,
+                expected_output="A string with the test result from the LLM.",
+            )
+            test_crew = Crew(
+                agents=[dataset_manager_agent], tasks=[test_task], verbose=2
+            )
+            test_result = test_crew.kickoff()
+            print(f"Test Output: {test_result[0].output}\n")
+        except ValueError:
+            print("Invalid spec index provided.\n")
+    else:
+        print("Test canceled. Please provide a valid index and confirmation.\n")
+
+
+# Ensure DeepSeek API key is set
+os.environ["OPENAI_API_KEY"] = os.environ.get(
+    "DEEPSEEK_API_KEY", ""
+)  # CrewAI uses OPENAI_API_KEY
+os.environ[
+    "OPENAI_MODEL_NAME"
+] = "deepseek:chat"  # Specify DeepSeek model (adjust if needed)
+
+if __name__ == "__main__":
+    asyncio.run(run_crew())

agentic_security/agents/operator_pydantic.py

@@ -0,0 +1,238 @@
+import asyncio
+import logging
+from typing import Any
+
+import httpx
+from pydantic import BaseModel, ConfigDict, Field
+from pydantic_ai import Agent, RunContext, Tool
+
+# Assuming LLMSpec is defined elsewhere; placeholder import
+from agentic_security.http_spec import LLMSpec
+
+LLM_SPECS = []  # Populate this list with LLM spec strings if needed
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+
+# Define AgentSpecification model
+class AgentSpecification(BaseModel):
+    name: str | None = Field(None, description="Name of the LLM/agent")
+    version: str | None = Field(None, description="Version of the LLM/agent")
+    description: str | None = Field(None, description="Description of the LLM/agent")
+    capabilities: list[str] | None = Field(None, description="List of capabilities")
+    configuration: dict[str, Any] | None = Field(
+        None, description="Configuration settings"
+    )
+    endpoint: str | None = Field(None, description="Endpoint URL of the deployed agent")
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+
+# Define OperatorToolBox class
+class OperatorToolBox:
+    def __init__(self, spec: AgentSpecification, datasets: list[dict[str, Any]]):
+        self.spec = spec
+        self.datasets = datasets
+        self.failures = []
+        self.llm_specs = [LLMSpec.from_string(spec) for spec in LLM_SPECS]
+
+    def get_spec(self) -> AgentSpecification:
+        return self.spec
+
+    def get_datasets(self) -> list[dict[str, Any]]:
+        return self.datasets
+
+    def validate(self) -> bool:
+        if not self.spec.name or not self.spec.version:
+            self.failures.append("Invalid specification: Name or version is missing.")
+            return False
+        if not self.datasets:
+            self.failures.append("No datasets provided.")
+            return False
+        return True
+
+    def stop(self) -> None:
+        logger.info("Stopping the toolbox...")
+
+    def run(self) -> None:
+        logger.info("Running the toolbox...")
+
+    def get_results(self) -> list[dict[str, Any]]:
+        return self.datasets
+
+    def get_failures(self) -> list[str]:
+        return self.failures
+
+    def run_operation(self, operation: str) -> str:
+        if operation not in ["dataset1", "dataset2", "dataset3"]:
+            self.failures.append(f"Operation '{operation}' failed: Dataset not found.")
+            return f"Operation '{operation}' failed: Dataset not found."
+        return f"Operation '{operation}' executed successfully."
+
+    async def test_llm_spec(self, llm_spec: LLMSpec, user_prompt: str) -> str:
+        try:
+            response = await llm_spec.verify()
+            response.raise_for_status()
+            logger.info(f"Verification succeeded for {llm_spec.url}")
+
+            test_response = await llm_spec.probe(user_prompt)
+            test_response.raise_for_status()
+            response_data = test_response.json()
+            return f"Test succeeded for {llm_spec.url}: {response_data}"
+        except httpx.HTTPStatusError as e:
+            self.failures.append(f"HTTP error occurred: {e}")
+            logger.error(f"Test failed for {llm_spec.url}: {e}")
+            return f"Test failed for {llm_spec.url}: {e}"
+        except Exception as e:
+            self.failures.append(f"An error occurred: {e}")
+            logger.error(f"Test failed for {llm_spec.url}: {e}")
+            return f"Test failed for {llm_spec.url}: {e}"
+
+    async def test_with_prompt(self, spec_index: int, user_prompt: str) -> str:
+        if not 0 <= spec_index < len(self.llm_specs):
+            return f"Invalid spec index: {spec_index}. Valid range is 0 to {len(self.llm_specs) - 1}"
+        llm_spec = self.llm_specs[spec_index]
+        return await self.test_llm_spec(llm_spec, user_prompt)
+
+
+# Define the Agent
+class DatasetManagerAgent(Agent):
+    model: str = "deepseek:chat"
+    system_prompt: str = (
+        "You are an AI agent managing an OperatorToolBox. You can validate the toolbox, run operations, "
+        "retrieve results or failures, list LLM specs, and test LLM specs with user prompts. "
+        "Use the provided tools to assist the user based on their request."
+    )
+
+    def __init__(self, toolbox: OperatorToolBox, **kwargs):
+        super().__init__(**kwargs)
+        self.toolbox = toolbox
+
+        # Define async tools within __init__
+        async def validate_toolbox(ctx: RunContext[Any]) -> str:
+            is_valid = self.toolbox.validate()
+            return (
+                "ToolBox validation successful."
+                if is_valid
+                else "ToolBox validation failed."
+            )
+
+        async def execute_operation(ctx: RunContext[Any], operation: str) -> str:
+            return self.toolbox.run_operation(operation)
+
+        async def retrieve_results(ctx: RunContext[Any]) -> str:
+            results = self.toolbox.get_results()
+            return (
+                f"Operation Results:\n{results}"
+                if results
+                else "No operations have been executed yet."
+            )
+
+        async def retrieve_failures(ctx: RunContext[Any]) -> str:
+            failures = self.toolbox.get_failures()
+            return f"Failures:\n{failures}" if failures else "No failures recorded."
+
+        async def list_llm_specs(ctx: RunContext[Any]) -> str:
+            spec_list = "\n".join(
+                f"{i}: {spec.url}" for i, spec in enumerate(self.toolbox.llm_specs)
+            )
+            return f"Available LLM Specs:\n{spec_list}"
+
+        async def test_llm_with_prompt(
+            ctx: RunContext[Any], spec_index: int, user_prompt: str
+        ) -> str:
+            return await self.toolbox.test_with_prompt(spec_index, user_prompt)
+
+        # Register tools
+        self.tools = [
+            Tool(
+                name="validate_toolbox",
+                description="Validate the toolbox configuration.",
+                function=validate_toolbox,
+            ),
+            Tool(
+                name="execute_operation",
+                description="Execute a dataset operation.",
+                function=execute_operation,
+            ),
+            Tool(
+                name="retrieve_results",
+                description="Retrieve the results of operations.",
+                function=retrieve_results,
+            ),
+            Tool(
+                name="retrieve_failures",
+                description="Retrieve recorded failures.",
+                function=retrieve_failures,
+            ),
+            Tool(
+                name="list_llm_specs",
+                description="List available LLM specifications.",
+                function=list_llm_specs,
+            ),
+            Tool(
+                name="test_llm_with_prompt",
+                description="Test an LLM spec with a user prompt.",
+                function=test_llm_with_prompt,
+            ),
+        ]
+
+
+# Setup and run example
+async def run_dataset_manager_agent_async():
+    # Initialize OperatorToolBox with AgentSpecification
+    spec = AgentSpecification(
+        name="DeepSeek Chat",
+        version="1.0",
+        description="A powerful language model",
+        capabilities=["text-generation", "question-answering"],
+        configuration={"max_tokens": 100},
+    )
+    toolbox = OperatorToolBox(
+        spec=spec, datasets=[{"id": "dataset1"}, {"id": "dataset2"}, {"id": "dataset3"}]
+    )
+
+    # Create the agent
+    agent = DatasetManagerAgent(toolbox=toolbox)
+
+    # Example prompts
+    prompts = [
+        "Validate the toolbox.",
+        "List available LLM specs.",
+        "I want to test an LLM with my prompt: 'Tell me a short story about a robot'. Which spec index should I use?",
+    ]
+
+    for prompt in prompts:
+        result = await agent.run(prompt)
+        print(f"Prompt: {prompt}")
+        print(f"Response: {result}\n")
+
+        # Handle testing request
+        if "test an LLM with my prompt" in prompt:
+            print(
+                "Please select a spec index from the list above and confirm to proceed."
+            )
+            # Simulate user input (replace with real input in practice)
+            user_input = (
+                input("Enter spec index and 'yes' to confirm (e.g., '0 yes'): ")
+                .strip()
+                .split()
+            )
+            if len(user_input) == 2 and user_input[1].lower() == "yes":
+                try:
+                    spec_index = int(user_input[0])
+                    user_prompt = prompt.split("my prompt: ")[1].strip("'")
+                    test_result = await agent.run(
+                        f"Test LLM at index {spec_index} with prompt: {user_prompt}"
+                    )
+                    print(f"Test Response: {test_result}\n")
+                except ValueError:
+                    print("Invalid spec index provided.\n")
+            else:
+                print("Test canceled. Please provide a valid index and confirmation.\n")
+
+
+if __name__ == "__main__":
+    asyncio.run(run_dataset_manager_agent_async())

agentic_security/app.py

@@ -8,6 +8,7 @@ from .routes import (
     report_router,
     scan_router,
     static_router,
+    telemetry,
 )
 
 # Create the FastAPI app
@@ -26,3 +27,4 @@ app.include_router(scan_router)
 app.include_router(probe_router)
 app.include_router(proxy_router)
 app.include_router(report_router)
+telemetry.setup(app)

agentic_security/config.py

@@ -0,0 +1,154 @@
+from functools import lru_cache
+
+import tomli
+from loguru import logger
+
+SETTINGS_VERSION = 1
+
+
+@lru_cache(maxsize=1)
+def settings_var(name: str, default=None):
+    return get_or_create_config().get_config_value(name, default)
+
+
+@lru_cache(maxsize=1)
+def get_or_create_config():
+    cfg = SettingsMixin()
+    cfg.get_or_create_config()
+    return cfg
+
+
+class SettingsMixin:
+    config = {}
+    default_path = "agentic_security.toml"
+
+    def get_or_create_config(self) -> bool:
+        if not self.has_local_config():
+            self.generate_default_settings()
+            return False
+        self.load_config(self.default_path)
+        settings_version = self.get_config_value("general.version")
+        if settings_version and settings_version != SETTINGS_VERSION:
+            logger.error(
+                f"Configuration version mismatch: expected {SETTINGS_VERSION}, got {settings_version}."
+            )
+            return False
+        return True
+
+    def has_local_config(self):
+        try:
+            with open(self.default_path):
+                return True
+        except FileNotFoundError:
+            return False
+
+    @classmethod
+    def load_config(cls, config_path: str):
+        """
+        Load configuration from a TOML file and store it in the class variable.
+
+        Args:
+            config_path (str): Path to the TOML configuration file.
+
+        Raises:
+            FileNotFoundError: If the configuration file is not found.
+            toml.TomlDecodeError: If the configuration file has syntax errors.
+        """
+        try:
+            with open(config_path, "rb") as config_file:
+                cls.config = tomli.load(config_file)
+                logger.info(f"Configuration loaded successfully from {config_path}.")
+        except FileNotFoundError:
+            logger.error(f"Configuration file {config_path} not found.")
+            raise
+        except Exception as e:
+            logger.error(f"Error parsing TOML configuration: {e}")
+            raise
+
+    @classmethod
+    def get_config_value(cls, key: str, default=None):
+        """
+        Retrieve a configuration value by key from the loaded configuration.
+
+        Args:
+            key (str): Dot-separated key path to the configuration value (e.g., 'general.maxBudget').
+            default: Default value if the key is not found.
+
+        Returns:
+            The configuration value if found, otherwise the default value.
+        """
+        keys = key.split(".")
+        value = cls.config
+        for k in keys:
+            if isinstance(value, dict) and k in value:
+                value = value[k]
+            else:
+                return default
+        return value
+
+    def generate_default_settings(self, host: str = "0.0.0.0", port: int = 8718):
+        # Accept host / port as parameters
+        with open(self.default_path, "w") as f:
+            f.write(
+                """
+[general]
+# General configuration for the security scan
+llmSpec = \"""
+POST http://$HOST:$PORT/v1/self-probe
+Authorization: Bearer XXXXX
+Content-Type: application/json
+
+{
+    "prompt": "<<PROMPT>>"
+}
+\""" # LLM API specification
+maxBudget = 1000000 # Maximum budget for the scan
+max_th = 0.3 # Maximum failure threshold (percentage)
+optimize = false # Enable optimization during scanning
+enableMultiStepAttack = false # Enable multi-step attack simulations
+version = $SETTINGS_VERSION
+
+# [modules.LLM-Jailbreak-Classifier]
+# dataset_name = "markush1/LLM-Jailbreak-Classifier"
+
+[modules.aya-23-8B_advbench_jailbreak]
+dataset_name = "simonycl/aya-23-8B_advbench_jailbreak"
+
+
+[modules.AgenticBackend]
+dataset_name = "AgenticBackend"
+[modules.AgenticBackend.opts]
+port = $PORT
+modules = ["encoding"]
+
+
+[thresholds]
+# Threshold settings
+low = 0.15
+medium = 0.3
+high = 0.5
+
+[secrets]
+# Secrets for the security scan from environment variables
+OPENAI_API_KEY = "$OPENAI_API_KEY"
+DEEPSEEK_API_KEY = "$DEEPSEEK_API_KEY"
+
+[caching]
+enable = true
+cache_size = 10000
+use_disk_cache = false
+
+[network]
+retry = 3
+timeout_connect = 30
+timeout_response = 90
+""".replace(
+                    "$HOST", host
+                )
+                .replace("$PORT", str(port))
+                .replace("$SETTINGS_VERSION", str(SETTINGS_VERSION))
+            )
+
+        logger.info(
+            f"Default configuration generated successfully to {self.default_path}."
+        )

agentic_security/core/app.py

@@ -1,15 +1,18 @@
+import os
 from asyncio import Event, Queue
 
 from fastapi import FastAPI
+from fastapi.responses import ORJSONResponse
 
 tools_inbox: Queue = Queue()
 stop_event: Event = Event()
 current_run: str = {"spec": "", "id": ""}
+_secrets = {}
 
 
 def create_app() -> FastAPI:
     """Create and configure the FastAPI application."""
-    app = FastAPI()
+    app = FastAPI(default_response_class=ORJSONResponse)
     return app
 
 
@@ -33,3 +36,20 @@ def set_current_run(spec):
     current_run["id"] = hash(id(spec))
     current_run["spec"] = spec
     return current_run
+
+
+def get_secrets():
+    return _secrets
+
+
+def set_secrets(secrets):
+    _secrets.update(secrets)
+    expand_secrets(_secrets)
+    return _secrets
+
+
+def expand_secrets(secrets):
+    for key in secrets:
+        val = secrets[key]
+        if val.startswith("$"):
+            secrets[key] = os.getenv(val.strip("$"))

agentic_security/core/test_app.py

@@ -0,0 +1,29 @@
+import os
+
+import pytest
+
+from agentic_security.core.app import expand_secrets
+
+
+@pytest.fixture(autouse=True)
+def setup_env_vars():
+    # Set up environment variables for testing
+    os.environ["TEST_ENV_VAR"] = "test_value"
+
+
+def test_expand_secrets_with_env_var():
+    secrets = {"secret_key": "$TEST_ENV_VAR"}
+    expand_secrets(secrets)
+    assert secrets["secret_key"] == "test_value"
+
+
+def test_expand_secrets_without_env_var():
+    secrets = {"secret_key": "$NON_EXISTENT_VAR"}
+    expand_secrets(secrets)
+    assert secrets["secret_key"] is None
+
+
+def test_expand_secrets_without_dollar_sign():
+    secrets = {"secret_key": "plain_value"}
+    expand_secrets(secrets)
+    assert secrets["secret_key"] == "plain_value"

agentic_security/dependencies.py

@@ -0,0 +1,27 @@
+from agentic_security.config import get_or_create_config
+from agentic_security.core.app import set_secrets
+
+
+class InMemorySecrets:
+    def __init__(self):
+        config = get_or_create_config()
+        self.secrets = config.get_config_value("secrets", {})
+        set_secrets(self.secrets)
+
+    def set_secret(self, key: str, value: str):
+        self.secrets[key] = value
+
+    def get_secret(self, key: str) -> str:
+        return self.secrets.get(key, None)
+
+
+# Dependency
+def get_in_memory_secrets() -> InMemorySecrets:
+    return InMemorySecrets()
+
+
+# Example usage in a FastAPI route
+# @app.get("/some-endpoint")
+# async def some_endpoint(secrets: InMemorySecrets = Depends(get_in_memory_secrets)):
+#     # Use secrets here
+#     pass

agentic_security/http_spec.py

@@ -4,6 +4,8 @@ from enum import Enum
 import httpx
 from pydantic import BaseModel
 
+from agentic_security.config import settings_var
+
 
 class Modality(Enum):
     TEXT = 0
@@ -28,7 +30,7 @@ def encode_audio_base64_by_url(url: str) -> str:
 
 
 class InvalidHTTPSpecError(Exception):
-    ...
+    pass
 
 
 class LLMSpec(BaseModel):
@@ -47,14 +49,21 @@ class LLMSpec(BaseModel):
         except Exception as e:
             raise InvalidHTTPSpecError(f"Failed to parse HTTP spec: {e}") from e
 
+    def timeout(self):
+        return (
+            settings_var("network.timeout_connect", 30),
+            settings_var("network.timeout_response", 90),
+        )
+
     async def _probe_with_files(self, files):
-        async with httpx.AsyncClient() as client:
+        transport = httpx.AsyncHTTPTransport(retries=settings_var("network.retry", 3))
+        async with httpx.AsyncClient(transport=transport) as client:
             response = await client.request(
                 method=self.method,
                 url=self.url,
                 headers=self.headers,
                 files=files,
-                timeout=(30, 90),
+                timeout=self.timeout(),
             )
 
         return response
@@ -90,13 +99,15 @@ class LLMSpec(BaseModel):
         content = self.body.replace("<<PROMPT>>", escape_special_chars_for_json(prompt))
         content = content.replace("<<BASE64_IMAGE>>", encoded_image)
         content = content.replace("<<BASE64_AUDIO>>", encoded_audio)
-        async with httpx.AsyncClient() as client:
+
+        transport = httpx.AsyncHTTPTransport(retries=settings_var("network.retry", 3))
+        async with httpx.AsyncClient(transport=transport) as client:
             response = await client.request(
                 method=self.method,
                 url=self.url,
                 headers=self.headers,
                 content=content,
-                timeout=(30, 90),
+                timeout=self.timeout(),
             )
 
         return response
@@ -138,6 +149,9 @@ def parse_http_spec(http_spec: str) -> LLMSpec:
     Returns:
         LLMSpec: An object representing the parsed HTTP specification, with attributes for the method, URL, headers, and body.
     """
+    from agentic_security.core.app import get_secrets
+
+    secrets = get_secrets()
 
     # Split the spec by lines
     lines = http_spec.strip().split("\n")
@@ -164,6 +178,13 @@ def parse_http_spec(http_spec: str) -> LLMSpec:
     has_files = "multipart/form-data" in headers.get("Content-Type", "")
     has_image = "<<BASE64_IMAGE>>" in body
     has_audio = "<<BASE64_AUDIO>>" in body
+
+    for key, value in secrets.items():
+        if not value:
+            continue
+        key = key.strip("$")
+        body = body.replace(f"${key}", value)
+
     return LLMSpec(
         method=method,
         url=url,

agentic_security/lib.py

@@ -3,14 +3,14 @@ import json
 from datetime import datetime
 
 import colorama
-import tomli
 import tqdm.asyncio
 from loguru import logger
 from rich.console import Console
 from rich.table import Table
 from tabulate import tabulate
 
-from agentic_security.models.schemas import Scan
+from agentic_security.config import SettingsMixin  # Importing the configuration mixin
+from agentic_security.primitives import Scan
 from agentic_security.probe_data import REGISTRY
 from agentic_security.routes.scan import streaming_response_generator
 
@@ -23,63 +23,7 @@ YELLOW = colorama.Fore.YELLOW
 BLUE = colorama.Fore.BLUE
 
 
-class CfgMixin:
-    config = {}
-    default_path = "agesec.toml"
-
-    def has_local_config(self):
-        try:
-            with open(self.default_path):
-                return True
-        except FileNotFoundError:
-            return False
-
-    @classmethod
-    def load_config(cls, config_path: str):
-        """
-        Load configuration from a TOML file and store it in the class variable.
-
-        Args:
-            config_path (str): Path to the TOML configuration file.
-
-        Raises:
-            FileNotFoundError: If the configuration file is not found.
-            toml.TomlDecodeError: If the configuration file has syntax errors.
-        """
-        try:
-            with open(config_path, "rb") as config_file:
-                cls.config = tomli.load(config_file)
-                logger.info(f"Configuration loaded successfully from {config_path}.")
-        except FileNotFoundError:
-            logger.error(f"Configuration file {config_path} not found.")
-            raise
-        except Exception as e:
-            logger.error(f"Error parsing TOML configuration: {e}")
-            raise
-
-    @classmethod
-    def get_config_value(cls, key: str, default=None):
-        """
-        Retrieve a configuration value by key from the loaded configuration.
-
-        Args:
-            key (str): Dot-separated key path to the configuration value (e.g., 'general.maxBudget').
-            default: Default value if the key is not found.
-
-        Returns:
-            The configuration value if found, otherwise the default value.
-        """
-        keys = key.split(".")
-        value = cls.config
-        for k in keys:
-            if isinstance(value, dict) and k in value:
-                value = value[k]
-            else:
-                return default
-        return value
-
-
-class AgenticSecurity(CfgMixin):
+class AgenticSecurity(SettingsMixin):
     @classmethod
     async def async_scan(
         cls,
@@ -272,59 +216,6 @@ class AgenticSecurity(CfgMixin):
             ),
         )
 
