mirror of
https://github.com/msoedov/agentic_security.git
synced 2026-06-24 06:09:55 +02:00
feat(Update app structure):
This commit is contained in:
Alexander Myasoedov
+24
-283
@@ -1,287 +1,28 @@
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import os
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import random
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from asyncio import Event, Queue
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from datetime import datetime
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from logging import config
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from pathlib import Path
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from fastapi import BackgroundTasks, FastAPI, HTTPException, Request, Response
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import FileResponse, StreamingResponse
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from loguru import logger
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from pydantic import BaseModel, Field
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from starlette.middleware.base import BaseHTTPMiddleware
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from .http_spec import LLMSpec
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from .probe_actor import fuzzer
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from .probe_actor.refusal import REFUSAL_MARKS
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from .probe_data import REGISTRY
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from .report_chart import plot_security_report
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# Create the FastAPI app instance
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app = FastAPI()
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origins = [
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"*",
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]
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# Configuration
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class Settings:
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MAX_BUDGET = 1000
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MAX_DATASETS = 10
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RATE_LIMIT = "100/minute"
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DISABLE_TELEMETRY = os.getenv("DISABLE_TELEMETRY", False)
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FEATURE_PROXY = False
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settings = Settings()
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# Middleware setup
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app.add_middleware(
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CORSMiddleware,
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allow_origins=origins,
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allow_credentials=True,
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allow_methods=["*"], # Allows all methods
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allow_headers=["*"], # Allows all headers
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from .core.app import create_app
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from .core.logging import setup_logging
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from .middleware.cors import setup_cors
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from .middleware.logging import LogNon200ResponsesMiddleware
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from .routes import (
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static_router,
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scan_router,
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probe_router,
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proxy_router,
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report_router,
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)
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tools_inbox = Queue()
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# Global stop event for cancelling scans
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stop_event = Event() # Added stop_event to cancel the scan
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# Create the FastAPI app
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app = create_app()
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@app.get("/")
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async def root():
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agentic_security_path = Path(__file__).parent
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return FileResponse(f"{agentic_security_path}/static/index.html")
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@app.get("/main.js")
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async def main_js():
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agentic_security_path = Path(__file__).parent
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return FileResponse(f"{agentic_security_path}/static/main.js")
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@app.get("/telemetry.js")
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async def telemetry_js():
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agentic_security_path = Path(__file__).parent
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if settings.DISABLE_TELEMETRY:
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return FileResponse(f"{agentic_security_path}/static/telemetry_disabled.js")
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return FileResponse(f"{agentic_security_path}/static/telemetry.js")
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@app.get("/favicon.ico")
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async def favicon():
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agentic_security_path = Path(__file__).parent
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return FileResponse(f"{agentic_security_path}/static/favicon.ico")
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class LLMInfo(BaseModel):
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spec: str
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@app.post("/verify")
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async def verify(info: LLMInfo):
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spec = LLMSpec.from_string(info.spec)
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r = await spec.probe("test")
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if r.status_code >= 400:
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raise HTTPException(status_code=r.status_code, detail=r.text)
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return dict(
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status_code=r.status_code,
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body=r.text,
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elapsed=r.elapsed.total_seconds(),
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timestamp=datetime.now().isoformat(),
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)
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class Scan(BaseModel):
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llmSpec: str
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maxBudget: int
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datasets: list[dict] = []
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optimize: bool = False
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class ScanResult(BaseModel):
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module: str
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tokens: int
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cost: float
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progress: float
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failureRate: float = 0.0
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def streaming_response_generator(scan_parameters: Scan):
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# The generator function for StreamingResponse
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request_factory = LLMSpec.from_string(scan_parameters.llmSpec)
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async def _gen():
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async for scan_result in fuzzer.perform_scan(
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request_factory=request_factory,
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max_budget=scan_parameters.maxBudget,
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datasets=scan_parameters.datasets,
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tools_inbox=tools_inbox,
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optimize=scan_parameters.optimize,
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stop_event=stop_event, # Pass the stop_event to the generator
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):
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yield scan_result + "\n" # Adding a newline for separation
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return _gen()
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@app.post("/scan")
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async def scan(scan_parameters: Scan, background_tasks: BackgroundTasks):
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# Initiates streaming of scan results
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return StreamingResponse(
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streaming_response_generator(scan_parameters), media_type="application/json"
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)
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class Probe(BaseModel):
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prompt: str
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@app.post("/v1/self-probe")
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def self_probe(probe: Probe):
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refuse = random.random() < 0.2
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message = random.choice(REFUSAL_MARKS) if refuse else "This is a test!"
