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Autonomous AI Pentester — find vulnerabilities before hackers do

Project description

🥀 Briar — Autonomous AI Pentester

Find vulnerabilities before hackers do. Free. Open Source. No Docker.

PyPI Python License Stars

Briar is an autonomous AI pentester. It scans web applications, injects real payloads, validates exploits, and generates professional security reports — powered by 11 AI providers including a completely free local mode via Ollama.

pip install briar-pentest && briar setup && briar scan -u https://target.com --deep

What Briar Found — Real Example

Against a file server on port 666 (ransomware-like deployment):

# Vulnerability Severity CVSS
1 Path Traversal 🔴 Critical 9.1
2 IDOR — File Enumeration 🟠 High 7.5
3 Unauthenticated File Access 🔴 Critical 9.1
4 Arbitrary File Upload (RCE) 🔴 Critical 9.8
5 Directory Listing 🟠 High 6.5
6 HTTP Verb Tampering 🟡 Medium 5.0
7 Missing Security Headers 🟢 Low 3.1
8 SSRF via URL param 🟠 High 8.6
9 Reflected XSS 🟠 High 7.2
10 Sensitive File Exposure 🟡 Medium 5.3

Each finding includes: copy-paste curl PoC, CVSS score, tech-specific remediation (nginx/Apache/Flask/Express code).


Features

Category Details
🤖 11 AI Providers Ollama (free, local), OpenAI, Claude, DeepSeek, Groq, Mistral, xAI/Grok, Google/Gemini, OpenRouter, Together, Custom
🛡️ 12 Security Agents Recon, Injection, XSS, SSRF, Auth, AuthZ, CSRF, Upload, Traversal, RCE, API, Secrets
🎯 No Exploit, No Report Every High/Critical finding replayed and confirmed before reporting
🔌 Blackbox + Whitebox Works with just a URL. Add -r /path/to/source for code-aware analysis
📡 Port Scanning 24 common ports scanned during recon
📓 LLM-Wiki (Obsidian) Interlinked vault, frontmatter YAML, index, log, canvas mindmap — Karpathy pattern
📄 Reports Markdown, Word (.docx), Excel (.xlsx), HTML slides
📊 Charts Donut severity, heatmap severity×endpoint, bar charts (type + agent)
🌐 Dashboard Web UI on port 8233 (FastAPI) with live scan launcher
💾 Workspaces Resume interrupted scans, checkpoint after every agent
⚙️ YAML Config Authenticated scanning, login flows, custom rules (avoid/focus paths)
🐳 No Docker Required Native Python. pip install and go. Docker optional.

Quick Start

# Install
pip install briar-pentest

# Configure (pick Ollama for free local AI)
briar setup

# Quick scan
briar scan -u https://target.com --quick

# Deep scan with browser exploits
briar scan -u https://target.com --deep

# With config file (authenticated)
briar scan -c config.yaml

# Resume interrupted scan
briar scan --resume workspace-name

# Web dashboard
briar serve  # → http://localhost:8233

Config File (YAML)

target:
  url: http://localhost:3000
provider: deepseek
mode: deep

authentication:
  login_url: /rest/user/login
  method: json
  credentials:
    email: admin@test.com
    password: admin123

rules:
  avoid:
    - path: /logout
  focus:
    - path: /api
    - path: /rest

Commands

briar             Show banner + version
briar status      Show configured provider + API key
briar setup       Pick AI provider (interactive)
briar scan        Run pentest (-u URL, --quick, --deep, -c config.yaml)
briar serve       Start web dashboard (:8233)
briar workspaces  List saved workspaces
briar resume      Resume an interrupted scan

Install from Source

git clone https://github.com/Stiimy/briar
cd briar
pip install -e .
briar setup

License: AGPL-3.0 — Free. Forever.

"No exploit, no report."

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