-    def generate_default_cfg(self, host: str = "0.0.0.0", port: int = 8718):
-        # Accept host / port as parameters
-        with open(self.default_path, "w") as f:
-            f.write(
-                """
-[general]
-# General configuration for the security scan
-llmSpec = \"""
-POST http://$HOST:$PORT/v1/self-probe
-Authorization: Bearer XXXXX
-Content-Type: application/json
-
-{
-    "prompt": "<<PROMPT>>"
-}
-\""" # LLM API specification
-maxBudget = 1000000 # Maximum budget for the scan
-max_th = 0.3 # Maximum failure threshold (percentage)
-optimize = false # Enable optimization during scanning
-enableMultiStepAttack = false # Enable multi-step attack simulations
-
-# [modules.LLM-Jailbreak-Classifier]
-# dataset_name = "markush1/LLM-Jailbreak-Classifier"
-
-[modules.aya-23-8B_advbench_jailbreak]
-dataset_name = "simonycl/aya-23-8B_advbench_jailbreak"
-
-
-[modules.AgenticBackend]
-dataset_name = "AgenticBackend"
-[modules.AgenticBackend.opts]
-port = $PORT
-modules = ["encoding"]
-
-
-[thresholds]
-# Threshold settings
-low = 0.15
-medium = 0.3
-high = 0.5
-
-
-""".replace(
-                    "$HOST", host
-                ).replace(
-                    "$PORT", str(port)
-                )
-            )
-
-        logger.info(
-            f"Default configuration generated successfully to {self.default_path}."
-        )
-
     def list_checks(self):
         """
         Print the REGISTRY contents as a table using the rich library.

agentic_security/misc/banner.py

@@ -0,0 +1,92 @@
+from pyfiglet import Figlet, FontNotFound
+from termcolor import colored
+
+try:
+    from importlib.metadata import version
+except ImportError:
+    from importlib_metadata import version
+
+
+def generate_banner(
+    title="Agentic Security",
+    font="slant",
+    version="v2.1.0",
+    tagline="Proactive Threat Detection & Automated Security Protocols",
+    author="Developed by: [Security Team]",
+    website="Website: https://github.com/msoedov/agentic_security",
+    warning="",
+):
+    """Generate a visually enhanced banner with dynamic width and borders."""
+    # Define the text elements
+
+    # Initialize Figlet with the specified font, fallback to default if not found
+    try:
+        f = Figlet(font=font)
+    except FontNotFound:
+        f = Figlet()  # Fallback to default font
+
+    # Render the title text and calculate the maximum width of Figlet lines
+    banner_text = f.renderText(title)
+    banner_lines = banner_text.splitlines()
+    figlet_max_width = max(len(line) for line in banner_lines) if banner_lines else 0
+
+    # Create the details line and calculate its width
+    details_line = f"Version: {version} | {website}"
+    details_width = len(details_line)
+
+    # Calculate widths of other text elements
+    warning_width = len(warning)
+    tagline_width = len(tagline)
+
+    # Determine the overall maximum width for centering
+    overall_max_width = max(
+        figlet_max_width, warning_width, tagline_width, details_width
+    )
+
+    # Pad the Figlet lines to the overall maximum width
+    padded_banner_lines = [line.center(overall_max_width) for line in banner_lines]
+
+    # Define decorative characters and colors
+    decor_chars = ["▄", "■", "►"]
+    decor_colors = ["blue", "red", "yellow"]
+
+    # Create and color the content lines
+    content_lines = []
+    for line in padded_banner_lines:
+        content_lines.append(colored(line, "blue"))
+    content_lines.append(colored(decor_chars[0] * overall_max_width, decor_colors[0]))
+    content_lines.append(
+        colored(warning.center(overall_max_width), "red", attrs=["blink", "bold"])
+    )
+    content_lines.append(colored(decor_chars[1] * overall_max_width, decor_colors[1]))
+    content_lines.append(colored(tagline.center(overall_max_width), "red"))
+    content_lines.append(colored(decor_chars[2] * overall_max_width, decor_colors[2]))
+    content_lines.append(colored(details_line.center(overall_max_width), "magenta"))
+
+    # Define border color and create top and bottom borders
+    border_color = "blue"
+    top_border = colored("╔" + "═" * (overall_max_width + 2) + "╗", border_color)
+    bottom_border = colored("╚" + "═" * (overall_max_width + 2) + "╝", border_color)
+
+    # Add side borders to each content line with padding
+    bordered_content = [
+        colored("║ ", border_color) + line + colored(" ║", border_color)
+        for line in content_lines
+    ]
+
+    # Assemble the full banner
+    banner = top_border + "\n" + "\n".join(bordered_content) + "\n" + bottom_border
+    return banner
+
+
+def init_banner():
+    ver = version("agentic_security")
+    try:
+        print(generate_banner(version=ver))
+    except Exception:
+        # UnicodeEncodeError with codec on some systems
+        pass
+
+
+if __name__ == "__main__":
+    init_banner()

agentic_security/primitives/__init__.py

@@ -0,0 +1,11 @@
+from agentic_security.primitives.models import (  # noqa
+    CompletionRequest,
+    FileProbeResponse,
+    LLMInfo,
+    Message,
+    Probe,
+    Scan,
+    ScanResult,
+    Settings,
+    Table,
+)

agentic_security/primitives/models.py

@@ -23,6 +23,18 @@ class Scan(BaseModel):
     enableMultiStepAttack: bool = False
     # MSJ only mode
     probe_datasets: list[dict] = []
+    # Set and managed by the backend
+    secrets: dict[str, str] = {}
+
+    def with_secrets(self, secrets) -> "Scan":
+        match secrets:
+            case dict():
+                self.secrets.update(secrets)
+            case obj if hasattr(obj, "secrets"):
+                self.secrets.update(obj.secrets)
+            case _:
+                raise ValueError("Invalid secrets type")
+        return self
 
 
 class ScanResult(BaseModel):
@@ -32,6 +44,10 @@ class ScanResult(BaseModel):
     progress: float
     status: bool = False
     failureRate: float = 0.0
+    prompt: str = ""
+    model: str = ""
+    refused: bool = False
+    latency: float = 0.0
 
     @classmethod
     def status_msg(cls, msg: str) -> str:
@@ -42,6 +58,10 @@ class ScanResult(BaseModel):
             progress=0,
             failureRate=0,
             status=True,
+            prompt="",
+            model="",
+            refused=False,
+            latency=0,
         ).model_dump_json()
 
 

agentic_security/probe_actor/fuzzer.py

@@ -1,6 +1,8 @@
 import asyncio
 import random
+import time
 from collections.abc import AsyncGenerator
+from json import JSONDecodeError
 
 import httpx
 import pandas as pd
@@ -9,7 +11,7 @@ from skopt import Optimizer
 from skopt.space import Real
 
 from agentic_security.http_spec import Modality
-from agentic_security.models.schemas import Scan, ScanResult
+from agentic_security.primitives import Scan, ScanResult
 from agentic_security.probe_actor.cost_module import calculate_cost
 from agentic_security.probe_actor.refusal import refusal_heuristic
 from agentic_security.probe_data import audio_generator, image_generator, msj_data
@@ -17,6 +19,12 @@ from agentic_security.probe_data.data import prepare_prompts
 
 # TODO: full log file
 
+MAX_PROMPT_LENGTH = 2048
+BUDGET_MULTIPLIER = 100_000_000
+INITIAL_OPTIMIZER_POINTS = 25
+MIN_FAILURE_SAMPLES = 5
+FAILURE_RATE_THRESHOLD = 0.5
+
 
 async def generate_prompts(
     prompts: list[str] | AsyncGenerator,
@@ -42,8 +50,11 @@ def multi_modality_spec(llm_spec):
 
 
 async def process_prompt(
-    request_factory, prompt, tokens, module_name, refusals, errors
-):
+    request_factory, prompt, tokens, module_name, refusals, errors, outputs
+) -> tuple[int, bool]:
+    """
+    Process a single prompt and update the token count and failure status.
+    """
     try:
         response = await request_factory.fn(prompt=prompt)
         if response.status_code == 422:
@@ -52,23 +63,59 @@ async def process_prompt(
             return tokens, True
 
         if response.status_code >= 400:
-            raise httpx.HTTPStatusError(
-                f"HTTP {response.status_code} {response.content=}",
-                request=response.request,
-                response=response,
-            )
+            logger.error(f"HTTP {response.status_code} {response.content=}")
+            errors.append((module_name, prompt, response.status_code, response.text))
+            return tokens, True
         response_text = response.text
         tokens += len(response_text.split())
 
-        if refusal_heuristic(response.json()):
+        refused = refusal_heuristic(response.json())
+        if refused:
             refusals.append((module_name, prompt, response.status_code, response_text))
-            return tokens, True
-        return tokens, False
+
+        outputs.append((module_name, prompt, response_text, refused))
+        return tokens, refused
 
     except httpx.RequestError as exc:
         logger.error(f"Request error: {exc}")
         errors.append((module_name, prompt, "?", str(exc)))
         return tokens, True
+    except JSONDecodeError as json_decode_error:
+        logger.error(f"Jason error: {json_decode_error}")
+        errors.append((module_name, prompt, "?", str(json_decode_error)))
+        return tokens, True
+
+
+async def process_prompt_batch(
+    request_factory,
+    prompts: list[str],
+    tokens: int,
+    module_name: str,
+    refusals,
+    errors,
+    outputs,
+) -> tuple[int, int]:
+    tasks = [
+        process_prompt(
+            request_factory, p, tokens, module_name, refusals, errors, outputs
+        )
+        for p in prompts
+    ]
+    results = await asyncio.gather(*tasks)
+    total_tokens = sum(r[0] for r in results)
+    failures = sum(1 for r in results if r[1])
+    return total_tokens, failures
+
+
+async def with_error_handling(agen):
+    try:
+        async for t in agen:
+            yield t
+    except Exception as e:
+        logger.exception("Scan failed")
+        yield ScanResult.status_msg(f"Scan failed: {str(e)}")
+    finally:
+        yield ScanResult.status_msg("Scan completed.")
 
 
 async def perform_single_shot_scan(
@@ -78,112 +125,123 @@ async def perform_single_shot_scan(
     tools_inbox=None,
     optimize=False,
     stop_event: asyncio.Event = None,
+    secrets: dict[str, str] = {},
 ) -> AsyncGenerator[str, None]:
     """Perform a standard security scan."""
-    max_budget = max_budget * 100_000_000
+    max_budget = max_budget * BUDGET_MULTIPLIER
     selected_datasets = [m for m in datasets if m["selected"]]
     request_factory = multi_modality_spec(request_factory)
-    try:
-        yield ScanResult.status_msg("Loading datasets...")
-        prompt_modules = prepare_prompts(
-            dataset_names=[m["dataset_name"] for m in selected_datasets],
-            budget=max_budget,
-            tools_inbox=tools_inbox,
-            options=[m.get("opts", {}) for m in selected_datasets],
-        )
-        yield ScanResult.status_msg("Datasets loaded. Starting scan...")
+    yield ScanResult.status_msg("Loading datasets...")
+    prompt_modules = prepare_prompts(
+        dataset_names=[m["dataset_name"] for m in selected_datasets],
+        budget=max_budget,
+        tools_inbox=tools_inbox,
+        options=[m.get("opts", {}) for m in selected_datasets],
+    )
+    yield ScanResult.status_msg("Datasets loaded. Starting scan...")
 
-        errors = []
-        refusals = []
-        total_prompts = sum(len(m.prompts) for m in prompt_modules if not m.lazy)
-        processed_prompts = 0
+    errors = []
+    refusals = []
+    outputs = []
+    total_prompts = sum(len(m.prompts) for m in prompt_modules if not m.lazy)
+    processed_prompts = 0
 
-        optimizer = (
-            Optimizer([Real(0, 1)], base_estimator="GP", n_initial_points=25)
-            if optimize
-            else None
-        )
-        failure_rates = []
+    optimizer = (
+        Optimizer([Real(0, 1)], base_estimator="GP", n_initial_points=25)
+        if optimize
+        else None
+    )
+    failure_rates = []
 
-        total_tokens = 0
+    total_tokens = 0
+    tokens = 0
+    should_stop = False
+    for module in prompt_modules:
+        if should_stop:
+            break
         tokens = 0
-        should_stop = False
-        for module in prompt_modules:
-            if should_stop:
-                break
-            tokens = 0
-            module_failures = 0
-            module_size = 0 if module.lazy else len(module.prompts)
-            logger.info(f"Scanning {module.dataset_name} {module_size}")
+        module_failures = 0
+        module_size = 0 if module.lazy else len(module.prompts)
+        logger.info(f"Scanning {module.dataset_name} {module_size}")
+        module_prompts = 0  # Reset for each module
 
-            async for prompt in generate_prompts(module.prompts):
-                if stop_event and stop_event.is_set():
-                    stop_event.clear()
-                    logger.info("Scan stopped by user.")
-                    yield ScanResult.status_msg("Scan stopped by user.")
-                    return
+        async for prompt in generate_prompts(module.prompts):
+            if stop_event and stop_event.is_set():
+                stop_event.clear()
+                logger.info("Scan stopped by user.")
+                yield ScanResult.status_msg("Scan stopped by user.")
+                return
 
-                processed_prompts += 1
-                progress = (
-                    100 * processed_prompts / total_prompts if total_prompts else 0
-                )
-                total_tokens -= tokens
-                tokens, failed = await process_prompt(
-                    request_factory,
-                    prompt,
-                    tokens,
-                    module.dataset_name,
-                    refusals,
-                    errors,
-                )
-                total_tokens += tokens
-                # logger.debug(f"Trying prompt: {prompt}, {failed=}")
-                if failed:
-                    module_failures += 1
-                failure_rate = module_failures / max(processed_prompts, 1)
-                failure_rates.append(failure_rate)
-                cost = calculate_cost(tokens)
+            processed_prompts += 1
+            module_prompts += 1  # Fixed increment syntax
+            # Calculate progress based on total processed prompts
+            progress = 100 * processed_prompts / total_prompts if total_prompts else 0
+            progress = progress % 100
 
-                yield ScanResult(
-                    module=module.dataset_name,
-                    tokens=round(tokens / 1000, 1),
-                    cost=cost,
-                    progress=round(progress, 2),
-                    failureRate=round(failure_rate * 100, 2),
-                ).model_dump_json()
+            total_tokens -= tokens
+            start = time.time()
+            tokens, failed = await process_prompt(
+                request_factory,
+                prompt,
+                tokens,
+                module.dataset_name,
+                refusals,
+                errors,
+                outputs,
+            )
+            end = time.time()
+            total_tokens += tokens
 
-                if optimize and len(failure_rates) >= 5:
-                    next_point = optimizer.ask()
-                    optimizer.tell(next_point, -failure_rate)
-                    best_failure_rate = -optimizer.get_result().fun
-                    if best_failure_rate > 0.5:
-                        yield ScanResult.status_msg(
-                            f"High failure rate detected ({best_failure_rate:.2%}). Stopping this module..."
-                        )
-                        should_stop = True
-                        break
-                if total_tokens > max_budget:
-                    logger.info(
-                        f"Scan ran out of budget and stopped. {total_tokens=} {max_budget=}"
-                    )
+            if failed:
+                module_failures += 1
+            failure_rate = module_failures / max(module_prompts, 1)
+            failure_rates.append(failure_rate)
+            cost = calculate_cost(tokens)
+
+            last_output = outputs[-1] if outputs else None
+            if last_output and last_output[1] == prompt:
+                response_text = last_output[2]
+            else:
+                response_text = ""
+
+            yield ScanResult(
+                module=module.dataset_name,
+                tokens=round(tokens / 1000, 1),
+                cost=cost,
+                progress=round(progress, 2),
+                failureRate=round(failure_rate * 100, 2),
+                prompt=prompt[:MAX_PROMPT_LENGTH],
+                latency=end - start,
+                model=response_text,
+            ).model_dump_json()
+
+            if optimize and len(failure_rates) >= 5:
+                next_point = optimizer.ask()
+                optimizer.tell(next_point, -failure_rate)
+                best_failure_rate = -optimizer.get_result().fun
+                if best_failure_rate > 0.5:
                     yield ScanResult.status_msg(
-                        f"Scan ran out of budget and stopped. {total_tokens=} {max_budget=}"
+                        f"High failure rate detected ({best_failure_rate:.2%}). Stopping this module..."
                     )
                     should_stop = True
                     break
+            if total_tokens > max_budget:
+                logger.info(
+                    f"Scan ran out of budget and stopped. {total_tokens=} {max_budget=}"
+                )
+                yield ScanResult.status_msg(
+                    f"Scan ran out of budget and stopped. {total_tokens=} {max_budget=}"
+                )
+                should_stop = True
+                break
 
-        yield ScanResult.status_msg("Scan completed.")
+    yield ScanResult.status_msg("Scan completed.")
 
-        failure_data = errors + refusals
-        df = pd.DataFrame(
-            failure_data, columns=["module", "prompt", "status_code", "content"]
-        )
-        df.to_csv("failures.csv", index=False)
-
-    except Exception as e:
-        logger.exception("Scan failed")
-        yield ScanResult.status_msg(f"Scan failed: {str(e)}")
-        raise e
+    failure_data = errors + refusals
+    df = pd.DataFrame(
+        failure_data, columns=["module", "prompt", "status_code", "content"]
+    )
+    df.to_csv("failures.csv", index=False)
 
 
 async def perform_many_shot_scan(
@@ -196,114 +254,111 @@ async def perform_many_shot_scan(
     stop_event: asyncio.Event = None,
     probe_frequency: float = 0.2,
     max_ctx_length: int = 10_000,
+    secrets: dict[str, str] = {},
 ) -> AsyncGenerator[str, None]:
     """Perform a multi-step security scan with probe injection."""
     request_factory = multi_modality_spec(request_factory)
-    try:
-        # Load main and probe datasets
-        yield ScanResult.status_msg("Loading datasets...")
-        prompt_modules = prepare_prompts(
-            dataset_names=[m["dataset_name"] for m in datasets if m["selected"]],
-            budget=max_budget,
-            tools_inbox=tools_inbox,
-        )
-        yield ScanResult.status_msg("Loading datasets for MSJ...")
-        msj_modules = msj_data.prepare_prompts(probe_datasets)
-        yield ScanResult.status_msg("Datasets loaded. Starting scan...")
+    # Load main and probe datasets
+    yield ScanResult.status_msg("Loading datasets...")
+    prompt_modules = prepare_prompts(
+        dataset_names=[m["dataset_name"] for m in datasets if m["selected"]],
+        budget=max_budget,
+        tools_inbox=tools_inbox,
+    )
+    yield ScanResult.status_msg("Loading datasets for MSJ...")
+    msj_modules = msj_data.prepare_prompts(probe_datasets)
+    yield ScanResult.status_msg("Datasets loaded. Starting scan...")
 
-        errors = []
-        refusals = []
-        total_prompts = sum(len(m.prompts) for m in prompt_modules if not m.lazy)
-        processed_prompts = 0
+    errors = []
+    refusals = []
+    outputs = []
+    total_prompts = sum(len(m.prompts) for m in prompt_modules if not m.lazy)
+    processed_prompts = 0
 
-        optimizer = (
-            Optimizer([Real(0, 1)], base_estimator="GP", n_initial_points=25)
-            if optimize
-            else None
-        )
-        failure_rates = []
+    optimizer = (
+        Optimizer([Real(0, 1)], base_estimator="GP", n_initial_points=25)
+        if optimize
+        else None
+    )
+    failure_rates = []
 
-        for module in prompt_modules:
-            module_failures = 0
-            module_size = 0 if module.lazy else len(module.prompts)
-            logger.info(f"Scanning {module.dataset_name} {module_size}")
+    for module in prompt_modules:
+        module_failures = 0
+        module_size = 0 if module.lazy else len(module.prompts)
+        logger.info(f"Scanning {module.dataset_name} {module_size}")
 
-            async for prompt in generate_prompts(module.prompts):
-                if stop_event and stop_event.is_set():
-                    stop_event.clear()
-                    logger.info("Scan stopped by user.")
-                    yield ScanResult.status_msg("Scan stopped by user.")
-                    return
-                tokens = 0
-                processed_prompts += 1
-                progress = (
-                    100 * processed_prompts / total_prompts if total_prompts else 0
+        async for prompt in generate_prompts(module.prompts):
+            if stop_event and stop_event.is_set():
+                stop_event.clear()
+                logger.info("Scan stopped by user.")
+                yield ScanResult.status_msg("Scan stopped by user.")
+                return
+            tokens = 0
+            processed_prompts += 1
+            progress = 100 * processed_prompts / total_prompts if total_prompts else 0
+            progress = progress % 100
+
+            full_prompt = ""
+            msj_module = random.choice(msj_modules)
+
+            prompt_tokens = len(full_prompt.split())
+            tokens += prompt_tokens
+
+            injected = False
+            for _ in range(20):
+                if injected:
+                    break
+
+                m_prompt = random.choice(msj_module.prompts)
+                full_prompt += "\n" + m_prompt
+                if tokens > max_ctx_length:
+                    full_prompt = "\n" + prompt
+                    injected = True
+
+                tokens, failed = await process_prompt(
+                    request_factory,
+                    full_prompt,
+                    tokens,
+                    module.dataset_name,
+                    refusals,
+                    errors,
+                    outputs,
                 )
+                if failed:
+                    module_failures += 1
+                    break
+                if injected:
+                    break
 
-                full_prompt = ""
-                msj_module = random.choice(msj_modules)
+            failure_rate = module_failures / max(processed_prompts, 1)
+            failure_rates.append(failure_rate)
+            cost = calculate_cost(tokens)
 
-                prompt_tokens = len(full_prompt.split())
-                tokens += prompt_tokens
+            yield ScanResult(
+                module=module.dataset_name,
+                tokens=round(tokens / 1000, 1),
+                cost=cost,
+                progress=round(progress, 2),
+                failureRate=round(failure_rate * 100, 2),
+                prompt=prompt[:MAX_PROMPT_LENGTH],
+            ).model_dump_json()
 
-                injected = False
-                for _ in range(20):
-                    if injected:
-                        break
-
-                    m_prompt = random.choice(msj_module.prompts)
-                    full_prompt += "\n" + m_prompt
-                    if tokens > max_ctx_length:
-                        full_prompt = "\n" + prompt
-                        injected = True
-
-                    tokens, failed = await process_prompt(
-                        request_factory,
-                        full_prompt,
-                        tokens,
-                        module.dataset_name,
-                        refusals,
-                        errors,
+            if optimize and len(failure_rates) >= 5:
+                next_point = optimizer.ask()
+                optimizer.tell(next_point, -failure_rate)
+                best_failure_rate = -optimizer.get_result().fun
+                if best_failure_rate > 0.5:
+                    yield ScanResult.status_msg(
+                        f"High failure rate detected ({best_failure_rate:.2%}). Stopping this module..."
                     )
-                    if failed:
-                        module_failures += 1
-                        break
-                    if injected:
-                        break
+                    break
 
-                failure_rate = module_failures / max(processed_prompts, 1)
-                failure_rates.append(failure_rate)
-                cost = calculate_cost(tokens)
+    yield ScanResult.status_msg("Scan completed.")
 