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message = probe.prompt + " " + message
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return {
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"id": "chatcmpl-abc123",
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"object": "chat.completion",
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"created": 1677858242,
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"model": "gpt-3.5-turbo-0613",
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"usage": {"prompt_tokens": 13, "completion_tokens": 7, "total_tokens": 20},
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"choices": [
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{
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"message": {"role": "assistant", "content": message},
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"logprobs": None,
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"finish_reason": "stop",
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"index": 0,
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}
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],
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}
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@app.get("/v1/data-config")
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async def data_config():
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return [m for m in REGISTRY]
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@app.get("/failures")
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async def failures_csv():
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if not Path("failures.csv").exists():
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return {"error": "No failures found"}
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return FileResponse("failures.csv")
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class Table(BaseModel):
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table: list[dict]
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@app.post("/plot.jpeg", response_class=Response)
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async def get_plot(table: Table):
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buf = plot_security_report(table.table)
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return StreamingResponse(buf, media_type="image/jpeg")
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class Message(BaseModel):
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role: str
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content: str
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class CompletionRequest(BaseModel):
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"""Model for completion requests."""
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model: str
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messages: list[Message]
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temperature: float = Field(default=0.7, ge=0.0, le=2.0)
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top_p: float = Field(default=1.0, ge=0.0, le=1.0)
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n: int = Field(default=1, ge=1, le=10)
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stop: list[str] | None = None
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max_tokens: int = Field(default=100, ge=1, le=4096)
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presence_penalty: float = Field(default=0.0, ge=-2.0, le=2.0)
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frequency_penalty: float = Field(default=0.0, ge=-2.0, le=2.0)
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# OpenAI proxy endpoint
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@app.post("/proxy/chat/completions")
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async def proxy_completions(request: CompletionRequest):
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refuse = random.random() < 0.2
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message = random.choice(REFUSAL_MARKS) if refuse else "This is a test!"
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prompt_content = " ".join(
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[msg.content for msg in request.messages if msg.role == "user"]
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)
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message = prompt_content + " " + message
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ready = Event()
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ref = dict(message=message, reply="", ready=ready)
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tools_inbox.put_nowait(ref)
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if settings.FEATURE_PROXY:
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# Proxy to agent
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await ready.wait()
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reply = ref["reply"]
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return reply
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# Simulate a completion response
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return {
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"id": "chatcmpl-abc123",
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"object": "chat.completion",
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"created": 1677858242,
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"model": "gpt-3.5-turbo-0613",
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"usage": {"prompt_tokens": 13, "completion_tokens": 7, "total_tokens": 20},
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"choices": [
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{
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"message": {"role": "assistant", "content": message},
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"logprobs": None,
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"finish_reason": "stop",
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"index": 0,
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}
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],
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}
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config.dictConfig(
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{
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"version": 1,
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"disable_existing_loggers": True,
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"handlers": {
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"console": {
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"class": "logging.StreamHandler",
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},
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},
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"root": {
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"handlers": ["console"],
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"level": "INFO",
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},
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"loggers": {
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"uvicorn.access": {
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"level": "ERROR", # Set higher log level to suppress info logs globally
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"handlers": ["console"],
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"propagate": False,
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}
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},
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}
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)
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@app.post("/stop")
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async def stop_scan():
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stop_event.set() # Set the stop event to cancel the scan
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return {"status": "Scan stopped"}
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class LogNon200ResponsesMiddleware(BaseHTTPMiddleware):
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async def dispatch(self, request: Request, call_next):
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try:
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response = await call_next(request)
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except Exception as e:
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logger.exception("Yikes")
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raise e
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if response.status_code != 200:
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logger.error(
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f"{request.method} {request.url} - Status code: {response.status_code}"
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)
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return response
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# Add middleware to the application
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# Setup middleware
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setup_cors(app)
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app.add_middleware(LogNon200ResponsesMiddleware)
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# Setup logging
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setup_logging()
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# Register routers
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app.include_router(static_router)
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app.include_router(scan_router)
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app.include_router(probe_router)
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app.include_router(proxy_router)
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app.include_router(report_router)
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@@ -0,0 +1,21 @@
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from asyncio import Event, Queue
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from fastapi import FastAPI
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tools_inbox: Queue = Queue()
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stop_event: Event = Event()
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def create_app() -> FastAPI:
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"""Create and configure the FastAPI application."""
