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AI-Driven Security Assessment

Autonomous Pentesting Agent

An agent that runs full security assessments end-to-end.
You define the scope. You review the findings.

Quick StartWhat It DoesInstallationUser GuideAgent Tools

License Autonomous Models Version GitHub Stars


AIDA turns any LLM into an autonomous pentester capable of assessing web applications, APIs, and infrastructure. The agent reasons, understands application logic, executes commands in an isolated container, and documents every finding with the commands used.


AIDA Dashboard


Real Results

Claude + AIDA isn't just talk. It produces results that end up in CVE databases.

ID Severity Project Description
CVE-2026-32034 MEDIUM openclaw/openclaw Insecure HTTP permits hijacking
GHSA-xfvv-ggvq-pchh HIGH appsmithorg/appsmith RCE via newline injection in env variable endpoint
GHSA-vvxf-f8q9-86gh MEDIUM appsmithorg/appsmith SSRF via SMTP test endpoint — internal port scanning

More under responsible disclosure — awaiting publication.


What It Does

AIDA was built to give your AI everything a pentester needs to work.

A fully equipped execution environment. A Docker container loaded with Linux pentesting tools — nmap, sqlmap, ffuf, nuclei, and anything else it needs. If a tool is missing, the agent installs it.

Custom exploitation via Python. The agent generates and executes Python scripts on the fly — custom payloads, encoding tricks, protocol quirks, or any logic that off-the-shelf tools can't handle.

Burp-level HTTP control. The agent sends and manipulates HTTP requests directly — headers, cookies, body, auth tokens. Stored credentials are auto-injected via placeholders. Same power as Burp Repeater, without the UI overhead.

A persistent notebook. The agent logs what it knows about the application, maps attack paths, records observations, flags interesting behaviors, and documents every confirmed vulnerability — commands used, raw output, full context. Stop an engagement and resume it days later for retest, deeper analysis, or handoff.

Where is the real pentester?

You review. The AI hands you findings with full context notes, commands, reproduction steps, and the reasoning that led there. You reproduce, triage, prioritize, and report.

Your expertise stays where it matters. The grunt work runs on its own.


Quick Start

Prerequisites: Docker Desktop + any AI client (Claude, Gemini, GPT...)

git clone https://github.com/Vasco0x4/AIDA.git
cd AIDA
./start.sh

Dashboard: http://localhost:31337

./start.sh --dev — hot reload for contributors ./start.sh --lan — share across your local network

Launch the Agent

# Auto-detects Claude or Kimi CLI
python3 aida.py --assessment "target-corp"

# Force a specific model
python3 aida.py --assessment "target-corp" --cli claude

# No confirmation prompts
python3 aida.py --assessment "target-corp" --yes

Define Your Scope

Load assessment 'target-corp' and start the pentest on https://example.com
Scope: all subdomains, authentication flows, API endpoints
Exclude: brute-force on /login

Full setup for all AI clients → INSTALLATION.md


Supported Models

AIDA is model-agnostic. Any LLM with tool-calling support works.

Client Setup
Claude Code python3 aida.py (automatic)
Kimi CLI python3 aida.py (automatic)
External API (OpenAI-compatible) python3 aida.py --base-url
Claude Desktop MCP config
ChatGPT Desktop MCP config
Gemini CLI MCP config

The smarter the model, the deeper the engagement. Swap models without changing anything else.


Agent Tools

Tool
execute() Run any command in the pentesting container
scan() nmap, gobuster, ffuf, nikto, dirb
subdomain_enum() Subdomain discovery
ssl_analysis() TLS/SSL audit
tech_detection() Technology fingerprinting
python_exec() Execute Python in the container
http_request() HTTP client with credential auto-substitution
add_card() Log a finding — CVSS 4.0 auto-scored
credentials_add() Store credentials, auto-injected via {{PLACEHOLDER}}

Built-in aida-pentest container (~2 GB, starts automatically). Plug in Exegol for 400+ tools — switchable anytime from the dashboard.

Full reference → MCP_TOOLS.md


What's New in v1.1.0

  • Authentication — JWT, admin/user roles, first-run setup wizard
  • PDF reports — one-click export per assessment
  • CVSS 4.0 — automatic scoring on every finding
  • Attack timeline — auto-generated per engagement
  • Notifications — Telegram, Slack, Email with optional PDF attachment
  • Assessment templates — start from predefined methodologies
  • aida-pentest container — lightweight built-in environment, no Exegol required
  • python_exec + http_request — advanced execution tools
  • Cross-assessment findings view — aggregate and filter findings across all engagements
  • Security hardening — Docker socket proxy, path traversal prevention, localhost-only DB

!! Run locally or on your LAN. Do not expose the dashboard to the public. !!


Documentation

INSTALLATION.md Full setup — all AI clients
USER_GUIDE.md Platform usage guide
MCP_TOOLS.md Agent tool reference
ARCHITECTURE.md Technical deep dive

Contributing

AIDA is actively developed.

Planned:

  • OWASP testing guidelines integration
  • Multi-agent mode — specialized sub-agents per phase
  • Active Directory / internal network module
  • Enhanced CLI capabilities

Issues and PRs welcome → GitHub Issues


License

AGPL v3 — free and open source.


Credits

  • Anthropic MCP — the tool-calling protocol powering agent actions
  • Exegol — supported as alternative container
  • The security community for the open-source tooling

Need help? vasco0x4 on Discord

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Turn any LLM into an autonomous pentester. You define the scope, the agent does the work, you review the findings.

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