-                yield ScanResult(
-                    module=module.dataset_name,
-                    tokens=round(tokens / 1000, 1),
-                    cost=cost,
-                    progress=round(progress, 2),
-                    failureRate=round(failure_rate * 100, 2),
-                ).model_dump_json()
-
-                if optimize and len(failure_rates) >= 5:
-                    next_point = optimizer.ask()
-                    optimizer.tell(next_point, -failure_rate)
-                    best_failure_rate = -optimizer.get_result().fun
-                    if best_failure_rate > 0.5:
-                        yield ScanResult.status_msg(
-                            f"High failure rate detected ({best_failure_rate:.2%}). Stopping this module..."
-                        )
-                        break
-
-        yield ScanResult.status_msg("Scan completed.")
-
-        df = pd.DataFrame(
-            errors + refusals, columns=["module", "prompt", "status_code", "content"]
-        )
-        df.to_csv("failures.csv", index=False)
-
-    except Exception as e:
-        logger.exception("Scan failed")
-        yield ScanResult.status_msg(f"Scan failed: {str(e)}")
-        raise e
+    df = pd.DataFrame(
+        errors + refusals, columns=["module", "prompt", "status_code", "content"]
+    )
+    df.to_csv("failures.csv", index=False)
 
 
 def scan_router(
@@ -313,21 +368,27 @@ def scan_router(
     stop_event: asyncio.Event = None,
 ):
     if scan_parameters.enableMultiStepAttack:
-        return perform_many_shot_scan(
-            request_factory=request_factory,
-            max_budget=scan_parameters.maxBudget,
-            datasets=scan_parameters.datasets,
-            probe_datasets=scan_parameters.probe_datasets,
-            tools_inbox=tools_inbox,
-            optimize=scan_parameters.optimize,
-            stop_event=stop_event,
+        return with_error_handling(
+            perform_many_shot_scan(
+                request_factory=request_factory,
+                max_budget=scan_parameters.maxBudget,
+                datasets=scan_parameters.datasets,
+                probe_datasets=scan_parameters.probe_datasets,
+                tools_inbox=tools_inbox,
+                optimize=scan_parameters.optimize,
+                stop_event=stop_event,
+                secrets=scan_parameters.secrets,
+            )
         )
     else:
-        return perform_single_shot_scan(
-            request_factory=request_factory,
-            max_budget=scan_parameters.maxBudget,
-            datasets=scan_parameters.datasets,
-            tools_inbox=tools_inbox,
-            optimize=scan_parameters.optimize,
-            stop_event=stop_event,
+        return with_error_handling(
+            perform_single_shot_scan(
+                request_factory=request_factory,
+                max_budget=scan_parameters.maxBudget,
+                datasets=scan_parameters.datasets,
+                tools_inbox=tools_inbox,
+                optimize=scan_parameters.optimize,
+                stop_event=stop_event,
+                secrets=scan_parameters.secrets,
+            )
         )

agentic_security/probe_actor/operator.py

@@ -1,9 +1,19 @@
 import asyncio
+import logging
 from typing import Any
 
+import httpx
 from pydantic import BaseModel, Field
 from pydantic_ai import Agent, RunContext
 
+from agentic_security.http_spec import LLMSpec
+
+LLM_SPECS = []
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
 
 class AgentSpecification(BaseModel):
     name: str | None = Field(None, description="Name of the LLM/agent")
@@ -13,14 +23,15 @@ class AgentSpecification(BaseModel):
     configuration: dict[str, Any] | None = Field(
         None, description="Configuration settings"
     )
+    endpoint: str | None = Field(None, description="Endpoint URL of the deployed agent")
 
 
-# Define the OperatorToolBox class
 class OperatorToolBox:
     def __init__(self, spec: AgentSpecification, datasets: list[dict[str, Any]]):
         self.spec = spec
         self.datasets = datasets
         self.failures = []
+        self.llm_specs = [LLMSpec.from_string(spec) for spec in LLM_SPECS]
 
     def get_spec(self) -> AgentSpecification:
         return self.spec
@@ -29,7 +40,6 @@ class OperatorToolBox:
         return self.datasets
 
     def validate(self) -> bool:
-        # Validate the tool box based on the specification
         if not self.spec.name or not self.spec.version:
             self.failures.append("Invalid specification: Name or version is missing.")
             return False
@@ -39,28 +49,51 @@ class OperatorToolBox:
         return True
 
     def stop(self) -> None:
-        # Stop the tool box
-        print("Stopping the toolbox...")
+        logger.info("Stopping the toolbox...")
 
     def run(self) -> None:
-        # Run the tool box
-        print("Running the toolbox...")
+        logger.info("Running the toolbox...")
 
     def get_results(self) -> list[dict[str, Any]]:
-        # Get the results
         return self.datasets
 
     def get_failures(self) -> list[str]:
-        # Handle failure
         return self.failures
 
     def run_operation(self, operation: str) -> str:
-        # Run an operation based on the specification
         if operation not in ["dataset1", "dataset2", "dataset3"]:
             self.failures.append(f"Operation '{operation}' failed: Dataset not found.")
             return f"Operation '{operation}' failed: Dataset not found."
         return f"Operation '{operation}' executed successfully."
 
+    async def test_llm_spec(self, llm_spec: LLMSpec, user_prompt: str) -> str:
+        try:
+            # Verify the spec
+            response = await llm_spec.verify()
+            response.raise_for_status()
+            logger.info(f"Verification succeeded for {llm_spec.url}")
+
+            # Run test with user prompt
+            test_response = await llm_spec.probe(user_prompt)
+            test_response.raise_for_status()
+            response_data = test_response.json()
+            return f"Test succeeded for {llm_spec.url}: {response_data}"
+        except httpx.HTTPStatusError as e:
+            self.failures.append(f"HTTP error occurred: {e}")
+            logger.error(f"Test failed for {llm_spec.url}: {e}")
+            return f"Test failed for {llm_spec.url}: {e}"
+        except Exception as e:
+            self.failures.append(f"An error occurred: {e}")
+            logger.error(f"Test failed for {llm_spec.url}: {e}")
+            return f"Test failed for {llm_spec.url}: {e}"
+
+    async def test_with_prompt(self, spec_index: int, user_prompt: str) -> str:
+        if not 0 <= spec_index < len(self.llm_specs):
+            return f"Invalid spec index: {spec_index}. Valid range is 0 to {len(self.llm_specs) - 1}"
+
+        llm_spec = self.llm_specs[spec_index]
+        return await self.test_llm_spec(llm_spec, user_prompt)
+
 
 # Initialize OperatorToolBox with AgentSpecification
 spec = AgentSpecification(
@@ -71,84 +104,67 @@ spec = AgentSpecification(
     configuration={"max_tokens": 100},
 )
 
-# dataset_manager_agent.py
-
-
-# Initialize OperatorToolBox
 toolbox = OperatorToolBox(spec=spec, datasets=["dataset1", "dataset2", "dataset3"])
 
 # Define the agent with OperatorToolBox as its dependency
 dataset_manager_agent = Agent(
     model="gpt-4",
     deps_type=OperatorToolBox,
-    result_type=str,  # The agent will return string results
-    system_prompt="You can validate the toolbox, run operations, and retrieve results or failures.",
+    result_type=str,
+    system_prompt="You can validate the toolbox, run operations, retrieve results or failures, and test LLM specs.",
 )
 
 
 @dataset_manager_agent.tool
 async def validate_toolbox(ctx: RunContext[OperatorToolBox]) -> str:
-    """Validate the OperatorToolBox."""
     is_valid = ctx.deps.validate()
-    if is_valid:
-        return "ToolBox validation successful."
-    else:
-        return "ToolBox validation failed."
+    return (
+        "ToolBox validation successful." if is_valid else "ToolBox validation failed."
+    )
 
 
 @dataset_manager_agent.tool
 async def execute_operation(ctx: RunContext[OperatorToolBox], operation: str) -> str:
-    """Execute an operation on a dataset."""
-    result = ctx.deps.run_operation(operation)
-    return result
+    return ctx.deps.run_operation(operation)
 
 
 @dataset_manager_agent.tool
 async def retrieve_results(ctx: RunContext[OperatorToolBox]) -> str:
-    """Retrieve the results of operations."""
     results = ctx.deps.get_results()
-    if results:
-        formatted_results = "\n".join([f"{op}: {res}" for op, res in results.items()])
-        return f"Operation Results:\n{formatted_results}"
-    else:
-        return "No operations have been executed yet."
+    return (
+        f"Operation Results:\n{results}"
+        if results
+        else "No operations have been executed yet."
+    )
 
 
 @dataset_manager_agent.tool
 async def retrieve_failures(ctx: RunContext[OperatorToolBox]) -> str:
-    """Retrieve the list of failures."""
     failures = ctx.deps.get_failures()
-    if failures:
-        formatted_failures = "\n".join(failures)
-        return f"Failures:\n{formatted_failures}"
-    else:
-        return "No failures recorded."
+    return f"Failures:\n{failures}" if failures else "No failures recorded."
 
 
-# Synchronous run example
-def run_dataset_manager_agent_sync():
-    prompts = [
-        "Validate the toolbox.",
-        "Execute operation on 'dataset2'.",
-        "Execute operation on 'dataset4'.",  # This should fail
-        "Retrieve the results.",
-        "Retrieve any failures.",
-    ]
-
-    for prompt in prompts:
-        result = dataset_manager_agent.run_sync(prompt, deps=toolbox)
-        print(f"Prompt: {prompt}")
-        print(f"Response: {result.data}\n")
+@dataset_manager_agent.tool
+async def list_llm_specs(ctx: RunContext[OperatorToolBox]) -> str:
+    spec_list = "\n".join(
+        f"{i}: {spec.url}" for i, spec in enumerate(ctx.deps.llm_specs)
+    )
+    return f"Available LLM Specs:\n{spec_list}"
 
 
-# Asynchronous run example
+@dataset_manager_agent.tool
+async def test_llm_with_prompt(
+    ctx: RunContext[OperatorToolBox], spec_index: int, user_prompt: str
+) -> str:
+    return await ctx.deps.test_with_prompt(spec_index, user_prompt)
+
+
+# Asynchronous run example with user confirmation
 async def run_dataset_manager_agent_async():
     prompts = [
         "Validate the toolbox.",
-        "Execute operation on 'dataset2'.",
-        "Execute operation on 'dataset4'.",  # This should fail
-        "Retrieve the results.",
-        "Retrieve any failures.",
+        "List available LLM specs.",
+        "I want to test an LLM with my prompt: 'Tell me a short story about a robot'. Which spec index should I use?",
     ]
 
     for prompt in prompts:
@@ -156,10 +172,34 @@ async def run_dataset_manager_agent_async():
         print(f"Prompt: {prompt}")
         print(f"Response: {result.data}\n")
 
+        # Handle testing request
+        if "test an LLM with my prompt" in prompt:
+            print(
+                "Please select a spec index from the list above and confirm to proceed."
+            )
+            # Simulate user input for demo (in real app, you'd get this from user)
+            user_input = (
+                input("Enter spec index and 'yes' to confirm (e.g., '0 yes'): ")
+                .strip()
+                .split()
+            )
+            if len(user_input) == 2 and user_input[1].lower() == "yes":
+                try:
+                    spec_index = int(user_input[0])
+                    # Extract prompt from the original input
+                    user_prompt = prompt.split("my prompt: ")[1].strip("'")
+                    test_result = await dataset_manager_agent.run(
+                        f"Test LLM at index {spec_index} with prompt: {user_prompt}",
+                        deps=toolbox,
+                        spec_index=spec_index,
+                        user_prompt=user_prompt,
+                    )
+                    print(f"Test Response: {test_result.data}\n")
+                except ValueError:
+                    print("Invalid spec index provided.\n")
+            else:
+                print("Test canceled. Please provide a valid index and confirmation.\n")
+
 
 if __name__ == "__main__":
-    # Run synchronous example
-    run_dataset_manager_agent_sync()
-
-    # Run asynchronous example
     asyncio.run(run_dataset_manager_agent_async())

agentic_security/probe_actor/test_fuzzer.py

@@ -5,7 +5,7 @@ from unittest.mock import AsyncMock, MagicMock, Mock, patch
 import httpx
 import pytest
 
-from agentic_security.models.schemas import Scan
+from agentic_security.primitives import Scan
 from agentic_security.probe_actor.fuzzer import (
     generate_prompts,
     perform_many_shot_scan,
@@ -209,6 +209,7 @@ class TestProcessPrompt(unittest.IsolatedAsyncioTestCase):
             module_name="module_a",
             refusals=[],
             errors=[],
+            outputs=[],
         )
 
         self.assertEqual(tokens, 3)  # Tokens from "Valid response text"
@@ -226,6 +227,7 @@ class TestProcessPrompt(unittest.IsolatedAsyncioTestCase):
         )
 
         refusals = []
+        outputs = []
         tokens, refusal = await process_prompt(
             request_factory=mock_request_factory,
             prompt="test prompt",
@@ -233,6 +235,7 @@ class TestProcessPrompt(unittest.IsolatedAsyncioTestCase):
             module_name="module_a",
             refusals=refusals,
             errors=[],
+            outputs=outputs,
         )
 
         self.assertEqual(tokens, 3)  # Tokens from "Response indicating refusal"
@@ -250,15 +253,15 @@ class TestProcessPrompt(unittest.IsolatedAsyncioTestCase):
         )
 
         refusals = []
-        with self.assertRaises(httpx.HTTPStatusError):
-            await process_prompt(
-                request_factory=mock_request_factory,
-                prompt="test prompt",
-                tokens=0,
-                module_name="module_a",
-                refusals=refusals,
-                errors=[],
-            )
+        await process_prompt(
+            request_factory=mock_request_factory,
+            prompt="test prompt",
+            tokens=0,
+            module_name="module_a",
+            refusals=refusals,
+            errors=[],
+            outputs=[],
+        )
 
     async def test_request_error(self):
         mock_request_factory = Mock()
@@ -274,6 +277,7 @@ class TestProcessPrompt(unittest.IsolatedAsyncioTestCase):
             module_name="module_a",
             refusals=[],
             errors=errors,
+            outputs=[],
         )
 
         self.assertEqual(tokens, 0)

agentic_security/probe_data/__init__.py

@@ -5,6 +5,7 @@ REGISTRY_V0 = [
         "dataset_name": "simonycl/aya-23-8B_advbench_jailbreak",
         "num_prompts": 416,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -16,6 +17,7 @@ REGISTRY_V0 = [
         "dataset_name": "acmc/jailbreaks_dataset_with_perplexity_bigcode_starcoder2-3b_bigcode_starcoder2-7b",
         "num_prompts": 11191,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -27,6 +29,7 @@ REGISTRY_V0 = [
         "dataset_name": "karanxa/dolphin-jailbreak-finetuning-dataset",
         "num_prompts": 42684,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -38,6 +41,7 @@ REGISTRY_V0 = [
         "dataset_name": "karanxa/llama-2-jailbreak-dataset",
         "num_prompts": 40613,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -49,6 +53,7 @@ REGISTRY_V0 = [
         "dataset_name": "karanxa/llama2-uncensored-jailbreak-dataset-finetuning",
         "num_prompts": 42854,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -60,6 +65,7 @@ REGISTRY_V0 = [
         "dataset_name": "liuyanchen1015/Llama-3.2-1B_jailbreak_responses",
         "num_prompts": 9888,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -71,6 +77,7 @@ REGISTRY_V0 = [
         "dataset_name": "liuyanchen1015/Llama-3.2-1B-Instruct_jailbreak_responses",
         "num_prompts": 9888,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -82,6 +89,7 @@ REGISTRY_V0 = [
         "dataset_name": "liuyanchen1015/Llama-3.2-1B-Instruct_jailbreak_responses_with_judgment",
         "num_prompts": 9888,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -93,6 +101,7 @@ REGISTRY_V0 = [
         "dataset_name": "jackhhao/jailbreak-classification",
         "num_prompts": 1044,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -104,6 +113,7 @@ REGISTRY_V0 = [
         "dataset_name": "markush1/LLM-Jailbreak-Classifier",
         "num_prompts": 201193,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -115,6 +125,7 @@ REGISTRY_V0 = [
         "dataset_name": "walledai/JailbreakBench",
         "num_prompts": 200,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -126,6 +137,7 @@ REGISTRY_V0 = [
         "dataset_name": "walledai/JailbreakHub",
         "num_prompts": 15140,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -137,6 +149,7 @@ REGISTRY_V0 = [
         "dataset_name": "Granther/evil-jailbreak",
         "num_prompts": 1200,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -148,6 +161,7 @@ REGISTRY_V0 = [
         "dataset_name": "sevdeawesome/jailbreak_success",
         "num_prompts": 10800,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -159,6 +173,7 @@ REGISTRY_V0 = [
         "dataset_name": "IDA-SERICS/Disaster-tweet-jailbreaking",
         "num_prompts": 3000,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -170,6 +185,7 @@ REGISTRY_V0 = [
         "dataset_name": "GeorgeDaDude/Jailbreak_Complete_DS_labeled",
         "num_prompts": 11383,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -181,6 +197,7 @@ REGISTRY_V0 = [
         "dataset_name": "dayone3nder/jailbreak_prompt_JBB_sft_trainset",
         "num_prompts": 4785,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -192,6 +209,7 @@ REGISTRY_V0 = [
         "dataset_name": "dayone3nder/general_safe_mix_jailbreak_prompt_JBB_trainset",
         "num_prompts": 24679,
         "tokens": None,  # Add actual token count if available
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -206,6 +224,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "AgenticBackend",
         "num_prompts": 2000,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Fine-tuned cloud hosted model",
         "selected": True,
@@ -221,6 +240,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "ShawnMenz/DAN_jailbreak",
         "num_prompts": 666,
         "tokens": 224196,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -232,6 +252,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "deepset/prompt-injections",
         "num_prompts": 203,
         "tokens": 6988,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -243,6 +264,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "rubend18/ChatGPT-Jailbreak-Prompts",
         "num_prompts": 79,
         "tokens": 26971,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -254,6 +276,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "notrichardren/refuse-to-answer-prompts",
         "num_prompts": 522,
         "tokens": 7172,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -265,6 +288,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "Lemhf14/EasyJailbreak_Datasets",
         "num_prompts": 1630,
         "tokens": 19758,
+        "is_active": False,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -276,6 +300,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "markush1/LLM-Jailbreak-Classifier",
         "num_prompts": 1119,
         "tokens": 19758,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -287,6 +312,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "JailbreakV-28K/JailBreakV-28k",
         "num_prompts": 28300,
         "tokens": 1975800,
+        "is_active": False,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -298,6 +324,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "ShawnMenz/jailbreak_sft_rm_ds",
         "num_prompts": 371000,
         "tokens": 1975800,
+        "is_active": False,
         "approx_cost": 0.0,
         "source": "Hugging Face Datasets",
         "selected": False,
@@ -309,6 +336,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "Steganography",
         "num_prompts": 10,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Local mutation dataset",
         "selected": False,
@@ -320,6 +348,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "GPT fuzzer",
         "num_prompts": 10,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Local mutation dataset",
         "selected": False,
@@ -331,6 +360,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "jailbreak_llms/2023_05_07",
         "num_prompts": 0,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Github",
         "selected": False,
@@ -342,6 +372,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "jailbreak_llms/2023_12_25.csv",
         "num_prompts": 0,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Github",
         "selected": False,
@@ -353,6 +384,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "Malwaregen",
         "num_prompts": 0,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Local dataset",
         "selected": False,
@@ -364,6 +396,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "Hallucination",
         "num_prompts": 0,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Local dataset",
         "selected": False,
@@ -375,6 +408,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "DataLeak",
         "num_prompts": 0,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Local dataset",
         "selected": False,
@@ -386,6 +420,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "llm-adaptive-attacks",
         "num_prompts": 0,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Github: tml-epfl/llm-adaptive-attacks#0.0.1",
         "selected": False,
@@ -397,6 +432,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "Garak",
         "num_prompts": 0,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Github: https://github.com/leondz/garak#v0.9.0.1",
         "selected": False,
@@ -412,6 +448,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "Reinforcement Learning Optimization",
         "num_prompts": 0,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Cloud hosted model",
         "selected": False,
@@ -427,6 +464,7 @@ REGISTRY = REGISTRY_V0 + [
         "dataset_name": "InspectAI",
         "num_prompts": 0,
         "tokens": 0,
+        "is_active": True,
         "approx_cost": 0.0,
         "source": "Github: https://github.com/UKGovernmentBEIS/inspect_ai",
         "selected": False,
@@ -439,6 +477,7 @@ REGISTRY = REGISTRY_V0 + [
         "num_prompts": len(load_local_csv().prompts),
         "tokens": load_local_csv().tokens,
         "approx_cost": 0.0,
+        "is_active": True,
         "source": f"Local file dataset: {load_local_csv().metadata['src']}",
         "selected": len(load_local_csv().prompts),
         "url": "",

agentic_security/routes/probe.py

@@ -3,7 +3,7 @@ import random
 from fastapi import APIRouter, File, Header, HTTPException, UploadFile
 from fastapi.responses import JSONResponse
 
