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Author SHA1 Message Date
dependabot[bot] de3972bc21 build(deps): bump h11 from 0.14.0 to 0.16.0
Bumps [h11](https://github.com/python-hyper/h11) from 0.14.0 to 0.16.0.
- [Commits](https://github.com/python-hyper/h11/compare/v0.14.0...v0.16.0)

---
updated-dependencies:
- dependency-name: h11
  dependency-version: 0.16.0
  dependency-type: indirect
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-05-02 10:31:29 +00:00
5 changed files with 58 additions and 81 deletions
+3 -1
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@@ -21,7 +21,9 @@
<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>
</p>
+36 -30
View File
@@ -245,47 +245,61 @@ def load_jailbreak_v28k() -> ProbeDataset:
return create_probe_dataset("JailbreakV-28K/JailBreakV-28k", [])
@cache_to_disk(1)
def file_dataset(file) -> list[str]:
prompts = []
try:
df = pd.read_csv(os.path.join("./datasets", file), encoding_errors="ignore")
if "prompt" in df.columns:
prompts = df["prompt"].tolist()
else:
logger.warning(f"File {file} lacks a suitable prompt column")
except Exception as e:
logger.error(f"Error reading {file}: {e}")
return prompts
@cache_to_disk()
def load_local_csv() -> ProbeDataset:
"""Load prompts from local CSV files."""
os.makedirs("./datasets", exist_ok=True)
csv_files = [f for f in os.listdir("./datasets") if f.endswith(".csv")]
csv_files = [f for f in os.listdir(".") if f.endswith(".csv")]
logger.info(f"Found {len(csv_files)} CSV files: {csv_files}")
prompts = []
for file in csv_files:
prompts.extend(file_dataset(file))
try:
df = pd.read_csv(file)
if "prompt" in df.columns:
prompts.extend(df["prompt"].tolist())
else:
logger.warning(f"File {file} lacks a suitable prompt column")
except Exception as e:
logger.error(f"Error reading {file}: {e}")
return create_probe_dataset("Local CSV", prompts, {"src": str(csv_files)})
@cache_to_disk(1)
def load_csv(file: str) -> ProbeDataset:
"""Load prompts from local CSV files."""
prompts = file_dataset(file)
prompts = []
try:
df = pd.read_csv(file)
prompts = df["prompt"].tolist()
if "prompt" in df.columns:
prompts.extend(df["prompt"].tolist())
else:
logger.warning(f"File {file} lacks a suitable prompt column")
except Exception as e:
logger.error(f"Error reading {file}: {e}")
return create_probe_dataset(f"fs://{file}", prompts, {"src": str(file)})
@cache_to_disk(1)
def load_local_csv_files() -> list[ProbeDataset]:
"""Load prompts from local CSV files and return a list of ProbeDataset objects."""
csv_files = [f for f in os.listdir("./datasets") if f.endswith(".csv")]
csv_files = [f for f in os.listdir(".") if f.endswith(".csv")]
logger.info(f"Found {len(csv_files)} CSV files: {csv_files}")
datasets = []
for file in csv_files:
datasets.append(create_probe_dataset(file, file_dataset(file), {"src": file}))
try:
df = pd.read_csv(file)
if "prompt" in df.columns:
prompts = df["prompt"].tolist()
datasets.append(create_probe_dataset(file, prompts, {"src": file}))
else:
logger.warning(f"File {file} lacks a suitable prompt column")
except Exception as e:
logger.error(f"Error reading {file}: {e}")
return datasets
@@ -322,20 +336,12 @@ class StenographyTransformer:
)
continue
# Convert async generator (if any) to a list
prompts = (
list(dataset.prompts) if hasattr(dataset.prompts, "__iter__") else []
)
size = len(prompts)
if size == 0:
continue
size = len(dataset.prompts)
sample_size = max(1, int(size * 0.25)) # At least 1 sample
for name, fn in self.TRANSFORMATIONS.items():
logger.info(f"Applying {name} to {dataset.dataset_name}")
sampled = random.sample(prompts, min(sample_size, size))
sampled = random.sample(dataset.prompts, min(sample_size, size))
try:
transformed = [
f"Follow the instructions in {name}: {fn(str(p))}"
+5 -36
View File
@@ -1,54 +1,23 @@
# Getting Started
Welcome to Agentic Security! This guide will help you orient yourself within the project and start using the tool quickly.
