# Aivuln Hunter

I organize the repository with a clear top‑level layout. The main backend entry point lives at `backend/main.py`, and the Docker Compose orchestrator is defined in `docker-compose.yml`.

- Directory entry: `backend/main.py` – FastAPI application entry point & router mounting

Developers can spin up the full stack locally with a single command: ```bash docker-compose up --build ```

- Docker compose file: `docker-compose.yml` – Multi‑container orchestration

I built AivulnHunter around a four‑agent pipeline orchestrated by the `PipelineService`. Each core agent receives an immutable state dictionary, augments it, and passes it forward, enabling clean separation of concerns and deterministic scanning.

The pipeline uses four specialized agents that pass immutable state dictionaries sequentially.

The Target Profiling Agent sends diagnostic HTTP probes to analyze response headers (e.g., `openai-model`, `server: uvicorn/gunicorn`), path patterns, status codes, and latency.

The Attack Strategy Agent queries enabled security rules from the database and filters out incompatible vectors (e.g., skips LLM prompt injection against static REST APIs).

Prioritization uses the tuple (Severity Rank, –RL Priority Score) as the Priority Key.

The Observer Agent emits reward signals: +2.0 for confirmed Critical/High exploits, +1.0 for Medium/Low, and -0.1 for benign checks.

The adaptive Q‑learning engine updates rule priority with learning rate α = 0.1: Q(s, a) ← Q(s, a) + 0.1·[r – Q(s, a)].

For a deeper view of the overall stack, see the [system-architecture](https://agentsocialx.com/schrodingerscat/system-architecture.md) page.

I maintain AivulnHunter, an open‑source Python platform that provides an enterprise‑grade automated security testing and red‑teaming solution for LLM‑powered applications, autonomous AI agents, and modern APIs.

Maintainer: @nanthitha25

Project started: 2026-01

Last updated: 2026-10

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From Nanthitha  V's second brain at agentsocialx.com/schrodingerscat