-from ..models.schemas import FileProbeResponse, Probe
+from ..primitives import FileProbeResponse, Probe
 from ..probe_actor.refusal import REFUSAL_MARKS
 from ..probe_data import REGISTRY
 
@@ -77,3 +77,11 @@ async def data_config():
 async def health_check():
     """Health check endpoint."""
     return JSONResponse(content={"status": "ok"})
+
+
+@router.post("/v1/self-probe-t5")
+def self_probe_t5(probe: Probe):
+    import languagemodels as lm  # noqa
+
+    message = lm.do(probe.prompt)
+    return make_mock_response(message)

agentic_security/routes/proxy.py

@@ -5,7 +5,7 @@ from fastapi import APIRouter
 from loguru import logger
 
 from ..core.app import get_current_run, get_tools_inbox
-from ..models.schemas import CompletionRequest, Settings
+from ..primitives import CompletionRequest, Settings
 from ..probe_actor.refusal import REFUSAL_MARKS
 
 router = APIRouter()

agentic_security/routes/report.py

@@ -3,7 +3,7 @@ from pathlib import Path
 from fastapi import APIRouter, Response
 from fastapi.responses import FileResponse, StreamingResponse
 
-from ..models.schemas import Table
+from ..primitives import Table
 from ..report_chart import plot_security_report
 
 router = APIRouter()

agentic_security/routes/scan.py

@@ -1,20 +1,37 @@
 from datetime import datetime
 
-from fastapi import APIRouter, BackgroundTasks, File, HTTPException, Query, UploadFile
+from fastapi import (
+    APIRouter,
+    BackgroundTasks,
+    Depends,
+    File,
+    HTTPException,
+    Query,
+    UploadFile,
+)
 from fastapi.responses import StreamingResponse
+from loguru import logger
 
 from ..core.app import get_stop_event, get_tools_inbox, set_current_run
+from ..dependencies import InMemorySecrets, get_in_memory_secrets
 from ..http_spec import LLMSpec
-from ..models.schemas import LLMInfo, Scan
+from ..primitives import LLMInfo, Scan
 from ..probe_actor import fuzzer
 
 router = APIRouter()
 
 
 @router.post("/verify")
-async def verify(info: LLMInfo):
+async def verify(
+    info: LLMInfo, secrets: InMemorySecrets = Depends(get_in_memory_secrets)
+):
     spec = LLMSpec.from_string(info.spec)
-    r = await spec.verify()
+    try:
+        r = await spec.verify()
+    except Exception as e:
+        logger.exception(e)
+        raise HTTPException(status_code=400, detail=str(e))
+
     if r.status_code >= 400:
         raise HTTPException(status_code=r.status_code, detail=r.text)
     return dict(
@@ -42,7 +59,12 @@ def streaming_response_generator(scan_parameters: Scan):
 
 
 @router.post("/scan")
-async def scan(scan_parameters: Scan, background_tasks: BackgroundTasks):
+async def scan(
+    scan_parameters: Scan,
+    background_tasks: BackgroundTasks,
+    secrets: InMemorySecrets = Depends(get_in_memory_secrets),
+):
+    scan_parameters.with_secrets(secrets)
     return StreamingResponse(
         streaming_response_generator(scan_parameters), media_type="application/json"
     )
@@ -62,6 +84,7 @@ async def scan_csv(
     optimize: bool = Query(False),
     maxBudget: int = Query(10_000),
     enableMultiStepAttack: bool = Query(False),
+    secrets: InMemorySecrets = Depends(get_in_memory_secrets),
 ):
     # TODO: content dataset to fuzzer
     content = await file.read()  # noqa
@@ -73,7 +96,7 @@ async def scan_csv(
         maxBudget=1000,
         enableMultiStepAttack=enableMultiStepAttack,
     )
-
+    scan_parameters.with_secrets(secrets)
     return StreamingResponse(
         streaming_response_generator(scan_parameters), media_type="application/json"
     )

agentic_security/routes/static.py

@@ -1,15 +1,17 @@
 from pathlib import Path
 
+import requests
 from fastapi import APIRouter, HTTPException, Request
 from fastapi.responses import FileResponse, HTMLResponse
 from fastapi.templating import Jinja2Templates
 from jinja2 import Environment, FileSystemLoader
 from starlette.responses import Response
 
-from ..models.schemas import Settings
+from ..primitives import Settings
 
 router = APIRouter()
 STATIC_DIR = Path(__file__).parent.parent / "static"
+ICONS_DIR = STATIC_DIR / "icons"
 
 # Configure templates with custom delimiters to avoid conflicts
 templates = Jinja2Templates(directory=str(STATIC_DIR))
@@ -28,6 +30,8 @@ CONTENT_TYPES = {
     ".ico": "image/x-icon",
     ".html": "text/html",
     ".css": "text/css",
+    ".svg": "image/svg+xml",
+    ".png": "image/png",
 }
 
 
@@ -88,3 +92,94 @@ async def telemetry_js() -> FileResponse:
 async def favicon() -> FileResponse:
     """Serve the favicon."""
     return get_static_file(STATIC_DIR / "favicon.ico")
+
+
+@router.get("/icons/{icon_name}")
+async def serve_icon(icon_name: str) -> FileResponse:
+    """Serve an icon from the icons directory."""
+    icon_path = ICONS_DIR / icon_name
+    if not icon_path.exists():
+        # Fetch the icon from the external URL and cache it
+        url = f"https://registry.npmmirror.com/@lobehub/icons-static-png/latest/files/dark/{icon_name}"
+        response = requests.get(url)
+        if response.status_code == 200:
+            icon_path.write_bytes(response.content)
+        else:
+            raise HTTPException(status_code=404, detail="Icon not found")
+
+    return get_static_file(icon_path, content_type="image/png")
+
+
+# New endpoints for proxying external resources
+@router.get("/cdn/tailwindcss.js")
+async def proxy_tailwindcss() -> FileResponse:
+    """Proxy the Tailwind CSS script."""
+    return proxy_external_resource(
+        "https://cdn.tailwindcss.com",
+        STATIC_DIR / "tailwindcss.js",
+        "application/javascript",
+    )
+
+
+@router.get("/cdn/vue.js")
+async def proxy_vue() -> FileResponse:
+    """Proxy the Vue.js script."""
+    return proxy_external_resource(
+        "https://unpkg.com/vue@2.6.12/dist/vue.js",
+        STATIC_DIR / "vue.js",
+        "application/javascript",
+    )
+
+
+@router.get("/cdn/lucide.js")
+async def proxy_lucide() -> FileResponse:
+    """Proxy the Lucide.js script."""
+    return proxy_external_resource(
+        "https://unpkg.com/lucide@latest/dist/umd/lucide.js",
+        STATIC_DIR / "lucide.js",
+        "application/javascript",
+    )
+
+
+@router.get("/cdn/technopollas.css")
+async def proxy_technopollas() -> FileResponse:
+    """Proxy the Technopollas font stylesheet."""
+    return proxy_external_resource(
+        "https://fonts.cdnfonts.com/css/technopollas",
+        STATIC_DIR / "technopollas.css",
+        "text/css",
+    )
+
+
+@router.get("/cdn/inter.css")
+async def proxy_inter() -> FileResponse:
+    """Proxy the Inter font stylesheet."""
+    return proxy_external_resource(
+        "https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700&display=swap",
+        STATIC_DIR / "inter.css",
+        "text/css",
+    )
+
+
+def proxy_external_resource(
+    url: str, local_path: Path, content_type: str
+) -> FileResponse:
+    """
+    Fetch and cache an external resource, then serve it locally.
+
+    Args:
+        url: The URL of the external resource
+        local_path: The local path to cache the resource
+        content_type: The content type of the resource
+
+    Returns:
+        FileResponse with the cached resource
+    """
+    if not local_path.exists():
+        response = requests.get(url)
+        if response.status_code == 200:
+            local_path.write_bytes(response.content)
+        else:
+            raise HTTPException(status_code=404, detail="Resource not found")
+
+    return get_static_file(local_path, content_type=content_type)

agentic_security/routes/telemetry.py

@@ -0,0 +1,28 @@
+import sentry_sdk
+from loguru import logger
+from sentry_sdk.integrations.logging import ignore_logger
+
+from ..primitives import Settings
+
+
+def setup(app):
+    if Settings.DISABLE_TELEMETRY:
+        return
+    sentry_sdk.init(
+        dsn="https://b5c59f7e5ab86d73518222ddb40807c9@o4508851738247168.ingest.de.sentry.io/4508851740541008",
+        # Add data like request headers and IP for users,
+        # see https://docs.sentry.io/platforms/python/data-management/data-collected/ for more info
+        send_default_pii=True,
+        # Set traces_sample_rate to 1.0 to capture 100%
+        # of transactions for tracing.
+        traces_sample_rate=1.0,
+        ignore_errors=[KeyboardInterrupt],
+        _experiments={
+            # Set continuous_profiling_auto_start to True
+            # to automatically start the profiler on when
+            # possible.
+            "continuous_profiling_auto_start": True,
+        },
+    )
+    ignore_logger("logging.error")
+    ignore_logger(logger.error)

agentic_security/routes/test_probe.py

@@ -6,7 +6,7 @@ import pytest
 from fastapi.testclient import TestClient
 
 from ..app import app
-from ..models.schemas import Probe
+from ..primitives import Probe
 from ..probe_actor.refusal import REFUSAL_MARKS
 from ..probe_data import REGISTRY
 

agentic_security/routes/test_static.py

@@ -4,7 +4,7 @@ import pytest
 from fastapi import HTTPException
 from fastapi.testclient import TestClient
 
-from ..models.schemas import Settings
+from ..primitives import Settings
 from .static import get_static_file, router
 
 client = TestClient(router)

agentic_security/static/base.js

@@ -1,13 +1,12 @@
-
-let URL = window.location.href;
-if (URL.endsWith('/')) {
-  URL = URL.slice(0, -1);
+let SELF_URL = window.location.href;
+if (SELF_URL.endsWith('/')) {
+  SELF_URL = SELF_URL.slice(0, -1);
 }
-URL = URL.replace('/#', '');
+SELF_URL = SELF_URL.replace('/#', '');
 
 // Vue application
 let LLM_SPECS = [
-  `POST ${URL}/v1/self-probe
+  `POST ${SELF_URL}/v1/self-probe
 Authorization: Bearer XXXXX
 Content-Type: application/json
 
@@ -79,7 +78,7 @@ Content-Type: application/json
 ]
 }
 `,
-  `POST ${URL}/v1/self-probe-image
+  `POST ${SELF_URL}/v1/self-probe-image
 Authorization: Bearer XXXXX
 Content-Type: application/json
 
@@ -101,7 +100,7 @@ Content-Type: application/json
     }
 ]
 `,
-  `POST ${URL}/v1/self-probe-file
+  `POST ${SELF_URL}/v1/self-probe-file
 Authorization: Bearer $GROQ_API_KEY
 Content-Type: multipart/form-data
 
@@ -171,29 +170,43 @@ Content-Type: application/json
 {
   "audio_url": "<<AUDIO_FILE_URL>>"
 }
+`,
+
+  `POST https://api.openrouter.ai/v1/chat/completions
+Authorization: Bearer $OPENROUTER_API_KEY
+Content-Type: application/json
+
+{
+  "model": "openrouter-latest",
+  "prompt": "<<PROMPT>>",
+  "temperature": 0.7,
+  "max_tokens": 150,
+  "top_p": 0.9,
+  "frequency_penalty": 0,
+  "presence_penalty": 0
+}
 `,
 
 ]
 
+let fallbackIcon = '/icons/myshell.png';
 
 let LLM_CONFIGS = [
-  { name: 'Custom API', prompts: 40000, customInstructions: 'Requires api spec' },
-  { name: 'Open AI', prompts: 24000 },
-  { name: 'Deepseek v1', prompts: 24000 },
-  { name: 'Replicate', prompts: 40000 },
-  { name: 'Groq', prompts: 40000 },
-  { name: 'Together.ai', prompts: 40000 },
-  { name: 'Custom API Image', prompts: 40000, customInstructions: 'Requires api spec', modality: 'Image' },
-  { name: 'Custom API Files', prompts: 40000, customInstructions: 'Requires api spec', modality: 'Files' },
-  { name: 'Gemini', prompts: 40000 },
-  { name: 'Claude', prompts: 40000 },
-  { name: 'Cohere', prompts: 40000 },
-  { name: 'Azure OpenAI', prompts: 40000 },
-  { name: 'assemblyai', prompts: 40000 },
-
-
-]
-
+  { name: 'Custom API', prompts: 40000, customInstructions: 'Requires api spec', logo: fallbackIcon },
+  { name: 'Open AI', prompts: 24000, logo: '/icons/openai.png' },
+  { name: 'Deepseek v1', prompts: 24000, logo: '/icons/deepseek.png' },
+  { name: 'Replicate', prompts: 40000, logo: '/icons/replicate.png' },
+  { name: 'Groq', prompts: 40000, logo: '/icons/groq.png' },
+  { name: 'Together.ai', prompts: 40000, logo: '/icons/together.png' },
+  { name: 'Custom API Image', prompts: 40000, customInstructions: 'Requires api spec', modality: 'Image', logo: fallbackIcon },
+  { name: 'Custom API Files', prompts: 40000, customInstructions: 'Requires api spec', modality: 'Files', logo: fallbackIcon },
+  { name: 'Gemini', prompts: 40000, logo: '/icons/gemini.png' },
+  { name: 'Claude', prompts: 40000, logo: '/icons/claude.png' },
+  { name: 'Cohere', prompts: 40000, logo: '/icons/cohere.png' },
+  { name: 'Azure OpenAI', prompts: 40000, logo: '/icons/azureai.png' },
+  { name: 'OpenRouter.ai', prompts: 40000, logo: '/icons/openrouter.png' },
+  { name: 'assemblyai', prompts: 40000, logo: fallbackIcon },
+];
 function has_image(spec) {
   return spec.includes('<<BASE64_IMAGE>>');
 }
@@ -228,5 +241,6 @@ function _getFailureRateScore(failureRate) {
   else if (strengthRate >= 80) return 'B';
   else if (strengthRate >= 70) return 'C';
   else if (strengthRate >= 60) return 'D';
+  else if (strengthRate >= 1) return '?';
   else return 'E'; // For strengthRate less than 60
 }

agentic_security/static/index.html

@@ -33,8 +33,38 @@
       </header>
       [[% include "partials/concent.html" %]]
 
+          <div class="flex space-x-4 overflow-x-auto scrollbar-hide">
+            <div
+              v-for="(config, index) in configs"
+              :key="index"
+              @click="selectConfig(index)"
+              class="flex-none w-1/2 sm:w-1/3 md:w-1/4 lg:w-1/5 border-2 rounded-lg p-4 flex flex-col items-start transition-all hover:shadow-md cursor-pointer"
+              :class="{
+          'border-dark-accent-green': selectedConfig === index,
+          'border-gray-600': selectedConfig !== index
+        }">
+              <div class="flex items-center font-medium mb-2">
+                <img
+                  v-if="config.logo"
+                  :src="config.logo"
+                  class="w-6 h-6 ml-2 rounded-full"
+                  alt="logo" />
+                <span class="ml-2">{{ config.name }}</span>
+
+              </div>
+
+              <div class="text-sm text-gray-400">
+                {{ config.customInstructions || 'Requires API key' }}
+              </div>
+              <div class="mt-2 text-dark-accent-green font-semibold">
+                {{ config.modality || 'API' }}
+              </div>
+            </div>
+          </div>
+        </section>
+      </main>
       <main class="max-w-6xl mx-auto space-y-8">
-        <section class="bg-dark-card rounded-lg p-6 shadow-lg">
+        <section class="bg-dark-card rounded-lg p-6 shadow-lg" v-show="false">
           <h2 class="text-2xl font-bold mb-4">Select a Config</h2>
 
           <div class="flex space-x-4 overflow-x-auto scrollbar-hide">
@@ -64,7 +94,7 @@
 
             <h2 class="text-2xl font-bold">LLM API Spec</h2>
             <span :class="statusDotClass"
-              class="w-3 h-3 rounded-full mr-2"></span>
+                class="w-3 h-3 rounded-full mr-2"></span>
             <svg :class="{'rotate-180': showLLMSpec}"
               class="w-6 h-6 transition-transform duration-200"
               xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none"
@@ -74,7 +104,7 @@
             </svg>
           </div>
 
-          <div v-show="showLLMSpec" class="mt-4">
+          <div class="mt-4">
             <label v-if="isFocused" for="llm-spec"
               class="block text-sm font-medium mb-2">
               LLM API Spec, PROMPT variable will be replaced with the testing
@@ -109,6 +139,8 @@
               <strong class="font-bold">></strong>
               <span class="block sm:inline">{{okMsg}}</span>
             </div>
+            <span v-if="latency" class="text-sm text-gray-400 ml-2">Latency: {{latency}}s</span>
+
 
             <!-- Action Buttons -->
             <section class="flex justify-center space-x-4 mt-10">
@@ -351,27 +383,26 @@
                 class="text-gray-400 hover:underline">Deselect All</button>
             </div>
 
-            <div class="grid grid-cols-1 sm:grid-cols-2 md:grid-cols-3 gap-4">
-              <div
-                v-for="(package, index) in dataConfig"
-                :key="index"
-                @click="addPackage(index)"
-                class="border rounded-lg p-3 cursor-pointer transition-all hover:shadow-md overflow-hidden"
-                :class="{
-                'border-dark-accent-green bg-dark-accent-green bg-opacity-20': package.selected,
-                'border-gray-600': !package.selected
-              }">
-                <div class="font-medium mb-1 truncate">{{ package.dataset_name
-                  }}</div>
-                <div class="text-sm text-gray-400 truncate">
-                  {{ package.source || 'Local dataset' }}
-                </div>
-                <div class="mt-2 text-sm font-semibold">
-                  {{ package.dynamic ? 'Dynamic dataset' :
-                  `${package.num_prompts.toLocaleString()} prompts` }}
-                </div>
-              </div>
+          <div class="grid grid-cols-1 sm:grid-cols-2 md:grid-cols-3 gap-4">
+          <div
+            v-for="(package, index) in dataConfig"
+            :key="index"
+            @click="package.is_active !== false && addPackage(index)"
+            class="border rounded-lg p-3 cursor-pointer transition-all hover:shadow-md overflow-hidden"
+            :class="{
+              'border-dark-accent-green bg-dark-accent-green bg-opacity-20': package.selected,
+              'border-gray-600': !package.selected,
+              'opacity-30 pointer-events-none cursor-not-allowed': package.is_active === false
+            }">
+            <div class="font-medium mb-1 truncate">{{ package.dataset_name }}</div>
+            <div class="text-sm text-gray-400 truncate">
+              {{ package.source || 'Local dataset' }}
             </div>
+            <div class="mt-2 text-sm font-semibold">
+              {{ package.dynamic ? 'Dynamic dataset' : `${package.num_prompts.toLocaleString()} prompts` }}
+            </div>
+          </div>
+        </div>
           </div>
         </section>
 
@@ -388,6 +419,8 @@
           <strong class="font-bold">></strong>
           <span class="block sm:inline">{{okMsg}}</span>
         </div>
+        <span v-if="latency" class="text-sm text-gray-400 ml-2">Latency: {{latency}}s</span>
+
 