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app = FastAPI()
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return app
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def get_tools_inbox() -> Queue:
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"""Get the global tools inbox queue."""
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return tools_inbox
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def get_stop_event() -> Event:
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"""Get the global stop event."""
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return stop_event
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@@ -0,0 +1,26 @@
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from logging import config
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def setup_logging():
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config.dictConfig(
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{
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"version": 1,
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"disable_existing_loggers": True,
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"handlers": {
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"console": {
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"class": "logging.StreamHandler",
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},
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},
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"root": {
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"handlers": ["console"],
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"level": "INFO",
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},
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"loggers": {
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"uvicorn.access": {
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"level": "ERROR", # Set higher log level to suppress info logs globally
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"handlers": ["console"],
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"propagate": False,
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}
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},
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}
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)
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@@ -5,7 +5,8 @@ import colorama
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import tqdm.asyncio
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from tabulate import tabulate
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from agentic_security.app import Scan, streaming_response_generator
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from agentic_security.models.schemas import Scan
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from agentic_security.routes.scan import streaming_response_generator
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from agentic_security.probe_data import REGISTRY
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RESET = colorama.Style.RESET_ALL
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@@ -0,0 +1,14 @@
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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def setup_cors(app: FastAPI):
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origins = ["*"]
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app.add_middleware(
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CORSMiddleware,
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allow_origins=origins,
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allow_credentials=True,
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allow_methods=["*"], # Allows all methods
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allow_headers=["*"], # Allows all headers
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)
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@@ -0,0 +1,17 @@
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from fastapi import Request
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from starlette.middleware.base import BaseHTTPMiddleware
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from loguru import logger
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class LogNon200ResponsesMiddleware(BaseHTTPMiddleware):
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async def dispatch(self, request: Request, call_next):
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try:
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response = await call_next(request)
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except Exception as e:
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logger.exception("Yikes")
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raise e
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if response.status_code != 200:
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logger.error(
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f"{request.method} {request.url} - Status code: {response.status_code}"
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)
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return response
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@@ -0,0 +1,56 @@
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import os
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from pydantic import BaseModel, Field
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class Settings:
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MAX_BUDGET = 1000
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MAX_DATASETS = 10
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RATE_LIMIT = "100/minute"
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DISABLE_TELEMETRY = os.getenv("DISABLE_TELEMETRY", False)
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FEATURE_PROXY = False
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class LLMInfo(BaseModel):
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spec: str
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class Scan(BaseModel):
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llmSpec: str
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maxBudget: int
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datasets: list[dict] = []
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optimize: bool = False
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class ScanResult(BaseModel):
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module: str
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tokens: int
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cost: float
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progress: float
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failureRate: float = 0.0
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|
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class Probe(BaseModel):
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prompt: str
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|
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class Message(BaseModel):
|
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role: str
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content: str
|
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|
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|
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class CompletionRequest(BaseModel):
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"""Model for completion requests."""
