airtasystems/genbounty-llm-hunter-community-free — explained in plain English
Analysis updated 2026-05-18
Run a structured, repeatable pipeline of adversarial prompt tests against an authorized bug bounty target.
Generate jailbreak, prompt injection, or multi-step attack test suites for an AI chatbot or agent.
Export findings as a structured JSON report for a bug bounty submission or pentest deliverable.
Run regression security testing against an LLM app before each release.
| airtasystems/genbounty-llm-hunter-community-free | 0xustaz/streamgate | a-bissell/unleash-lite | |
|---|---|---|---|
| Stars | 1 | 1 | 1 |
| Language | Python | Python | Python |
| Setup difficulty | moderate | hard | hard |
| Complexity | 3/5 | 4/5 | 4/5 |
| Audience | developer | developer | researcher |
Figures from each repo's GitHub metadata at analysis time.
Requires a Gemini API key and Playwright's Chromium browser, installed automatically on first run.
Genbounty LLM Hunter is a free, community edition toolkit for authorized security testing of chatbots, AI agents, and apps built on top of language models. It is aimed at bug bounty hunters and whitehat testers who need a repeatable process instead of manually trying prompts one at a time and taking screenshots. The README is explicit that it is meant for authorized testing only, on systems you have permission to assess. The tool walks through a pipeline with clear stages. First you connect to a target chatbot or API, either through browser automation or a direct API connection. Then it runs a reconnaissance step to build a baseline of what the target looks like. Next it generates a suite of adversarial test prompts using a chosen strategy, such as straightforward attempts, jailbreak style prompts, or multi step prompt sequences, aimed at things like prompt injection, jailbreaks, leaking the system prompt, or exposing sensitive data. It then runs those tests against the target and records the prompts and responses as evidence. An assessment step uses AI to judge how severe each finding is and explain its reasoning. Finally you can export a structured report as a JSON file, or submit it directly to the Genbounty platform if you have an account there. The community edition covers a baseline of features for free, while a separate paid premium tier unlocks more advanced attack strategies, deeper reconnaissance, file upload and multimodal testing, prompt obfuscation techniques, and larger scale automated runs. Setup requires Python 3.10 or newer and the Playwright browser automation library, which the included start script installs automatically on first run, along with a Gemini API key for the test generation and assessment steps. A small local test target app is included so you can try the tool against a sample chatbot before pointing it at a real authorized target. The full README is longer than what was shown.
A free toolkit for authorized whitehat testers to run a repeatable pipeline of AI security tests against chatbots and LLM apps, from generation to reporting.
Mainly Python. The stack also includes Python, Playwright, Gemini API.
No license information is provided in the README.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
double-check against the repo, no cap.