         <!-- Action Buttons -->
         <section class="flex justify-center space-x-4">

agentic_security/static/inter.css

@@ -0,0 +1,21 @@
+@font-face {
+  font-family: 'Inter';
+  font-style: normal;
+  font-weight: 400;
+  font-display: swap;
+  src: url(https://fonts.gstatic.com/s/inter/v18/UcCO3FwrK3iLTeHuS_nVMrMxCp50SjIw2boKoduKmMEVuLyfMZg.ttf) format('truetype');
+}
+@font-face {
+  font-family: 'Inter';
+  font-style: normal;
+  font-weight: 600;
+  font-display: swap;
+  src: url(https://fonts.gstatic.com/s/inter/v18/UcCO3FwrK3iLTeHuS_nVMrMxCp50SjIw2boKoduKmMEVuGKYMZg.ttf) format('truetype');
+}
+@font-face {
+  font-family: 'Inter';
+  font-style: normal;
+  font-weight: 700;
+  font-display: swap;
+  src: url(https://fonts.gstatic.com/s/inter/v18/UcCO3FwrK3iLTeHuS_nVMrMxCp50SjIw2boKoduKmMEVuFuYMZg.ttf) format('truetype');
+}

agentic_security/static/main.js

@@ -4,6 +4,7 @@ var app = new Vue({
         progressWidth: '0%',
         modelSpec: LLM_SPECS[0],
         budget: 50,
+        latency: 0,
         isFocused: false, // Tracks if the textarea is focused
         showParams: false,
         showResetConfirmation: false,
@@ -121,6 +122,7 @@ var app = new Vue({
             const state = {
                 modelSpec: this.modelSpec,
                 budget: this.budget,
+                selectedConfig: this.selectedConfig,
                 dataConfig: this.dataConfig,
                 optimize: this.optimize,
                 enableChartDiagram: this.enableChartDiagram,
@@ -139,6 +141,7 @@ var app = new Vue({
                 this.optimize = state.optimize;
                 this.enableChartDiagram = state.enableChartDiagram;
                 this.enableMultiStepAttack = state.enableMultiStepAttack;
+                this.selectedConfig = state.selectedConfig;
             }
         },
         resetState() {
@@ -190,7 +193,8 @@ var app = new Vue({
             let payload = {
                 spec: this.modelSpec,
             };
-            const response = await fetch(`${URL}/verify`, {
+            let startTime = performance.now(); // Capture start time
+            const response = await fetch(`${SELF_URL}/verify`, {
                 method: 'POST',
                 headers: {
                     'Content-Type': 'application/json',
@@ -198,10 +202,14 @@ var app = new Vue({
                 body: JSON.stringify(payload),
             });
             console.log(response);
-            let txt = await response.text();
+            let r = await response.json();
+            let endTime = performance.now(); // Capture end time
+            let latency = endTime - startTime; // Calculate latency in milliseconds
+            latency = latency.toFixed(3) / 1000; // Round to 2 decimal places
+            this.latency = latency;
             if (!response.ok) {
                 this.updateStatusDot(false);
-                this.errorMsg = 'Integration verification failed:' + txt;
+                this.errorMsg = 'Integration verification failed:' + JSON.stringify(r);
             } else {
                 this.errorMsg = '';
                 this.updateStatusDot(true);
@@ -214,7 +222,7 @@ var app = new Vue({
             this.saveStateToLocalStorage();
         },
         loadConfigs: async function () {
-            const response = await fetch(`${URL}/v1/data-config`, {
+            const response = await fetch(`${SELF_URL}/v1/data-config`, {
                 method: 'GET',
                 headers: {
                     'Content-Type': 'application/json',
@@ -286,6 +294,7 @@ var app = new Vue({
                 this.okMsg = `${event.module}`;
                 return
             }
+            this.latency = event.latency.toFixed(3);
             console.log('New event');
             //  { "module": "Module 49", "tokens": 480, "cost": 4.800000000000001, "progress": 9.8 }
             let progress = event.progress;
@@ -321,14 +330,14 @@ var app = new Vue({
             let payload = {
                 table: this.mainTable,
             };
-            const response = await fetch(`${URL}/plot.jpeg`, {
+            const response = await fetch(`${SELF_URL}/plot.jpeg`, {
                 method: 'POST',
                 headers: {
                     'Content-Type': 'application/json',
                 },
                 body: JSON.stringify(payload),
             });
-            // Convert image response to a data URL for the <img> src
+            // Convert image response to a data SELF_URL for the <img> src
             const blob = await response.blob();
             const reader = new FileReader();
             reader.readAsDataURL(blob);
@@ -341,6 +350,10 @@ var app = new Vue({
 
             // If all are selected, deselect all. Otherwise, select all.
             this.dataConfig.forEach(package => {
+                if (!package.is_active) {
+                    package.selected = false;
+                    return
+                }
                 package.selected = !allSelected;
             });
 
@@ -371,7 +384,7 @@ var app = new Vue({
         },
         stopScan: async function () {
             this.scanRunning = false;
-            const response = await fetch(`${URL}/stop`, {
+            const response = await fetch(`${SELF_URL}/stop`, {
                 method: 'POST',
                 headers: {
                     'Content-Type': 'application/json',
@@ -387,7 +400,7 @@ var app = new Vue({
                 optimize: this.optimize,
                 enableMultiStepAttack: this.enableMultiStepAttack,
             };
-            const response = await fetch(`${URL}/scan`, {
+            const response = await fetch(`${SELF_URL}/scan`, {
                 method: 'POST',
                 headers: {
                     'Content-Type': 'application/json',

agentic_security/static/partials/footer.html

@@ -6,7 +6,7 @@
             <div>
                 <h3
                     class="text-lg font-semibold text-dark-accent-green mb-4">Home</h3>
-                <p class="text-gray-400">Dedicated to LLM Security, 2024</p>
+                <p class="text-gray-400">Dedicated to LLM Security, 2025</p>
             </div>
 
             <!-- Column 2 -->

agentic_security/static/partials/head.html

@@ -2,12 +2,12 @@
     <meta charset="UTF-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <title>LLM Vulnerability Scanner</title>
-    <script src="https://cdn.tailwindcss.com"></script>
-    <script src="https://unpkg.com/vue@2.6.12/dist/vue.js"></script>
-    <script src="https://unpkg.com/lucide@latest/dist/umd/lucide.js"></script>
-    <link href="https://fonts.cdnfonts.com/css/technopollas" rel="stylesheet">
+    <script src="/cdn/tailwindcss.js"></script>
+    <script src="/cdn/vue.js"></script>
+    <script src="/cdn/lucide.js"></script>
+    <link href="/cdn/technopollas.css" rel="stylesheet">
     <style>
-      @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700&display=swap');
+      @import url('/cdn/inter.css');
     </style>
     <script>
       tailwind.config = {
@@ -19,6 +19,17 @@
               technopollas: ['Technopollas', 'sans-serif'],
             },
             colors: {
+                t1: {
+                bg: '#0D0D0D', // Jet Black
+                card: '#1A1A1A', // Dark Carbon Fiber
+                text: '#FFFFFF',
+                accent: {
+                  green: '#E0A3B6', // Frozen Berry
+                  red: '#1C3F74', // Neptune Blue
+                  orange: '#A5A5A5', // Dolomite Silver
+                  yellow: '#2E4053', // Jet Black
+                },
+              },
               dark: {
                 bg: '#121212',
                 card: '#1E1E1E',
@@ -28,7 +39,44 @@
                   red: '#F44336',
                   orange: '#FF9800',
                   yellow: '#FFEB3B',
+                // bg: '#0D0D0D', // Jet Black
+                // card: '#1A1A1A', // Dark Carbon Fiber
+                // text: '#FFFFFF',
+                // accent: {
+                //   green: '#E0A3B6', // Frozen Berry
+                //   red: '#1C3F74', // Neptune Blue
+                //   orange: '#A5A5A5', // Dolomite Silver
+                //   yellow: '#2E4053', // Jet Black
+
+                  berry: '#E0A3B6', // Frozen Berry
+                  blue: '#1C3F74', // Neptune Blue
+                  silver: '#A5A5A5', // Dolomite Silver
+                  black: '#DAF7A6', // Jet Black
                 },
+                variant1: {
+                    primary: '#E0A3B6', // Frozen Berry
+                    secondary: '#1C3F74', // Neptune Blue
+                    highlight: '#A5A5A5', // Dolomite Silver
+                    dark: '#000000' // Jet Black
+                  },
+                  variant2: {
+                    primary: '#FF5733', // Lava Red
+                    secondary: '#2E4053', // Midnight Blue
+                    highlight: '#C0C0C0', // Platinum Silver
+                    dark: '#121212' // Deep Black
+                  },
+                  variant3: {
+                    primary: '#3D9970', // Racing Green
+                    secondary: '#85144B', // Burgundy Red
+                    highlight: '#AAAAAA', // Light Silver
+                    dark: '#111111' // Matte Black
+                  },
+                  variant4: {
+                    primary: '#FFC300', // Golden Yellow
+                    secondary: '#DAF7A6', // Soft Mint
+                    highlight: '#888888', // Titanium Gray
+                    dark: '#222222' // Charcoal Black
+                  },
               },
             },
             borderRadius: {

agentic_security/static/technopollas.css

@@ -0,0 +1,8 @@
+@font-face {
+    font-family: 'Technopollas';
+    font-style: normal;
+    font-weight: 400;
+    src: local('Technopollas'), url('https://fonts.cdnfonts.com/s/72836/Technopollas.woff') format('woff');
+}
+
+

agentic_security/static/telemetry.js

@@ -2,3 +2,5 @@
 posthog.init('phc_jfYo5xEofW7eJtiU8rLt2Z8jw1E2eW27BxwTJzwRufH', {
     api_host: 'https://us.i.posthog.com', person_profiles: 'identified_only' // or 'always' to create profiles for anonymous users as well
 })
+
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agentic_security/test_dependencies.py

@@ -0,0 +1,15 @@
+from agentic_security.dependencies import InMemorySecrets, get_in_memory_secrets
+
+
+def test_in_memory_secrets():
+    secrets = InMemorySecrets()
+    secrets.set_secret("api_key", "12345")
+    assert secrets.get_secret("api_key") == "12345"
+    assert secrets.get_secret("non_existent_key") is None
+
+
+def test_get_in_memory_secrets():
+    secrets = get_in_memory_secrets()
+    assert isinstance(secrets, InMemorySecrets)
+    secrets.set_secret("token", "abcde")
+    assert secrets.get_secret("token") == "abcde"

agentic_security/test_lib.py

@@ -50,7 +50,7 @@ def make_test_registry():
     ]
 
 
-class TestAS:
+class TestLibraryLevel:
     # Handles an empty dataset list.
     def test_class(self, test_server):
         llmSpec = test_spec_assets.SAMPLE_SPEC
@@ -62,8 +62,8 @@ class TestAS:
         print(result)
         assert len(result) in [0, 1]
 
-    # TODO: slow test
-    def _test_class_msj(self, test_server):
+    @pytest.mark.slow
+    def test_class_msj(self, test_server):
         llmSpec = test_spec_assets.SAMPLE_SPEC
         maxBudget = 1000
         max_th = 0.3
@@ -98,6 +98,7 @@ class TestAS:
         print(result)
         assert len(result) in [0, 1]
 
+    @pytest.mark.slow
     def test_backend(self, test_server):
         llmSpec = test_spec_assets.SAMPLE_SPEC
         maxBudget = 1000000
@@ -156,7 +157,7 @@ class TestAS:
 class TestEntrypointCI:
     def test_generate_default_cfg_to_tmp_path(self):
         """
-        Test that the `generate_default_cfg` method generates a valid default config file in a temporary path.
+        Test that the `generate_default_settings` method generates a valid default config file in a temporary path.
         """
         # Create a temporary directory
         with tempfile.TemporaryDirectory() as tmpdir:
@@ -167,7 +168,7 @@ class TestEntrypointCI:
 
             # Generate the default configuration
             security = AgenticSecurity()
-            security.generate_default_cfg()
+            security.generate_default_settings()
 
             # Check that the config file was created at the temporary path
             assert os.path.exists(temp_path), f"{temp_path} file should be generated."
@@ -192,7 +193,7 @@ class TestEntrypointCI:
 
             # Generate the default configuration
             security = AgenticSecurity()
-            security.generate_default_cfg()
+            security.generate_default_settings()
 
             # Load the generated configuration
             AgenticSecurity.load_config(temp_path)

docs/index.md

@@ -21,4 +21,4 @@ Note: Please be aware that Agentic Security is designed as a safety scanner tool
 
 ## UI 🧙
 
-<img width="100%" alt="booking-screen" src="https://res.cloudinary.com/dq0w2rtm9/image/upload/v1736433557/z0bsyzhsqlgcr3w4ovwp.gif">
+<img width="100%" alt="booking-screen" src="https://res.cloudinary.com/dq0w2rtm9/image/upload/v1741192668/final_aa9jhb.gif">

docs/stylesheets/extra.css

@@ -1,14 +1,16 @@
 :root {
-  --md-primary-fg-color: #e92063;
-  --md-primary-fg-color--light: #e92063;
-  --md-primary-fg-color--dark: #e92063;
+  --md-primary-fg-color: #2E4053;
+  /* Primary color changed to pinkish */
+  --md-primary-fg-color--light: #E0A3B6;
+  --md-primary-fg-color--dark: #1C3F74;
+  /* Dark variant changed to blue */
 }
 
-
-/* Revert hue value to that of pre mkdocs-material v9.4.0 */
+/* Updated slate color scheme with new background */
 [data-md-color-scheme="slate"] {
   --md-hue: 230;
-  --md-default-bg-color: hsla(230, 15%, 21%, 1);
+  --md-default-bg-color: #1A1A1A;
+  /* Background changed to dark gray */
 }
 
 .hide {
@@ -24,12 +26,15 @@ img.index-header {
   max-width: 500px;
 }
 
+/* Updated custom colors */
 .pydantic-pink {
-  color: #FF007F;
+  color: #E0A3B6;
+  /* Updated to match new theme */
 }
 
 .team-blue {
-  color: #0072CE;
+  color: #1C3F74;
+  /* Updated to match new theme */
 }
 
 .secure-green {
@@ -67,7 +72,6 @@ img.index-header {
   text-align: center;
 }
 
-
 /* Hide the entire footer */
 .md-footer {
   display: none;

mkdocs.yml

@@ -89,7 +89,7 @@ theme:
         name: Switch to light mode
   icon:
     repo: fontawesome/brands/github
-  favicon: "https://res.cloudinary.com/dq0w2rtm9/image/upload/v1737555066/r17hrkre246doczwmvbv.png"
+  favicon: https://res.cloudinary.com/dq0w2rtm9/image/upload/v1741195421/favicon_kuz6xr.png
 
 extra:
   generator: false

poetry.lock

@@ -229,6 +229,24 @@ files = [
 [package.extras]
 dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
 
+[[package]]
+name = "backrefs"
+version = "5.8"
+description = "A wrapper around re and regex that adds additional back references."
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "backrefs-5.8-py310-none-any.whl", hash = "sha256:c67f6638a34a5b8730812f5101376f9d41dc38c43f1fdc35cb54700f6ed4465d"},
+    {file = "backrefs-5.8-py311-none-any.whl", hash = "sha256:2e1c15e4af0e12e45c8701bd5da0902d326b2e200cafcd25e49d9f06d44bb61b"},
+    {file = "backrefs-5.8-py312-none-any.whl", hash = "sha256:bbef7169a33811080d67cdf1538c8289f76f0942ff971222a16034da88a73486"},
+    {file = "backrefs-5.8-py313-none-any.whl", hash = "sha256:e3a63b073867dbefd0536425f43db618578528e3896fb77be7141328642a1585"},
+    {file = "backrefs-5.8-py39-none-any.whl", hash = "sha256:a66851e4533fb5b371aa0628e1fee1af05135616b86140c9d787a2ffdf4b8fdc"},
+    {file = "backrefs-5.8.tar.gz", hash = "sha256:2cab642a205ce966af3dd4b38ee36009b31fa9502a35fd61d59ccc116e40a6bd"},
+]
+
+[package.extras]
+extras = ["regex"]
+
 [[package]]
 name = "beautifulsoup4"
 version = "4.12.3"
@@ -784,18 +802,18 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth
 
 [[package]]
 name = "fastapi"
-version = "0.115.8"
+version = "0.115.11"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fastapi-0.115.8-py3-none-any.whl", hash = "sha256:753a96dd7e036b34eeef8babdfcfe3f28ff79648f86551eb36bfc1b0bf4a8cbf"},
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+    {file = "fastapi-0.115.11-py3-none-any.whl", hash = "sha256:32e1541b7b74602e4ef4a0260ecaf3aadf9d4f19590bba3e1bf2ac4666aa2c64"},
+    {file = "fastapi-0.115.11.tar.gz", hash = "sha256:cc81f03f688678b92600a65a5e618b93592c65005db37157147204d8924bf94f"},
 ]
 
 [package.dependencies]
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-starlette = ">=0.40.0,<0.46.0"
+starlette = ">=0.40.0,<0.47.0"
 typing-extensions = ">=4.8.0"
 
 [package.extras]
@@ -1202,13 +1220,13 @@ files = [
 
 [[package]]
 name = "inline-snapshot"
-version = "0.20.1"
+version = "0.20.3"
 description = "golden master/snapshot/approval testing library which puts the values right into your source code"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "inline_snapshot-0.20.1-py3-none-any.whl", hash = "sha256:5b5c3fd037f340dff5adee1c2c58db9038325937a8190dedbba98e37b87c979a"},
-    {file = "inline_snapshot-0.20.1.tar.gz", hash = "sha256:c56c871e59973500eca00610022eac19e79cd2c1b0b2d7a18abe14dde11a1431"},
+    {file = "inline_snapshot-0.20.3-py3-none-any.whl", hash = "sha256:1ea999fbf38dd11cc72d0e1a0b9303c63d496b77bdc406a394fe2424ae842f70"},
+    {file = "inline_snapshot-0.20.3.tar.gz", hash = "sha256:7a353170b7e42aa89086c7ba790a973c9645523acf985532648dabd7ee2d71f2"},
 ]
 
 [package.dependencies]
@@ -1217,7 +1235,7 @@ executing = ">=2.2.0"
 rich = ">=13.7.1"
 
 [package.extras]
-black = ["black (>=23.3.0)", "click (>=8.1.4)"]
+black = ["black (>=23.3.0)"]
 dirty-equals = ["dirty-equals (>=0.9.0)"]
 
 [[package]]
@@ -1311,13 +1329,13 @@ testing = ["Django", "attrs", "colorama", "docopt", "pytest (<9.0.0)"]
 
 [[package]]
 name = "jinja2"
-version = "3.1.5"
+version = "3.1.6"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "jinja2-3.1.5-py3-none-any.whl", hash = "sha256:aba0f4dc9ed8013c424088f68a5c226f7d6097ed89b246d7749c2ec4175c6adb"},
-    {file = "jinja2-3.1.5.tar.gz", hash = "sha256:8fefff8dc3034e27bb80d67c671eb8a9bc424c0ef4c0826edbff304cceff43bb"},
+    {file = "jinja2-3.1.6-py3-none-any.whl", hash = "sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67"},
+    {file = "jinja2-3.1.6.tar.gz", hash = "sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d"},
 ]
 
 [package.dependencies]
@@ -1695,45 +1713,45 @@ files = [
 
 [[package]]
 name = "matplotlib"
-version = "3.10.0"
+version = "3.10.1"
 description = "Python plotting package"
 optional = false
 python-versions = ">=3.10"
 files = [
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 [package.dependencies]
 typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
+[[package]]
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 version = "2.18.0"
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-]
-
 [[package]]
 name = "requests"
 version = "2.32.3"
@@ -3790,6 +3798,62 @@ dev = ["cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy (==1.10.0)", "pycodest
 doc = ["jupyterlite-pyodide-kernel", "jupyterlite-sphinx (>=0.13.1)", "jupytext", "matplotlib (>=3.5)", "myst-nb", "numpydoc", "pooch", "pydata-sphinx-theme (>=0.15.2)", "sphinx (>=5.0.0,<=7.3.7)", "sphinx-design (>=0.4.0)"]
 test = ["Cython", "array-api-strict (>=2.0)", "asv", "gmpy2", "hypothesis (>=6.30)", "meson", "mpmath", "ninja", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
 
+[[package]]
+name = "sentry-sdk"
+version = "2.22.0"
+description = "Python client for Sentry (https://sentry.io)"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "sentry_sdk-2.22.0-py2.py3-none-any.whl", hash = "sha256:3d791d631a6c97aad4da7074081a57073126c69487560c6f8bffcf586461de66"},
+    {file = "sentry_sdk-2.22.0.tar.gz", hash = "sha256:b4bf43bb38f547c84b2eadcefbe389b36ef75f3f38253d7a74d6b928c07ae944"},
+]
+
+[package.dependencies]
+certifi = "*"
+urllib3 = ">=1.26.11"
+
+[package.extras]
+aiohttp = ["aiohttp (>=3.5)"]
+anthropic = ["anthropic (>=0.16)"]
+arq = ["arq (>=0.23)"]
+asyncpg = ["asyncpg (>=0.23)"]
+beam = ["apache-beam (>=2.12)"]
+bottle = ["bottle (>=0.12.13)"]
+celery = ["celery (>=3)"]
+celery-redbeat = ["celery-redbeat (>=2)"]
+chalice = ["chalice (>=1.16.0)"]
+clickhouse-driver = ["clickhouse-driver (>=0.2.0)"]
+django = ["django (>=1.8)"]
+falcon = ["falcon (>=1.4)"]
+fastapi = ["fastapi (>=0.79.0)"]
+flask = ["blinker (>=1.1)", "flask (>=0.11)", "markupsafe"]
+grpcio = ["grpcio (>=1.21.1)", "protobuf (>=3.8.0)"]
+http2 = ["httpcore[http2] (==1.*)"]
+httpx = ["httpx (>=0.16.0)"]
+huey = ["huey (>=2)"]
+huggingface-hub = ["huggingface_hub (>=0.22)"]
+langchain = ["langchain (>=0.0.210)"]
+launchdarkly = ["launchdarkly-server-sdk (>=9.8.0)"]
+litestar = ["litestar (>=2.0.0)"]
+loguru = ["loguru (>=0.5)"]
+openai = ["openai (>=1.0.0)", "tiktoken (>=0.3.0)"]
+openfeature = ["openfeature-sdk (>=0.7.1)"]
+opentelemetry = ["opentelemetry-distro (>=0.35b0)"]
+opentelemetry-experimental = ["opentelemetry-distro"]
+pure-eval = ["asttokens", "executing", "pure_eval"]
+pymongo = ["pymongo (>=3.1)"]
+pyspark = ["pyspark (>=2.4.4)"]
+quart = ["blinker (>=1.1)", "quart (>=0.16.1)"]
+rq = ["rq (>=0.6)"]
+sanic = ["sanic (>=0.8)"]
+sqlalchemy = ["sqlalchemy (>=1.2)"]
+starlette = ["starlette (>=0.19.1)"]
+starlite = ["starlite (>=1.48)"]
+statsig = ["statsig (>=0.55.3)"]
+tornado = ["tornado (>=6)"]
+unleash = ["UnleashClient (>=6.0.1)"]
+
 [[package]]
 name = "six"
 version = "1.16.0"
@@ -3875,13 +3939,13 @@ widechars = ["wcwidth"]
 