|
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|
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model: str
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messages: list[Message]
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temperature: float = Field(default=0.7, ge=0.0, le=2.0)
|
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top_p: float = Field(default=1.0, ge=0.0, le=1.0)
|
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n: int = Field(default=1, ge=1, le=10)
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stop: list[str] | None = None
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max_tokens: int = Field(default=100, ge=1, le=4096)
|
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presence_penalty: float = Field(default=0.0, ge=-2.0, le=2.0)
|
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frequency_penalty: float = Field(default=0.0, ge=-2.0, le=2.0)
|
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|
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class Table(BaseModel):
|
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table: list[dict]
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@@ -0,0 +1,13 @@
|
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from .static import router as static_router
|
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from .scan import router as scan_router
|
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from .probe import router as probe_router
|
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from .proxy import router as proxy_router
|
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from .report import router as report_router
|
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|
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__all__ = [
|
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"static_router",
|
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"scan_router",
|
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"probe_router",
|
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"proxy_router",
|
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"report_router",
|
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]
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@@ -0,0 +1,34 @@
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import random
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from fastapi import APIRouter
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from ..models.schemas import Probe
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from ..probe_actor.refusal import REFUSAL_MARKS
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from ..probe_data import REGISTRY
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router = APIRouter()
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@router.post("/v1/self-probe")
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def self_probe(probe: Probe):
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refuse = random.random() < 0.2
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message = random.choice(REFUSAL_MARKS) if refuse else "This is a test!"
|
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message = probe.prompt + " " + message
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return {
|
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"id": "chatcmpl-abc123",
|
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"object": "chat.completion",
|
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"created": 1677858242,
|
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"model": "gpt-3.5-turbo-0613",
|
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"usage": {"prompt_tokens": 13, "completion_tokens": 7, "total_tokens": 20},
|
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"choices": [
|
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{
|
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"message": {"role": "assistant", "content": message},
|
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"logprobs": None,
|
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"finish_reason": "stop",
|
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"index": 0,
|
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}
|
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],
|
||||
}
|
||||
|
||||
|
||||
@router.get("/v1/data-config")
|
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async def data_config():
|
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return [m for m in REGISTRY]
|
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@@ -0,0 +1,45 @@
|
||||
import random
|
||||
from asyncio import Event
|
||||
from fastapi import APIRouter
|
||||
from ..models.schemas import CompletionRequest, Settings
|
||||
from ..probe_actor.refusal import REFUSAL_MARKS
|
||||
from ..core.app import get_tools_inbox
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
@router.post("/proxy/chat/completions")
|
||||
async def proxy_completions(request: CompletionRequest):
|
||||