## Project Overview
Agentic Security is an open-source vulnerability scanner for Large Language Models (LLMs). It provides both a command line interface and a FastAPI server so you can probe models for weaknesses such as jailbreaks or refusal patterns. The tool supports multimodal attacks, multi-step scans and reinforcement-learning based probes.
## Repository Layout
```
agentic_security/
├── __main__.py - CLI entry point
├── app.py - FastAPI app assembly
├── lib.py - SecurityScanner and utilities
├── config.py - Configuration handling
├── core/ - app state and logging helpers
├── probe_actor/ - scanning logic and RL modules
├── probe_data/ - dataset registry and loaders
├── routes/ - API endpoints
└── ui/ - Web UI assets (Vue)
```
`tests/` contains unit tests, and `docs/` houses the project documentation.
Welcome to Agentic Security! This guide will help you get started with using the tool.
## Quick Start
1. Ensure you have completed the [installation](installation.md) steps.
2. Run the following command to start the application:
1. Run the following command to start the application:
```bash
agentic_security
```
The server will start on `http://localhost:8718`.
3. Explore available commands with:
```bash
agentic_security --help
```
1. Access the application at `http://localhost:8718`.
## Basic Usage
- To view available commands, run:
- To view available commands, use:
```bash
agentic_security --help
```
## Next Steps
- Review the [Quickstart Guide](quickstart.md) for a fast setup walkthrough.
- Check [http_spec.md](http_spec.md) to learn how LLM endpoints are described.
- Browse the `probe_actor` and `probe_data` modules to understand how scanning works and how datasets are loaded.
- Explore the [Configuration](configuration.md) section to customize your setup.
- Run the tests in `tests/` to verify your environment once dependencies are installed.
This guide should give you a solid foundation for exploring and extending Agentic Security. For more details, see the rest of the documentation.
Explore the [Configuration](configuration.md) section to customize your setup.
Generated
+13 -13
View File
@@ -1151,37 +1151,37 @@ tests = ["pytest (>=7.1.3,<8.4.0)", "pytest-cov", "testfixtures"]
[[package]]
name = "h11"
version = "0.14.0"
version = "0.16.0"
description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
optional = false
python-versions = ">=3.7"
python-versions = ">=3.8"
groups = ["main", "dev"]
files = [
{file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
{file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
{file = "h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86"},
{file = "h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1"},
]
[[package]]
name = "httpcore"
version = "1.0.5"
version = "1.0.9"
description = "A minimal low-level HTTP client."
optional = false
python-versions = ">=3.8"
groups = ["main", "dev"]
files = [
{file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"},
{file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"},
{file = "httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55"},
{file = "httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8"},
]
[package.dependencies]
certifi = "*"
h11 = ">=0.13,<0.15"
h11 = ">=0.16"
[package.extras]
asyncio = ["anyio (>=4.0,<5.0)"]
http2 = ["h2 (>=3,<5)"]
socks = ["socksio (==1.*)"]
trio = ["trio (>=0.22.0,<0.26.0)"]
trio = ["trio (>=0.22.0,<1.0)"]
[[package]]
name = "httpx"
@@ -3751,19 +3751,19 @@ rpds-py = ">=0.7.0"
[[package]]
name = "requests"
version = "2.32.4"
version = "2.32.3"
description = "Python HTTP for Humans."
optional = false
python-versions = ">=3.8"
groups = ["main", "dev"]
files = [
{file = "requests-2.32.4-py3-none-any.whl", hash = "sha256:27babd3cda2a6d50b30443204ee89830707d396671944c998b5975b031ac2b2c"},
{file = "requests-2.32.4.tar.gz", hash = "sha256:27d0316682c8a29834d3264820024b62a36942083d52caf2f14c0591336d3422"},
{file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"},
{file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"},
]
[package.dependencies]
certifi = ">=2017.4.17"
charset_normalizer = ">=2,<4"
charset-normalizer = ">=2,<4"
idna = ">=2.5,<4"
urllib3 = ">=1.21.1,<3"
+1 -1
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@@ -1,6 +1,6 @@
[tool.poetry]
name = "agentic_security"
version = "0.7.4"
version = "0.7.2"
description = "Agentic LLM vulnerability scanner"
authors = ["Alexander Miasoiedov <msoedov@gmail.com>"]
maintainers = ["Alexander Miasoiedov <msoedov@gmail.com>"]