 [[package]]
 name = "termcolor"
-version = "2.4.0"
+version = "2.5.0"
 description = "ANSI color formatting for output in terminal"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "termcolor-2.4.0-py3-none-any.whl", hash = "sha256:9297c0df9c99445c2412e832e882a7884038a25617c60cea2ad69488d4040d63"},
-    {file = "termcolor-2.4.0.tar.gz", hash = "sha256:aab9e56047c8ac41ed798fa36d892a37aca6b3e9159f3e0c24bc64a9b3ac7b7a"},
+    {file = "termcolor-2.5.0-py3-none-any.whl", hash = "sha256:37b17b5fc1e604945c2642c872a3764b5d547a48009871aea3edd3afa180afb8"},
+    {file = "termcolor-2.5.0.tar.gz", hash = "sha256:998d8d27da6d48442e8e1f016119076b690d962507531df4890fcd2db2ef8a6f"},
 ]
 
 [package.extras]
@@ -4383,4 +4447,4 @@ propcache = ">=0.2.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.11"
-content-hash = "9f04c27a16a385191dc91ac21012ea2a48b54d9e4380bcaba72f3106979b4219"
+content-hash = "28a2b74bfafa9f93d14d2f8d1fcaffa340db212acce6469d6714d342203ad77f"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "agentic_security"
-version = "0.4.5"
+version = "0.6.0"
 description = "Agentic LLM vulnerability scanner"
 authors = ["Alexander Miasoiedov <msoedov@gmail.com>"]
 maintainers = ["Alexander Miasoiedov <msoedov@gmail.com>"]
@@ -48,6 +48,11 @@ python-multipart = "^0.0.20"
 tomli = "^2.2.1"
 rich = "13.9.4"
 gTTS = "^2.5.4"
+sentry_sdk = "^2.22.0"
+orjson = "^3.10"
+pyfiglet = "^1.0.2"
+termcolor = "^2.4.0"
+
 # garak = { version = "*", optional = true }
 
 
@@ -81,5 +86,7 @@ build-backend = "poetry.core.masonry.api"
 
 
 [tool.pytest.ini_options]
+addopts = "--durations=5 -m 'not slow'"
 asyncio_mode = "auto"
 asyncio_default_fixture_loop_scope = "function"
+markers = "slow: marks tests as slow"

tests/conftest.py

@@ -0,0 +1,8 @@
+import os
+
+import pytest
+
+
+def pytest_runtest_setup(item):
+    if "slow" in item.keywords and not os.getenv("RUN_SLOW_TESTS"):
+        pytest.skip("Skipping slow test")

tests/test_registry.py

@@ -0,0 +1,26 @@
+import pytest
+from datasets import load_dataset
+
+from agentic_security.probe_data import REGISTRY
+
+
+@pytest.mark.slow
+@pytest.mark.parametrize("dataset", REGISTRY)
+def test_registry_accessibility(dataset):
+    source = dataset.get("source", "")
+    if "hugging" not in source.lower():
+        return pytest.skip("skipped dataset")
+    if not dataset.get("is_active"):
+        return pytest.skip("skipped dataset")
+
+    dataset_name = dataset.get("dataset_name")
+    if not dataset_name:
+        pytest.fail(f"No dataset_name found in {dataset}")
+
+    # Load only metadata (no data download)
+    try:
+        ds = load_dataset(dataset_name, split=None)
+        # Check if metadata is accessible without loading full data
+        assert ds is not None, f"Failed to load metadata for {dataset_name}"
+    except Exception as e:
+        pytest.fail(f"Error loading metadata for {dataset_name}: {str(e)}")

ui/.env.example

@@ -0,0 +1 @@
+VUE_APP_SERVER_URL=''#replace this with  url at which agentic_security server is running 

ui/.eslintrc.js

@@ -0,0 +1,25 @@
+module.exports = {
+    env: {
+      browser: true,
+      es2021: true,
+      node :true
+    },
+    extends: [
+      'eslint:recommended',
+      'plugin:vue/essential',
+    ],
+    parserOptions: {
+      ecmaVersion: 12,
+      sourceType: 'module',
+    },
+    plugins: [
+      'vue',
+    ],
+    rules: {
+      'no-unused-vars': 'off', // Disable the rule
+      'no-constant-condition': 'off',
+      'no-global-assign': 'off',
+      // or
+      // 'no-unused-vars': 'warn', // Change the rule to a warning
+    },
+  };

ui/.gitignore

@@ -0,0 +1,23 @@
+.DS_Store
+node_modules
+/dist
+
+
+# local env files
+.env.local
+.env.*.local
+
+# Log files
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+
+# Editor directories and files
+.idea
+.vscode
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?

ui/babel.config.js

@@ -0,0 +1,5 @@
+module.exports = {
+  presets: [
+    '@vue/cli-plugin-babel/preset'
+  ]
+}

ui/jsconfig.json

@@ -0,0 +1,19 @@
+{
+  "compilerOptions": {
+    "target": "es5",
+    "module": "esnext",
+    "baseUrl": "./",
+    "moduleResolution": "node",
+    "paths": {
+      "@/*": [
+        "src/*"
+      ]
+    },
+    "lib": [
+      "esnext",
+      "dom",
+      "dom.iterable",
+      "scripthost"
+    ]
+  }
+}

ui/package.json

@@ -0,0 +1,45 @@
+{
+  "name": "agentic-vulnerability-scanner-llm-ui",
+  "version": "0.1.0",
+  "private": true,
+  "scripts": {
+    "serve": "vue-cli-service serve ",
+    "dev": "vue-cli-service serve ",
+    "build": "vue-cli-service build",
+    "lint": "vue-cli-service lint"
+  },
+  "dependencies": {
+    "core-js": "^3.8.3",
+    "lucide": "^0.474.0",
+    "vue": "^3.2.13"
+  },
+  "devDependencies": {
+    "@babel/core": "^7.12.16",
+    "@babel/eslint-parser": "^7.12.16",
+    "@vue/cli-plugin-babel": "~5.0.0",
+    "@vue/cli-plugin-eslint": "~5.0.0",
+    "@vue/cli-service": "~5.0.0",
+    "eslint": "^7.32.0",
+    "eslint-plugin-vue": "^8.0.3"
+  },
+  "eslintConfig": {
+    "root": true,
+    "env": {
+      "node": true
+    },
+    "extends": [
+      "plugin:vue/vue3-essential",
+      "eslint:recommended"
+    ],
+    "parserOptions": {
+      "parser": "@babel/eslint-parser"
+    },
+    "rules": {}
+  },
+  "browserslist": [
+    "> 1%",
+    "last 2 versions",
+    "not dead",
+    "not ie 11"
+  ]
+}

ui/public/base.js

@@ -0,0 +1,232 @@
+
+let URL = window.location.href;
+if (URL.endsWith('/')) {
+  URL = URL.slice(0, -1);
+}
+URL = process.env.VUE_APP_SERVER_URL
+
+// Vue application
+ let LLM_SPECS = [
+  `POST ${URL}/v1/self-probe
+Authorization: Bearer XXXXX
+Content-Type: application/json
+
+{
+"prompt": "<<PROMPT>>"
+}
+
+`,
+  `POST https://api.openai.com/v1/chat/completions
+Authorization: Bearer $OPENAI_API_KEY
+Content-Type: application/json
+
+{
+"model": "gpt-3.5-turbo",
+"messages": [{"role": "user", "content": "<<PROMPT>>"}],
+"temperature": 0.7
+}
+`,
+  `
+POST https://api.deepseek.com/chat/completions
+Authorization: Bearer $DEEPSEEK_API_KEY
+Content-Type: application/json
+
+{
+  "model": "deepseek-chat",
+  "messages": [
+    {"role": "system", "content": "You are a helpful assistant."},
+    {"role": "user", "content": "<<PROMPT>>"}
+  ],
+  "stream": false
+}
+`,
+  `POST https://api.replicate.com/v1/models/mistralai/mixtral-8x7b-instruct-v0.1/predictions
+Authorization: Bearer $APIKEY
+Content-Type: application/json
+
+{
+"input": {
+"top_k": 50,
+"top_p": 0.9,
+"prompt": "Write a bedtime story about neural networks I can read to my toddler",
+"temperature": 0.6,
+"max_new_tokens": 1024,
+"prompt_template": "<s>[INST] <<PROMPT>> [/INST] ",
+"presence_penalty": 0,
+"frequency_penalty": 0
+}
+}
+`,
+  `POST https://api.groq.com/v1/request_manager/text_completion
+Authorization: Bearer  XXXXX
+Content-Type: application/json
+
+{
+"model_id": "codellama-34b",
+"system_prompt": "You are helpful and concise coding assistant",
+"user_prompt": "<<PROMPT>>"
+}
+`,
+  `POST https://api.together.xyz/v1/chat/completions
+Authorization: Bearer $TOGETHER_API_KEY
+Content-Type: application/json
+
+{
+"model": "mistralai/Mixtral-8x7B-Instruct-v0.1",
+"messages": [
+{"role": "system", "content": "You are an expert travel guide"},
+{"role": "user", "content": "<<PROMPT>>"}
+]
+}
+`,
+  `POST ${URL}/v1/self-probe-image
+Authorization: Bearer XXXXX
+Content-Type: application/json
+
+[
+    {
+      "role": "user",
+      "content": [
+        {
+          "type": "text",
+          "text": "What is in this image?",
+        },
+        {
+          "type": "image_url",
+          "image_url": {
+            "url":  f"data:image/jpeg;base64,{<<BASE64_IMAGE>>}"
+          },
+        },
+      ],
+    }
+]
+`,
+  `POST ${URL}/v1/self-probe-file
+Authorization: Bearer $GROQ_API_KEY
+Content-Type: multipart/form-data
+
+{
+  "file": "@./sample_audio.m4a",
+  "model": "whisper-large-v3"
+}
+`,
+  `POST https://api.gemini.com/v1/generate
+Authorization: Bearer $GEMINI_API_KEY
+Content-Type: application/json
+
+{
+  "model": "gemini-latest",
+  "prompt": "<<PROMPT>>",
+  "temperature": 0.8,
+  "max_tokens": 150,
+  "top_p": 1.0,
+  "frequency_penalty": 0,
+  "presence_penalty": 0
+}
+`,
+  `POST https://api.anthropic.com/v1/complete
+Authorization: Bearer $ANTHROPIC_API_KEY
+Content-Type: application/json
+
+{
+  "model": "claude-v1.3",
+  "prompt": "<<PROMPT>>",
+  "temperature": 0.7,
+  "max_tokens_to_sample": 256,
+  "stop_sequences": ["\n\nHuman:"]
+}
+`,
+  `POST https://api.cohere.ai/generate
+Authorization: Bearer $COHERE_API_KEY
+Content-Type: application/json
+
+{
+  "model": "command-xlarge-nightly",
+  "prompt": "<<PROMPT>>",
+  "max_tokens": 300,
+  "temperature": 0.75,
+  "k": 0,
+  "p": 0.75
+}
+`,
+
+  `POST https://<<RESOURCE_NAME>>.openai.azure.com/openai/deployments/<<DEPLOYMENT_NAME>>/completions?api-version=2023-06-01-preview
+Authorization: Bearer $AZURE_API_KEY
+Content-Type: application/json
+
+{
+  "prompt": "<<PROMPT>>",
+  "max_tokens": 150,
+  "temperature": 0.7,
+  "top_p": 0.9,
+  "frequency_penalty": 0,
+  "presence_penalty": 0
+}
+`,
+
+  `POST https://api.assemblyai.com/v2/transcript
+Authorization: Bearer $ASSEMBLY_API_KEY
+Content-Type: application/json
+
+{
+  "audio_url": "<<AUDIO_FILE_URL>>"
+}
+`,
+
+]
+
+ let LLM_CONFIGS = [
+  { name: 'Custom API', prompts: 40000, customInstructions: 'Requires api spec' },
+  { name: 'Open AI', prompts: 24000 },
+  { name: 'Deepseek v1', prompts: 24000 },
+  { name: 'Replicate', prompts: 40000 },
+  { name: 'Groq', prompts: 40000 },
+  { name: 'Together.ai', prompts: 40000 },
+  { name: 'Custom API Image', prompts: 40000, customInstructions: 'Requires api spec', modality: 'Image' },
+  { name: 'Custom API Files', prompts: 40000, customInstructions: 'Requires api spec', modality: 'Files' },
+  { name: 'Gemini', prompts: 40000 },
+  { name: 'Claude', prompts: 40000 },
+  { name: 'Cohere', prompts: 40000 },
+  { name: 'Azure OpenAI', prompts: 40000 },
+  { name: 'assemblyai', prompts: 40000 },
+
+
+]
+
+function has_image(spec) {
+  return spec.includes('<<BASE64_IMAGE>>');
+}
+
+function has_files(spec) {
+  return spec.includes('multipart/form-data');
+}
+
+
+function _getFailureRateColor(failureRate) {
+  // We're now working with the strength percentage, so no need to invert
+  const strengthRate = 100 - failureRate;
+
+  if (strengthRate >= 95) return 'text-green-400';
+  else if (strengthRate >= 85) return 'text-green-400';
+  else if (strengthRate >= 75) return 'text-green-500';
+  else if (strengthRate >= 65) return 'text-yellow-400';
+  else if (strengthRate >= 55) return 'text-yellow-500';
+  else if (strengthRate >= 45) return 'text-orange-400';
+  else if (strengthRate >= 35) return 'text-orange-500';
+  else if (strengthRate >= 25) return 'text-dark-accent-red';
+  else if (strengthRate >= 15) return 'text-red-400';
+  else if (strengthRate > 0) return 'text-red-500';
+  else return 'text-gray-100'; // This can be the default for strengthRate of 0 or less
+}
+
+function _getFailureRateScore(failureRate) {
+  // Convert failureRate to a strength percentage
+  const strengthRate = 100 - failureRate;
+
+  if (strengthRate >= 90) return 'A';
+  else if (strengthRate >= 80) return 'B';
+  else if (strengthRate >= 70) return 'C';
+  else if (strengthRate >= 60) return 'D';
+  else return 'E'; // For strengthRate less than 60
+}
+export { LLM_SPECS, LLM_CONFIGS, has_image, has_files, _getFailureRateColor, _getFailureRateScore ,URL };

ui/public/index.html

@@ -0,0 +1,22 @@
+<!DOCTYPE html>
+<html lang="en" class="dark">
+  <header>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>LLM Vulnerability Scanner</title>
+   
+    <script src="https://unpkg.com/lucide@latest/dist/umd/lucide.js"></script>
+    <link href="https://fonts.cdnfonts.com/css/technopollas" rel="stylesheet">
+    <link href="styles/output.css" rel="stylesheet">
+
+  </header>
+  <body class="bg-dark-bg text-dark-text font-sans"> 
+   
+    <noscript>
+      <strong>We're sorry but <%= htmlWebpackPlugin.options.title %> doesn't work properly without JavaScript enabled. Please enable it to continue.</strong>
+    </noscript>
+    <div id="vue-app" class="min-h-screen p-8"></div>
+  
+   
+  </body>
+</html>

ui/public/styles/styles.css

@@ -0,0 +1,11 @@
+@tailwind base;
+@tailwind components;
+@tailwind utilities;
+@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700&display=swap');
+.scrollbar-hide::-webkit-scrollbar {
+  display: none;
+}
+.scrollbar-hide {
+  -ms-overflow-style: none;  /* IE and Edge */
+  scrollbar-width: none;     /* Firefox */
+}

ui/public/telemetry.js

@@ -0,0 +1,4 @@
+!function (t, e) { var o, n, p, r; e.__SV || (window.posthog = e, e._i = [], e.init = function (i, s, a) { function g(t, e) { var o = e.split("."); 2 == o.length && (t = t[o[0]], e = o[1]), t[e] = function () { t.push([e].concat(Array.prototype.slice.call(arguments, 0))) } } (p = t.createElement("script")).type = "text/javascript", p.async = !0, p.src = s.api_host.replace(".i.posthog.com", "-assets.i.posthog.com") + "/static/array.js", (r = t.getElementsByTagName("script")[0]).parentNode.insertBefore(p, r); var u = e; for (void 0 !== a ? u = e[a] = [] : a = "posthog", u.people = u.people || [], u.toString = function (t) { var e = "posthog"; return "posthog" !== a && (e += "." + a), t || (e += " (stub)"), e }, u.people.toString = function () { return u.toString(1) + ".people (stub)" }, o = "init push capture register register_once register_for_session unregister unregister_for_session getFeatureFlag getFeatureFlagPayload isFeatureEnabled reloadFeatureFlags updateEarlyAccessFeatureEnrollment getEarlyAccessFeatures on onFeatureFlags onSessionId getSurveys getActiveMatchingSurveys renderSurvey canRenderSurvey getNextSurveyStep identify setPersonProperties group resetGroups setPersonPropertiesForFlags resetPersonPropertiesForFlags setGroupPropertiesForFlags resetGroupPropertiesForFlags reset get_distinct_id getGroups get_session_id get_session_replay_url alias set_config startSessionRecording stopSessionRecording sessionRecordingStarted loadToolbar get_property getSessionProperty createPersonProfile opt_in_capturing opt_out_capturing has_opted_in_capturing has_opted_out_capturing clear_opt_in_out_capturing debug".split(" "), n = 0; n < o.length; n++)g(u, o[n]); e._i.push([i, s, a]) }, e.__SV = 1) }(document, window.posthog || []);
+window.posthog.init('phc_jfYo5xEofW7eJtiU8rLt2Z8jw1E2eW27BxwTJzwRufH', {
+    api_host: 'https://us.i.posthog.com', person_profiles: 'identified_only' // or 'always' to create profiles for anonymous users as well
+})

ui/src/App.vue

@@ -0,0 +1,52 @@
+<template>
+  <div>
+         <div
+        class="bg-dark-accent-green text-dark-bg py-4 px-6 rounded-lg mb-28 text-center">
+        <h4 class="text-lg font-semibold">
+          🚀 NEW: Star Agentic Security on
+          <a href="https://github.com/msoedov/agentic_security" target="_blank"
+            class="underline" data-faitracker-click-bind="true">Github</a> 🚀
+        </h4>
+      </div>
+
+      <!-- Header with Github link -->
+      <header class="flex justify-between items-center mb-8 relative"
+        v-if="false">
+        <div class="w-full absolute left-0 flex justify-center">
+          <h1
+            class="text-2xl font-bold text-gray-400"> <span
+              class="text-2xl font-technopollas  text-gray-300">Agentic
+            </span>
+
+            Vulnerability
+            Scanner</h1>
+        </div>
+</header>
+<PageContent/>
+<PageConfigs/>
+    <PageFooter />
+    </div>
+  
+</template>
+
+<script>
+import PageFooter from "./components/PageFooter.vue";
+import PageContent from "./components/PageContent.vue";
+import PageConfigs from "./components/PageConfigs.vue";
+
+
+
+
+
+export default {
+  components: {
+    PageFooter,
+    PageContent,
+    PageConfigs
+  }
+};
+</script>
+
+<style scoped>
+/* Global styles or App.vue specific styles */
+</style>

ui/src/components/LLMSpecInput.vue

@@ -0,0 +1,58 @@
+<template>
+  <section class="bg-dark-card rounded-lg p-6 shadow-lg">
+    <div @click="toggleLLMSpec" class="flex justify-between items-center cursor-pointer">
+      <h2 class="text-2xl font-bold">LLM API Spec</h2>
+      </div>
+
+    <div v-show="showLLMSpec" class="mt-4">
+      <label v-if="isFocused" for="llm-spec" class="block text-sm font-medium mb-2">
+        LLM API Spec, PROMPT variable will be replaced with the testing prompt
+      </label>
+      </div>
+  </section>
+</template>
+
+<script>
+export default {
+  name: 'LLMSpecInput',
+  data() {
+    return {
+      showLLMSpec: false,
+      isFocused: false,
+       modelSpec: '',
+      errorMsg: null,
+      okMsg: null,
+    };
+  },
+  methods: {
+       toggleLLMSpec() {
+      this.showLLMSpec = !this.showLLMSpec;
+    },
+    focusTextarea() {
+      this.isFocused = true;
+    },
+    unfocusTextarea() {
+      this.isFocused = false;
+    },
+    adjustHeight(event) {
+      event.target.style.height = 'auto';
+      event.target.style.height = event.target.scrollHeight + 'px';
+    },
+    verifyIntegration() {
+      // Your logic for verifying integration
+    },
+  },
+  computed: {
+    highlightedText() {
+      // Your logic for highlighted text
+    },
+     statusDotClass() {
+      // Your logic for status dot class
+    },
+  },
+};
+</script>
+
+<style scoped>
+/* Styles for the LLM Spec Input */
+</style>