refuse = random.random() < 0.2
|
||||
message = random.choice(REFUSAL_MARKS) if refuse else "This is a test!"
|
||||
prompt_content = " ".join(
|
||||
[msg.content for msg in request.messages if msg.role == "user"]
|
||||
)
|
||||
message = prompt_content + " " + message
|
||||
ready = Event()
|
||||
ref = dict(message=message, reply="", ready=ready)
|
||||
tools_inbox = get_tools_inbox()
|
||||
await tools_inbox.put(ref)
|
||||
|
||||
if Settings.FEATURE_PROXY:
|
||||
# Proxy to agent
|
||||
await ready.wait()
|
||||
reply = ref["reply"]
|
||||
return reply
|
||||
|
||||
# Simulate a completion response
|
||||
return {
|
||||
"id": "chatcmpl-abc123",
|
||||
"object": "chat.completion",
|
||||
"created": 1677858242,
|
||||
"model": "gpt-3.5-turbo-0613",
|
||||
"usage": {"prompt_tokens": 13, "completion_tokens": 7, "total_tokens": 20},
|
||||
"choices": [
|
||||
{
|
||||
"message": {"role": "assistant", "content": message},
|
||||
"logprobs": None,
|
||||
"finish_reason": "stop",
|
||||
"index": 0,
|
||||
}
|
||||
],
|
||||
}
|
||||
@@ -0,0 +1,20 @@
|
||||
from pathlib import Path
|
||||
from fastapi import APIRouter, Response
|
||||
from fastapi.responses import FileResponse, StreamingResponse
|
||||
from ..models.schemas import Table
|
||||
from ..report_chart import plot_security_report
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
@router.get("/failures")
|
||||
async def failures_csv():
|
||||
if not Path("failures.csv").exists():
|
||||
return {"error": "No failures found"}
|
||||
return FileResponse("failures.csv")
|
||||
|
||||
|
||||
@router.post("/plot.jpeg", response_class=Response)
|
||||
async def get_plot(table: Table):
|
||||
buf = plot_security_report(table.table)
|
||||
return StreamingResponse(buf, media_type="image/jpeg")
|
||||
@@ -0,0 +1,53 @@
|
||||
from datetime import datetime
|
||||
from fastapi import APIRouter, BackgroundTasks, HTTPException
|
||||
from fastapi.responses import StreamingResponse
|
||||
from ..models.schemas import LLMInfo, Scan
|
||||
from ..http_spec import LLMSpec
|
||||
from ..probe_actor import fuzzer
|
||||
from ..core.app import get_tools_inbox, get_stop_event
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
@router.post("/verify")
|
||||
async def verify(info: LLMInfo):
|
||||
spec = LLMSpec.from_string(info.spec)
|
||||
r = await spec.probe("test")
|
||||
if r.status_code >= 400:
|
||||
raise HTTPException(status_code=r.status_code, detail=r.text)
|
||||
return dict(
|
||||
status_code=r.status_code,
|
||||
body=r.text,
|
||||
elapsed=r.elapsed.total_seconds(),
|
||||
timestamp=datetime.now().isoformat(),
|
||||
)
|
||||
|
||||
|
||||
def streaming_response_generator(scan_parameters: Scan):
|
||||
request_factory = LLMSpec.from_string(scan_parameters.llmSpec)
|
||||
|
||||
async def _gen():
|
||||
async for scan_result in fuzzer.perform_scan(
|
||||
request_factory=request_factory,
|
||||
max_budget=scan_parameters.maxBudget,
|
||||
datasets=scan_parameters.datasets,
|
||||
tools_inbox=get_tools_inbox(),
|
||||
optimize=scan_parameters.optimize,
|
||||
stop_event=get_stop_event(),
|
||||
):
|
||||
yield scan_result + "\n"
|
||||
|
||||
return _gen()
|
||||
|
||||
|
||||
@router.post("/scan")
|
||||
async def scan(scan_parameters: Scan, background_tasks: BackgroundTasks):
|
||||
return StreamingResponse(
|
||||
streaming_response_generator(scan_parameters), media_type="application/json"
|
||||
)
|
||||
|
||||
|
||||
@router.post("/stop")
|
||||
async def stop_scan():
|
||||
get_stop_event().set()
|
||||
return {"status": "Scan stopped"}
|
||||
@@ -0,0 +1,32 @@
|
||||
from pathlib import Path
|
||||
from fastapi import APIRouter
|
||||
from fastapi.responses import FileResponse
|
||||
from ..models.schemas import Settings
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
@router.get("/")
|
||||
async def root():
|
||||
agentic_security_path = Path(__file__).parent.parent
|
||||
return FileResponse(f"{agentic_security_path}/static/index.html")
|
||||
|
||||
|
||||
@router.get("/main.js")
|
||||
async def main_js():
|
||||
agentic_security_path = Path(__file__).parent.parent
|
||||
return FileResponse(f"{agentic_security_path}/static/main.js")
|
||||
|
||||
|
||||
@router.get("/telemetry.js")
|
||||
async def telemetry_js():
|
||||
agentic_security_path = Path(__file__).parent.parent
|
||||
if Settings.DISABLE_TELEMETRY:
|
||||
return FileResponse(f"{agentic_security_path}/static/telemetry_disabled.js")
|
||||
return FileResponse(f"{agentic_security_path}/static/telemetry.js")
|
||||
|
||||
|
||||
@router.get("/favicon.ico")
|
||||
async def favicon():
|
||||
agentic_security_path = Path(__file__).parent.parent
|
||||
return FileResponse(f"{agentic_security_path}/static/favicon.ico")
|
||||
+1
-1
@@ -1,6 +1,6 @@
|
||||
[tool.poetry]
|
||||
name = "agentic_security"
|
||||
version = "0.2.6"
|
||||
version = "0.3.0"
|
||||
description = "Agentic LLM vulnerability scanner"
|
||||
authors = ["Alexander Miasoiedov <msoedov@gmail.com>"]
|
||||
maintainers = ["Alexander Miasoiedov <msoedov@gmail.com>"]
|
||||
|
||||
Reference in New Issue
Block a user