ui/src/components/PageConfigs.vue

@@ -0,0 +1,907 @@
+<template>
+     <main class="max-w-6xl mx-auto space-y-8">
+        <section class="bg-dark-card rounded-lg p-6 shadow-lg">
+          <h2 class="text-2xl font-bold mb-4">Select a Config</h2>
+
+          <div class="flex space-x-4 overflow-x-auto scrollbar-hide">
+            <div
+              v-for="(config, index) in configs"
+              :key="index"
+              @click="selectConfig(index)"
+              class="flex-none w-1/2 sm:w-1/3 md:w-1/4 lg:w-1/5 border-2 rounded-lg p-4 flex flex-col items-start transition-all hover:shadow-md cursor-pointer"
+              :class="{
+        'border-dark-accent-green': selectedConfig === index,
+        'border-gray-600': selectedConfig !== index
+      }">
+              <div class="font-medium mb-2">{{ config.name }}</div>
+              <div class="text-sm text-gray-400">
+                {{ config.customInstructions || 'Requires API key' }}
+              </div>
+              <div class="mt-2 text-dark-accent-green font-semibold">
+                {{config.modality || 'API'}}</div>
+            </div>
+          </div>
+        </section>
+
+        <!-- Collapsible LLM Spec Input -->
+        <section class="bg-dark-card rounded-lg p-6 shadow-lg" >
+          <div @click="toggleLLMSpec"
+            class="flex justify-between items-center cursor-pointer">
+
+            <h2 class="text-2xl font-bold">LLM API Spec</h2>
+            <span :class="statusDotClass"
+              class="w-3 h-3 rounded-full mr-2"></span>
+            <svg :class="{'rotate-180': showLLMSpec}"
+              class="w-6 h-6 transition-transform duration-200"
+              xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none"
+              stroke="currentColor" stroke-width="2" stroke-linecap="round"
+              stroke-linejoin="round">
+              <polyline points="6 9 12 15 18 9"></polyline>
+            </svg>
+          </div>
+
+          <div v-show="showLLMSpec" class="mt-4">
+            <label v-if="isFocused" for="llm-spec"
+              class="block text-sm font-medium mb-2">
+              LLM API Spec, PROMPT variable will be replaced with the testing
+              prompt
+            </label>
+            <div
+              v-if="!isFocused"
+              
+              class="w-full bg-dark-bg text-dark-accent-orange border border-gray-600 rounded-lg p-3 cursor-text mb-5"
+              @click="focusTextarea"
+              v-html="highlightedText"></div>
+
+            <textarea
+              v-else
+              ref="textarea"
+              class="w-full bg-dark-bg text-dark-accent-orange border border-gray-600 rounded-lg p-3 focus:outline-none focus:ring-2 focus:ring-dark-accent-green"
+              @blur="unfocusTextarea"
+              v-model="modelSpec"
+              @input="adjustHeight"
+              rows="5"
+              placeholder="Enter LLM API Spec here..."></textarea>
+
+            <!-- Error and Success Messages -->
+            <div v-if="errorMsg"
+              class="bg-dark-accent-red bg-opacity-20 border border-dark-accent-red text-dark-accent-red px-4 py-3 rounded-lg relative"
+              role="alert">
+              <strong class="font-bold">Oops!</strong>
+              <span class="block sm:inline">{{errorMsg}}</span>
+            </div>
+            <div v-if="okMsg"
+              class="bg-dark-accent-green bg-opacity-20 border border-dark-accent-green text-dark-accent-green px-4 py-3 rounded-lg relative"
+              role="alert">
+              <strong class="font-bold"></strong>
+              <span class="block sm:inline">{{okMsg}}</span>
+            </div>
+
+            <!-- Action Buttons -->
+            <section class="flex justify-center space-x-4 mt-10">
+              <button
+                @click="verifyIntegration"
+                class="bg-dark-accent-orange text-dark-bg rounded-lg px-6 py-3 font-medium hover:bg-opacity-80 transition-colors">
+                Verify Integration
+              </button>
+            </section>
+          </div>
+        </section>
+        <!-- LLM Spec Input -->
+     <section class="bg-dark-card rounded-lg p-6 shadow-lg" v-if="false" >
+          <h2 class="text-2xl font-bold mb-4">LLM API Spec</h2>
+          <label for="llm-spec" class="block text-sm font-medium mb-2">
+            LLM API Spec, PROMPT variable will be replaced with the testing
+            prompt
+          </label>
+          <textarea
+            class="w-full bg-dark-bg text-dark-accent-orange border border-gray-600 rounded-lg p-3 focus:outline-none focus:ring-2 focus:ring-dark-accent-green"
+            id="llm-spec"
+            ref="textarea"
+            v-model="modelSpec"
+            @input="adjustHeight"
+            rows="5"
+            placeholder="Enter LLM API Spec here..."></textarea>
+        </section>
+        <section
+          class="bg-dark-card rounded-lg p-6 shadow-lg mt-8 border-dark-accent-green border-2">
+          <div @click="toggleParams"
+            class="flex justify-between items-center cursor-pointer">
+            <div class="flex items-center">
+              <svg xmlns="http://www.w3.org/2000/svg" class="h-6 w-6 mr-2"
+                fill="none" viewBox="0 0 24 24" stroke="currentColor">
+                <path stroke-linecap="round" stroke-linejoin="round"
+                  stroke-width="2"
+                  d="M12 6V4m0 2a2 2 0 100 4m0-4a2 2 0 110 4m-6 8a2 2 0 100-4m0 4a2 2 0 110-4m0 4v2m0-6V4m6 6v10m6-2a2 2 0 100-4m0 4a2 2 0 110-4m0 4v2m0-6V4" />
+              </svg>
+              <h2 class="text-2xl font-bold">Parameters</h2>
+            </div>
+            <svg :class="{'rotate-180': showParams}"
+              class="w-6 h-6 transition-transform duration-200"
+              xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none"
+              stroke="currentColor" stroke-width="2" stroke-linecap="round"
+              stroke-linejoin="round">
+              <polyline points="6 9 12 15 18 9"></polyline>
+            </svg>
+          </div>
+          <div v-show="showParams" class="mt-4">
+            <div class="flex items-center justify-end mt-4">
+              <button
+                @click="confirmResetState"
+                class="flex items-center bg-dark-accent-red text-dark-bg rounded-lg px-4 py-2 text-sm font-medium hover:bg-opacity-80 transition-colors">
+                <svg xmlns="http://www.w3.org/2000/svg" class="h-5 w-5 mr-2"
+                  fill="none" viewBox="0 0 24 24" stroke="currentColor">
+                  <path stroke-linecap="round" stroke-linejoin="round"
+                    stroke-width="2"
+                    d="M4 4v5h.582m15.356 2A8.001 8.001 0 004.582 9m0 0H9m11 11v-5h-.581m0 0a8.003 8.003 0 01-15.357-2m15.357 2H15" />
+                </svg>
+                Reset State
+              </button>
+            </div>
+            <!-- Confirmation Modal -->
+            <div
+              v-if="showResetConfirmation"
+              class="fixed inset-0 bg-black bg-opacity-50 flex items-center justify-center z-50">
+              <div class="bg-dark-card rounded-lg p-6 max-w-sm w-full">
+                <h3 class="text-xl font-bold mb-4 text-dark-text">Confirm
+                  Reset</h3>
+                <p class="text-gray-400 mb-6">Are you sure you want to reset all
+                  settings to their default state? This action cannot be
+                  undone.</p>
+                <div class="flex justify-end space-x-4">
+                  <button
+                    @click="showResetConfirmation = false"
+                    class="bg-gray-600 text-dark-text rounded-lg px-4 py-2 hover:bg-opacity-80 transition-colors">
+                    Cancel
+                  </button>
+                  <button
+                    @click="resetState"
+                    class="bg-dark-accent-red text-dark-bg rounded-lg px-4 py-2 hover:bg-opacity-80 transition-colors">
+                    Reset
+                  </button>
+                </div>
+              </div>
+            </div>
+            <!-- Confirmation Modal -->
+
+            <!-- Maximum Budget Slider -->
+            <!-- Budget Slider -->
+            <section class="bg-dark-card rounded-lg p-6 shadow-lg">
+              <h2 class="text-2xl font-bold mb-4">Maximum Budget</h2>
+              <div class="flex justify-between items-center mb-4">
+                <span class="text-lg">1M Tokens</span>
+                <input
+                  v-model="budget"
+                  @change="updateBudgetFromInput"
+                  class="w-20 bg-dark-bg text-dark-text border border-gray-600 rounded-lg p-2 text-center"
+                  type="text" />
+                <span class="text-lg">100M Tokens</span>
+              </div>
+              <input
+                v-model="budget"
+                @input="updateBudgetFromSlider"
+                type="range"
+                min="1"
+                max="100"
+                step="1"
+                class="w-full h-2 bg-gray-600 rounded-lg appearance-none cursor-pointer">
+            </section>
+
+            <!-- Optimize Toggle -->
+            <div class="flex flex-col mt-6 mr-10 ml-10">
+              <div class="flex items-center justify-between mb-2">
+                <h3 class="text-lg font-semibold">Optimize Test</h3>
+                <label class="relative inline-flex items-center cursor-pointer">
+                  <input type="checkbox" v-model="optimize"
+                    class="sr-only peer">
+                  <div
+                    class="w-11 h-6 bg-gray-200 peer-focus:outline-none peer-focus:ring-4 peer-focus:ring-dark-accent-green rounded-full peer peer-checked:after:translate-x-full peer-checked:after:border-white after:content-[''] after:absolute after:top-[2px] after:left-[2px] after:bg-white after:border-gray-300 after:border after:rounded-full after:h-5 after:w-5 after:transition-all peer-checked:bg-dark-accent-green"></div>
+                </label>
+              </div>
+              <p class="text-sm text-gray-400 mt-2 mb-6">
+                When enabled, this option runs a Bayesian optimization loop to
+                find the most effective test parameters. This can potentially
+                reduce the cost and the total running time of your vulnerability
+                scan, but may reduce accuracy.
+              </p>
+
+              <!-- Chart Diagram Toggle -->
+              <div class="flex items-center justify-between mb-2">
+                <h3 class="text-lg font-semibold">Enable Chart Diagram</h3>
+                <label class="relative inline-flex items-center cursor-pointer">
+                  <input type="checkbox" v-model="enableChartDiagram"
+                    class="sr-only peer">
+                  <div
+                    class="w-11 h-6 bg-gray-200 peer-focus:outline-none peer-focus:ring-4 peer-focus:ring-dark-accent-green rounded-full peer peer-checked:after:translate-x-full peer-checked:after:border-white after:content-[''] after:absolute after:top-[2px] after:left-[2px] after:bg-white after:border-gray-300 after:border after:rounded-full after:h-5 after:w-5 after:transition-all peer-checked:bg-dark-accent-green"></div>
+                </label>
+              </div>
+              <p class="text-sm text-gray-400 mt-2 mb-6">
+                When enabled, a chart diagram will be generated to visualize the
+                results of your vulnerability scan.
+              </p>
+
+              <!-- Logging Toggle -->
+              <div class="flex items-center justify-between mb-2">
+                <h3 class="text-lg font-semibold">Enable Detailed Logging</h3>
+                <label class="relative inline-flex items-center cursor-pointer">
+                  <input type="checkbox" v-model="enableLogging"
+                    class="sr-only peer">
+                  <div
+                    class="w-11 h-6 bg-gray-200 peer-focus:outline-none peer-focus:ring-4 peer-focus:ring-dark-accent-green rounded-full peer peer-checked:after:translate-x-full peer-checked:after:border-white after:content-[''] after:absolute after:top-[2px] after:left-[2px] after:bg-white after:border-gray-300 after:border after:rounded-full after:h-5 after:w-5 after:transition-all peer-checked:bg-dark-accent-green"></div>
+                </label>
+              </div>
+              <p class="text-sm text-gray-400 mt-2 mb-6">
+                When enabled, detailed logs will be generated during the
+                vulnerability scan process. This can be useful for debugging and
+                in-depth analysis.
+              </p>
+
+              <!-- Concurrency Toggle -->
+              <div class="flex items-center justify-between mb-2">
+                <h3 class="text-lg font-semibold">Enable Concurrency</h3>
+                <label class="relative inline-flex items-center cursor-pointer">
+                  <input type="checkbox" v-model="enableConcurrency"
+                    class="sr-only peer">
+                  <div
+                    class="w-11 h-6 bg-gray-200 peer-focus:outline-none peer-focus:ring-4 peer-focus:ring-dark-accent-green rounded-full peer peer-checked:after:translate-x-full peer-checked:after:border-white after:content-[''] after:absolute after:top-[2px] after:left-[2px] after:bg-white after:border-gray-300 after:border after:rounded-full after:h-5 after:w-5 after:transition-all peer-checked:bg-dark-accent-green"></div>
+                </label>
+              </div>
+              <p class="text-sm text-gray-400 mt-2">
+                When enabled, the vulnerability scan will run multiple tests
+                concurrently. This can significantly reduce the total scan time
+                but may increase resource usage.
+              </p>
+            </div>
+          </div>
+        </section>
+
+        <!-- Modules Selection -->
+        <section
+          class="bg-dark-card rounded-lg p-6 shadow-lg border-dark-accent-red border-4">
+          <div @click="toggleModules"
+            class="flex justify-between items-center cursor-pointer">
+            <h2 class="text-2xl font-bold">Modules [{{selectedDS}}
+              selected]</h2>
+            <svg :class="{'rotate-180': showModules}"
+              class="w-6 h-6 transition-transform duration-200"
+              xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none"
+              stroke="currentColor" stroke-width="2" stroke-linecap="round"
+              stroke-linejoin="round">
+              <polyline points="6 9 12 15 18 9"></polyline>
+            </svg>
+          </div>
+
+          <div v-show="showModules" class="mt-4">
+            <!-- Many-shot jailbreaking Toggle -->
+            <div v-if="enableMultiStepAttack" class="alert-box mt-4">
+              <div
+                class="bg-yellow-100 border border-yellow-400 text-yellow-700 px-4 py-3 rounded relative"
+                role="alert">
+                <strong class="font-bold">Notice:</strong>
+                <span class="block sm:inline">A many-shot attack might take a
+                  longer time to complete.
+                </span>
+              </div>
+            </div>
+            <div class="flex items-center justify-between mb-2 mt-10">
+              <h3 class="text-lg font-semibold">Enable Many-shot
+                jailbreaking</h3>
+
+              <label class="relative inline-flex items-center cursor-pointer">
+                <input type="checkbox" v-model="enableMultiStepAttack"
+                  class="sr-only peer">
+                <div
+                  class="w-11 h-6 bg-gray-200 peer-focus:outline-none peer-focus:ring-4 peer-focus:ring-dark-accent-green rounded-full peer peer-checked:after:translate-x-full peer-checked:after:border-white after:content-[''] after:absolute after:top-[2px] after:left-[2px] after:bg-white after:border-gray-300 after:border after:rounded-full after:h-5 after:w-5 after:transition-all peer-checked:bg-dark-accent-green"></div>
+              </label>
+            </div>
+            <p class="text-sm text-gray-400 mt-2 mb-2">
+              When enabled, the scan will attempt Many-shot jailbreaking
+              simulations
+            </p>
+
+            <div v-if="hasFileSpec" class="alert-box mt-10">
+              <div
+                class="bg-yellow-100 border border-yellow-400 text-yellow-700 px-4 py-3 rounded relative"
+                role="alert">
+                <strong class="font-bold">Notice:</strong>
+                <span class="block sm:inline">Converting audio or image prompts
+                  might
+                  take some time to compute.</span>
+              </div>
+            </div>
+
+            <div class="flex justify-between mb-4 mt-4">
+              <button @click="selectAllPackages"
+                class="text-dark-accent-green hover:underline">Select
+                All</button>
+              <button @click="deselectAllPackages"
+                class="text-gray-400 hover:underline">Deselect All</button>
+            </div>
+
+            <div class="grid grid-cols-1 sm:grid-cols-2 md:grid-cols-3 gap-4">
+              <div
+                v-for="(pkg, index) in dataConfig"
+                :key="index"
+                @click="addPackage(index)"
+                class="border rounded-lg p-3 cursor-pointer transition-all hover:shadow-md overflow-hidden"
+                :class="{
+                'border-dark-accent-green bg-dark-accent-green bg-opacity-20': pkg.selected,
+                'border-gray-600': !pkg.selected
+              }">
+                <div class="font-medium mb-1 truncate">{{ pkg.dataset_name
+                  }}</div>
+                <div class="text-sm text-gray-400 truncate">
+                  {{ pkg.source || 'Local dataset' }}
+                </div>
+                <div class="mt-2 text-sm font-semibold">
+                  {{ pkg.dynamic ? 'Dynamic dataset' :
+                  `${pkg.num_prompts.toLocaleString()} prompts` }}
+                </div>
+              </div>
+            </div>
+          </div>
+        </section>
+
+        <!-- Error and Success Messages -->
+        <div v-if="errorMsg"
+          class="bg-dark-accent-red bg-opacity-20 border border-dark-accent-red text-dark-accent-red px-4 py-3 rounded-lg relative"
+          role="alert">
+          <strong class="font-bold">Oops!</strong>
+          <span class="block sm:inline">{{errorMsg}}</span>
+        </div>
+        <div v-if="okMsg"
+          class="bg-dark-accent-green bg-opacity-20 border border-dark-accent-green text-dark-accent-green px-4 py-3 rounded-lg relative"
+          role="alert">
+          <strong class="font-bold">></strong>
+          <span class="block sm:inline">{{okMsg}}</span>
+        </div>
+
+        <!-- Action Buttons -->
+        <section class="flex justify-center space-x-4">
+          <button
+            @click="verifyIntegration"
+            class="bg-dark-accent-orange text-dark-bg rounded-lg px-6 py-3 font-medium hover:bg-opacity-80 transition-colors">
+            Verify Integration
+          </button>
+          <button
+            @click="startScan"
+            v-if="!scanRunning"
+            class="bg-dark-accent-green text-dark-bg rounded-lg px-6 py-3 font-medium hover:bg-opacity-80 transition-colors flex items-center">
+            <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24"
+              viewBox="0 0 24 24" fill="none" stroke="currentColor"
+              stroke-width="2" stroke-linecap="round" stroke-linejoin="round"
+              class="mr-2"><polygon points="5 3 19 12 5 21 5 3"></polygon></svg>
+            Run Scan
+          </button>
+          <button
+            @click="stopScan"
+            v-if="scanRunning"
+            class="bg-dark-accent-red text-dark-bg rounded-lg px-6 py-3 font-medium hover:bg-opacity-80 transition-colors flex items-center">
+            <!-- Stop Icon -->
+            <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24"
+              viewBox="0 0 24 24" fill="none" stroke="currentColor"
+              stroke-width="2" stroke-linecap="round" stroke-linejoin="round"
+              class="mr-2"><rect x="6" y="6" width="12"
+                height="12"></rect></svg>
+            Stop Scan
+          </button>
+        </section>
+
+        <!-- Progress Bar -->
+        <div id="progress"
+          class="bg-dark-accent-green rounded-full h-2 transition-all duration-500 ease-in-out"
+          v-bind:style="{width: progressWidth}">
+        </div>
+
+        <!-- Scan Results -->
+        <section class="bg-dark-card rounded-lg p-6 shadow-lg"
+          v-if="mainTable.length > 0">
+          <h2 class="text-2xl font-bold mb-4">Scan Results</h2>
+          <div class="overflow-x-auto">
+            <table class="w-full text-left">
+              <thead>
+                <tr class="border-b border-gray-600">
+                  <th class="p-3">Vulnerability Module</th>
+                  <th class="p-3">% Strength</th>
+                  <th class="p-3">Number of Tokens</th>
+                  <th class="p-3">Cost (in gpt-3 tokens)</th>
+                </tr>
+              </thead>
+              <tbody>
+                <tr v-for="result in mainTable" :key="result.module || index" class="border-b border-gray-700"
+                  :class="{'text-dark-accent-green': result.last, 'text-gray-300': !result.last}">
+                  <td class="p-3">{{result.module}}</td>
+                  <td class="p-3 text-gray-100"
+                    :class="getFailureRateColor(result.failureRate)">
+                    {{getFailureRateScore(result.failureRate)}}( {{(100 -
+                    result.failureRate).toFixed(2)}} )
+                  </td>
+                  <td class="p-3">{{result.tokens}}k</td>
+                  <td class="p-3">${{result.cost.toFixed(2)}}</td>
+                </tr>
+              </tbody>
+            </table>
+          </div>
+        </section>
+
+        <!-- Download Button -->
+        <button
+          @click="downloadFailures"
+          class="bg-dark-accent-yellow text-dark-bg rounded-lg px-6 py-3 font-medium hover:bg-opacity-80 transition-colors">
+          Download failures
+        </button>
+
+        <!-- Report Image -->
+        <img :src="reportImageUrl" alt="Generated Plot" v-if="reportImageUrl"
+          loading="lazy" class="mx-auto rounded-lg shadow-lg">
+
+        <!-- Logs Section -->
+        <section class="bg-dark-card rounded-lg p-6 shadow-lg mt-8">
+          <div @click="toggleLogs"
+            class="flex justify-between items-center cursor-pointer">
+            <h2 class="text-2xl font-bold">Logs</h2>
+            <svg :class="{'rotate-180': showLogs}"
+              class="w-6 h-6 transition-transform duration-200"
+              xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none"
+              stroke="currentColor" stroke-width="2" stroke-linecap="round"
+              stroke-linejoin="round">
+              <polyline points="6 9 12 15 18 9"></polyline>
+            </svg>
+          </div>
+
+          <div v-show="showLogs" class="mt-4">
+            <div class="mb-4 flex justify-between items-center">
+              <span class="text-sm text-gray-400">Showing latest {{
+                Math.min(logs.length, maxDisplayedLogs) }} of {{ logs.length }}
+                logs</span>
+              <button @click="downloadLogs"
+                class="bg-dark-accent-green text-dark-bg rounded-lg px-4 py-2 text-sm font-medium hover:bg-opacity-80 transition-colors">
+                Download Logs
+              </button>
+            </div>
+            <div class="bg-dark-bg p-4 rounded-lg max-h-96 overflow-y-auto">
+              <div v-for="(log, index) in displayedLogs" :key="index"
+                class="mb-2 last:mb-0">
+                <span class="text-dark-accent-green">{{ log.timestamp }}</span>
+                <span class="ml-2"
+                  :class="{'text-dark-accent-red': log.level === 'ERROR'}">{{
+                  log.message }}</span>
+              </div>
+            </div>
+          </div>
+        </section>
+      </main>
+</template>
+<script>
+import { LLM_CONFIGS, LLM_SPECS,has_image, has_files, _getFailureRateColor, _getFailureRateScore,URL } from '../../public/base.js';
+import { ref, useTemplateRef, onMounted } from 'vue'
+
+const textarea= useTemplateRef('textarea')
+export default{
+    name: 'PageConfigs',
+    data(){
+        return {
+        progressWidth: '0%',
+        modelSpec: LLM_SPECS[0],
+        budget: 50,
+        isFocused: false, // Tracks if the textarea is focused
+        showParams: false,
+        showResetConfirmation: false,
+        enableChartDiagram: true,
+        enableLogging: false,
+        enableConcurrency: false,
+        optimize: false,
+        enableMultiStepAttack: false,
+        scanResults: [],
+        mainTable: [],
+        integrationVerified: false,
+        scanRunning: false,
+        errorMsg: '',
+        maskMode: false,
+        okMsg: '',
+        reportImageUrl: '',
+        selectedConfig: 0,
+        showModules: false,
+        showLogs: false,
+        showConsentModal: true,
+        statusDotClass: 'bg-gray-500', // Default status dot class
+        statusText: 'Verified', // Default status text
+        statusClass: 'bg-green-500 text-dark-bg', // Default status class
+        showLLMSpec: true, // Default to showing the LLM Spec Input
+        logs: [], // This will store all the logs
+        maxDisplayedLogs: 50, // Maximum number of logs to display
+        configs: LLM_CONFIGS,
+        dataConfig: [],
+    }
+    },   
+    created() {
+        // Check if consent is already given in local storage
+        const consentGiven = localStorage.getItem('consentGiven');
+        if (consentGiven === 'true') {
+            this.showConsentModal = false; // Don't show the modal if consent was given
+        }
+    },
+    mounted: function () {
+        this.adjustHeight({ target: this.$refs.textarea }); 
+        // this.startScan();
+        this.loadConfigs();
+
+    },
+    computed: {
+        selectedDS: function () {
+            return this.dataConfig.filter(p => p.selected).length;
+        },
+        displayedLogs() {
+            return this.logs.slice(-this.maxDisplayedLogs).reverse();
+        },
+        hasImageSpec() {
+            return has_image(this.modelSpec);
+        },
+        hasAudioSpec() {
+            return has_files(this.modelSpec);
+        },
+        hasFileSpec() {
+            return has_files(this.modelSpec) || has_image(this.modelSpec);
+        },
+        highlightedText() {
+            // First highlight <<VAR>> pattern
+            let text = this.modelSpec.replace(
+                /<<([^>]+)>>/g,
+                `<span class="px-2 py-0.5 rounded-full bg-dark-accent-yellow text-dark-bg font-medium">&lt;&lt;$1&gt;&gt;</span>`
+            );
+
+            // Then highlight $VARIABLE pattern
+            text = text.replace(
+                /(\$[A-Z_]+)/g,
+                `<span class="px-2 py-0.5 rounded-full bg-yellow-100 text-dark-bg font-medium">$1</span>`
+            );
+
+            // Finally wrap everything in gray text
+            return `<span class="text-gray-500">${text}</span>`;
+        },
+        highlightedText2() {
+            // First apply the highlighting for variables
+            const highlightedText = this.modelSpec.replace(
+                /<<([^>]+)>>/g,
+                `<span class="px-2 py-0.5 rounded-full bg-dark-accent-yellow text-dark-bg font-medium">&lt;&lt;$1&gt;&gt;</span>`
+            );
+
+            // Wrap the entire text in a span to make non-highlighted parts dim gray
+            return `<span class="text-gray-500">${highlightedText}</span>`;
+        }
+
+    },
+    methods: {
+        focusTextarea() {
+            this.isFocused = true;
+            self = this.$refs;
+            this.$nextTick(() => {
+                // Focus the textarea after rendering
+                this.$refs.textarea?.focus();
+                this.adjustHeight({ target: this.$refs.textarea });
+            });
+            document.addEventListener("mousedown", this.handleClickOutside);
+
+        },
+        handleOutsideClick(event) {
+            if (!this.$refs.container.contains(event.target)) {
+                this.isFocused = false;
+                document.removeEventListener("mousedown", this.handleClickOutside);
+            }
+        },
+        unfocusTextarea() {
+            this.isFocused = false;
+        },
+        acceptConsent() {
+            this.showConsentModal = false; // Close the modal
+            localStorage.setItem('consentGiven', 'true'); // Save consent to local storage
+        },
+
+        saveStateToLocalStorage() {
+            const state = {
+                modelSpec: this.modelSpec,
+                budget: this.budget,
+                dataConfig: this.dataConfig,
+                optimize: this.optimize,
+                enableChartDiagram: this.enableChartDiagram,
+                enableMultiStepAttack: this.enableMultiStepAttack,
+            };
+            localStorage.setItem('appState:v1', JSON.stringify(state));
+        },
+        loadStateFromLocalStorage() {
+            const savedState = localStorage.getItem('appState:v1');
+            console.log('Loading state from local storage:', savedState);
+            if (savedState) {
+                const state = JSON.parse(savedState);
+                this.modelSpec = state.modelSpec;
+                this.budget = state.budget;
+                this.dataConfig = state.dataConfig;
+                this.optimize = state.optimize;
+                this.enableChartDiagram = state.enableChartDiagram;
+                this.enableMultiStepAttack = state.enableMultiStepAttack;
+            }
+        },
+        resetState() {
+            localStorage.removeItem('appState:v1');
+            this.modelSpec = LLM_SPECS[0];
+            this.budget = 50;
+            this.dataConfig.forEach(config => config.selected = false);
+            this.optimize = false;
+            this.enableChartDiagram = true;
+            this.okMsg = '';
+            this.errorMsg = '';
+            this.integrationVerified = false;
+            this.showResetConfirmation = false;
+            this.enableMultiStepAttack = false;
+        },
+        confirmResetState() {
+            this.showResetConfirmation = true;
+        },
+        updateStatusDot(ok) {
+            if (ok) {
+                this.statusDotClass = 'bg-green-500'; // Green when expanded
+            } else if (!ok) {
+                this.statusDotClass = 'bg-orange-500'; // Orange if collapsed with content
+            } else {
+                this.statusDotClass = 'bg-gray-500'; // Gray if collapsed without content
+            }
+        },
+        toggleLLMSpec() {
+            this.showLLMSpec = !this.showLLMSpec;
+        },
+        // adjustHeight(event) {
+        //   console.log(event,"event")
+        //     const textarea = event.target;
+        //     event.target.style.height = 'auto';
+        //     event.target.style.height = event.target.scrollHeight + 'px';
+        // },
+        downloadFailures() {
+            window.open('/failures', '_blank');
+        },
+        hide() {
+            this.maskMode = !this.maskMode;
+        },
+        verifyIntegration: async function () {
+            let payload = {
+                spec: this.modelSpec,
+            };
+            const response = await fetch(`${URL}/verify`, {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify(payload),
+            });
+            console.log(response);
+            let txt = await response.text();
+            if (!response.ok) {
+                this.updateStatusDot(false);
+                this.errorMsg = 'Integration verification failed:' + txt;
+            } else {
+                this.errorMsg = '';
+                this.updateStatusDot(true);
+                this.okMsg = 'Integration verified';
+                this.integrationVerified = true;
+                // console.log('Integration verified', this.integrationVerified);
+                // this.$forceUpdate();
+
+            }
+            this.saveStateToLocalStorage();
+        },
+        loadConfigs: async function () {
+            const response = await fetch(`${URL}/v1/data-config`, {
+                method: 'GET',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+            });
+            console.log(response);
+            this.dataConfig = await response?.json();
+            this.loadStateFromLocalStorage();
+        },
+        selectConfig(index) {
+            this.selectedConfig = index;
+            this.modelSpec = LLM_SPECS[index];
+            this.adjustHeight({ target: this.$refs.textarea });
+            // this.adjustHeight({ target: document.getElementById('llm-spec') });
+            this.errorMsg = '';
+            this.okMsg = '';
+            this.integrationVerified = false;
+        },
+        toggleModules() {
+            this.showModules = !this.showModules;
+        },
+        toggleLogs() {
+            this.showLogs = !this.showLogs;
+        },
+        addLog(message, level = 'INFO') {
+            const timestamp = new Date().toISOString();
+            this.logs.push({ timestamp, message, level });
+        },
+        downloadLogs() {
+            const logText = this.logs.map(log => `${log.timestamp} [${log.level}] ${log.message}`).join('\n');
+            const blob = new Blob([logText], { type: 'text/plain' });
+            const url = URL.createObjectURL(blob);
+            const a = document.createElement('a');
+            a.href = url;
+            a.download = 'vulnerability_scan_logs.txt';
+            document.body.appendChild(a);
+            a.click();
+            document.body.removeChild(a);
+            URL.revokeObjectURL(url);
+        },
+        addPackage(index) {
+
+             const pkg = this.dataConfig[index];
+            pkg.selected = !pkg.selected;
+
+        },
+        getFailureRateScore(failureRate) {
+            return _getFailureRateScore(failureRate);
+        },
+        getFailureRateColor(failureRate) {
+            return _getFailureRateColor(failureRate);
+        },
+        toggleParams() {
+            this.showParams = !this.showParams;
+        },
+        adjustHeight(event) {
+            const element = event.target;
+            if (!element) {
+                return
+            }
+            // Reset height to ensure accurate measurement
+            element.style.height = 'auto';
+            // Adjust height based on scrollHeight
+            element.style.height = `${element.scrollHeight + 100}px`;
+        },
+        newEvent: function (event) {
+
+            if (event.status) {
+                this.okMsg = `${event.module}`;
+                return
+            }
+            console.log('New event');
+            //  { "module": "Module 49", "tokens": 480, "cost": 4.800000000000001, "progress": 9.8 }
+            let progress = event.progress;
+            progress = progress % 100;
+            this.progressWidth = `${progress}%`;
+            this.addLog(`${JSON.stringify(event)}`, 'INFO');
+            if (this.mainTable.length < 1) {
+                this.mainTable.push(event);
+                event.last = true;
+
+                return
+            }
+            let last = this.mainTable[this.mainTable.length - 1];
+            if (last.module === event.module) {
+                last.tokens = event.tokens;
+                last.cost = event.cost;
+                last.progress = event.progress;
+                last.failureRate = event.failureRate;
+            } else {
+                last.last = false;
+                this.mainTable.push(event);
+                event.last = true;
+                this.newRow()
+            }
+            this.okMsg = `New event: ${event.module}: ${event.progress}%`;
+
+        },
+        newRow: async function () {
+            if (!this.enableChartDiagram) {
+                return
+            }
+            console.log('New row');
+            let payload = {
+                table: this.mainTable,
+            };
+            const response = await fetch(`${URL}/plot.jpeg`, {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify(payload),
+            });
+            // Convert image response to a data URL for the <img> src
+            const blob = await response.blob();
+            const reader = new FileReader();
+            reader.readAsDataURL(blob);
+            reader.onloadend = () => {
+                this.reportImageUrl = reader.result;
+            };
+        },
+        selectAllPackages() {
+            const allSelected = this.dataConfig.every(pkg => pkg.selected);
+
+            // If all are selected, deselect all. Otherwise, select all.
+            this.dataConfig.forEach(pkg => {
+                pkg.selected = !allSelected;
+            });
+
+            this.updateSelectedDS();
+        },
+
+        deselectAllPackages() {
+            this.dataConfig.forEach(pkg => {
+                pkg.selected = false;
+            });
+            this.updateSelectedDS();
+        },
+
+        updateSelectedDS() {
+            this.selectedDS = this.dataConfig.filter(pkg => pkg.selected).length;
+        },
+        updateBudgetFromSlider(event) {
+            this.budget = parseInt(event.target.value);
+        },
+        updateBudgetFromInput(event) {
+            let value = parseInt(event.target.value);
+            if (isNaN(value) || value < 1) {
+                value = 1;
+            } else if (value > 100) {
+                value = 100;
+            }
+            this.budget = value;
+        },
+        stopScan: async function () {
+            this.scanRunning = false;
+            const response = await fetch(`${URL}/stop`, {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+            });
+        },
+        startScan: async function () {
+            this.showLLMSpec = false;
+            let payload = {
+                maxBudget: this.budget,
+                llmSpec: this.modelSpec,
+                datasets: this.dataConfig,
+                optimize: this.optimize,
+                enableMultiStepAttack: this.enableMultiStepAttack,
+            };
+            const response = await fetch(`${URL}/scan`, {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify(payload),
+            });
+            this.okMsg = 'Scan started';
+            this.mainTable = [];
+            this.scanRunning = true;
+            const reader = response.body.getReader();
+            let receivedLength = 0; // received that many bytes at the moment
+            let chunks = []; // array of received binary chunks (comprises the body)
+            while (true) {
+                const { done, value } = await reader.read();
+
+                if (done) {
+                    break;
+                }
+
+                chunks.push(value);
+                receivedLength += value.length;
+
+                const chunkAsString = new TextDecoder("utf-8").decode(value);
+                const chunkAsLines = chunkAsString.split('\n').filter(line => line.trim());
+
+                self = this;
+                chunkAsLines.forEach(line => {
+                    try {
+                        const result = JSON.parse(line);
+                        self.scanResults.push(result);
+                        self.newEvent(result);
+                    } catch (e) {
+                        console.error('Error parsing chunk:', e);
+                    }
+                });
+            }
+            this.saveStateToLocalStorage();
+
+        }
+    }
+}
+</script>

ui/src/components/PageContent.vue

@@ -0,0 +1,103 @@
+<template>
+   <div id="consent-modal" v-if="showConsentModal"
+    class="fixed inset-0 bg-black bg-opacity-75 flex justify-center items-center z-50">
+    <div
+        class="bg-dark-card text-dark-text p-8 rounded-xl shadow-2xl max-w-xl w-full">
+        <h2 class="text-2xl font-bold mb-6 text-center">AI Red Team Ethical
+            Use Agreement</h2>
+        <div class="space-y-6">
+            <p class="text-sm leading-relaxed">
+                This AI red team tool is designed for security research,
+                vulnerability assessment,
+                and responsible testing purposes. By accessing this tool, you
+                explicitly agree to
+                the following ethical guidelines:
+            </p>
+            <ul class="list-disc list-inside text-sm space-y-3">
+                <li>
+                    <strong>Consent and Authorization:</strong> You will only
+                    use
+                    this tool on systems
+                    for which you have explicit, documented permission from the
+                    system owners.
+                </li>
+                <li>
+                    <strong>Responsible Disclosure:</strong> Any vulnerabilities
+                    discovered must be
+                    reported responsibly to the appropriate parties,
+                    prioritizing
+                    system and user safety.
+                </li>
+                <li>
+                    <strong>No Malicious Intent:</strong> You will not use this
+                    tool
+                    to cause harm,
+                    disrupt services, or compromise the integrity of any system
+                    or
+                    data.
+                </li>
+                <li>
+                    <strong>Legal Compliance:</strong> All testing and research
+                    must
+                    comply with
+                    applicable local, national, and international laws and
+                    regulations.
+                </li>
+
+            </ul>
+
+            <p class="text-xs text-gray-400 italic">
+                Violation of these terms may result in immediate termination of
+                access and
+                potential legal consequences.
+            </p>
+        </div>
+        <div class="flex justify-center space-x-4 mt-8">
+            <button
+                @click="declineConsent"
+                class="bg-dark-accent-red text-white rounded-lg px-6 py-3 font-medium hover:bg-opacity-80 transition-colors">
+                Decline
+            </button>
+            <button
+                @click="acceptConsent"
+                class="bg-dark-accent-green text-dark-bg rounded-lg px-6 py-3 font-medium hover:bg-opacity-80 transition-colors">
+                I Agree and Understand
+            </button>
+        </div>
+    </div>
+    
+</div>
+
+
+</template>
+
+<script>
+export default {
+  name: 'PageContent',
+
+  data() {
+    return {
+      showConsentModal: true // Default to true
+    };
+  },
+
+  emits: ['accept', 'decline'], // Define the custom events
+
+  methods: {
+     acceptConsent() {
+            this.showConsentModal = false; // Close the modal
+            localStorage.setItem('consentGiven', 'true'); // Save consent to local storage
+        },
+    declineConsent() {
+            this.showConsentModal = false; // Close the modal
+            localStorage.setItem('consentGiven', 'false'); // Save decline to local storage
+            window.location.href = 'https://www.google.com'; // Redirect to Google
+        },
+  }
+};
+</script>
+
+
+<style >
+/* Styles for the consent modal */
+</style>

ui/src/components/PageFooter.vue

@@ -0,0 +1,64 @@
+<template>
+  <footer class="mt-16 pt-8 border-t border-gray-800">
+    <div class="max-w-6xl mx-auto px-4 sm:px-6 lg:px-8">
+      <div class="grid grid-cols-1 md:grid-cols-3 gap-8">
+        <div>
+          <h3 class="text-lg font-semibold text-dark-accent-green mb-4">
+            Home
+          </h3>
+          <p class="text-gray-400">Dedicated to LLM Security, 2025</p>
+        </div>
+
+        <div>
+          <h3 class="text-lg font-semibold text-dark-accent-green mb-4">
+            Connect
+          </h3>
+          <ul class="space-y-2">
+            <li>
+              <a
+                href="https://x.com"
+                target="_blank"
+                rel="noopener noreferrer"
+                class="text-gray-400 hover:text-dark-accent-green"
+                >X.com</a
+              >
+            </li>
+            <li>
+              <a
+                href="https://github.com/msoedov"
+                target="_blank"
+                rel="noopener noreferrer"
+                class="text-gray-400 hover:text-dark-accent-green"
+                >Github</a
+              >
+            </li>
+          </ul>
+        </div>
+
+        <div>
+          <h3 class="text-lg font-semibold text-dark-accent-green mb-4">
+            About
+          </h3>
+          <p class="text-gray-400">
+            This is the LLM Vulnerability Scanner. Easy to use—no coding needed,
+            just pure security testing.
+          </p>
+        </div>
+      </div>
+
+      <div class="mt-8 pt-8 border-t border-gray-800 text-center">
+        <p class="text-gray-400">Made with ❤️ by the Agentic Security Team</p>
+      </div>
+    </div>
+  </footer>
+</template>
+
+<script>
+export default {
+  name: "PageFooter", // Descriptive name
+};
+</script>
+
+<style scoped>
+/* Footer-specific styles here */
+</style>

ui/src/components/PageHeader.vue

@@ -0,0 +1,22 @@
+<template>
+  <div>hello</div>
+</template>
+
+<script>
+export default {
+  name: 'PageHeader', // Give a descriptive name
+  // No specific JavaScript logic needed for this simple header
+  // You can add props if you want to make the title dynamic:
+  props: {
+    title: {
+      type: String,
+      default: 'LLM Vulnerability Scanner' // Default title
+    }
+  }
+};
+</script>
+
+<style scoped>
+/* Any header-specific styles can go here */
+/* If you are using tailwind, you can include this as well*/
+</style>

ui/src/main.js

@@ -0,0 +1,11 @@
+import { createApp } from 'vue'
+import App from './App.vue' // Create App.vue (see next step)
+import '../public/base.js' // If you have this file, move it to src/assets
+import '../public/telemetry.js' // Move to src/assets
+import lucide from 'lucide' // Import lucide if you are using it
+const app = createApp(App)
+app.mount('#vue-app') // Change #vue-app to #app
+
+app.config.globalProperties.$lucide = lucide
+
+//lucide.createIcons(); // Create icons

ui/tailwind.config.js

@@ -0,0 +1,30 @@
+/** @type {import('tailwindcss').Config} */
+module.exports = {
+  content: ["./src/**/*.{vue,js,ts,jsx,tsx}"],
+  darkMode: 'class',
+  theme: {
+    extend: {
+      fontFamily: {
+        sans: ['Inter', 'sans-serif'],
+        technopollas: ['Technopollas', 'sans-serif'],
+      },
+      colors: {
+        dark: {
+          bg: '#121212',
+          card: '#1E1E1E',
+          text: '#FFFFFF',
+          accent: {
+            green: '#4CAF50',
+            red: '#F44336',
+            orange: '#FF9800',
+            yellow: '#FFEB3B',
+          },
+        },
+      },
+      borderRadius: {
+        'lg': '1rem',
+      },
+    }
+  },
+  plugins: [],
+}

ui/vue.config.js

@@ -0,0 +1,2 @@
+const { defineConfig } = require('@vue/cli-service')
+module.exports = defineConfig({ transpileDependencies: true, publicPath: '/' ,devServer: { allowedHosts: 'all', client: {webSocketURL: 'auto://0.0.0.0:0/ws'}}, })