LibreAI / Agents IA / pentagi
// agents · vxcontrol/pentagi

pentagi

pentagi est un projet de agents IA open source, créé par vxcontrol (vxcontrol/pentagi sur GitHub). Il compte 25 342 étoiles sur GitHub et 3 253 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 5 octobre 2026.

Autonomous AI agents for penetration testing — self-hosted, multi-agent, with a full web UI

★ 25,3 k étoiles⑂ 3,3 k forksMITmis à jour oct. 2026
▦ visuel — le README de ce projet ne contient aucune capture intégrable,
voici donc un emplacement réservé. Le guide ci-dessous est complet malgré tout.
// détails du projet

Détails du projet

Étoiles GitHub
25 342
Forks
3 253
Licence
MIT
Dernière mise à jour sur GitHub
5 octobre 2026
Catégorie
Agents IA
Type de fiche
Guide d'installation complet
Site officiel
Official site
// fonctionnement

Comment ça marche

  1. Clarify your goal

    Decide what you want to achieve with pentagi and check the README on GitHub for requirements before installing.

  2. Get the code

    Clone the repository from GitHub (or take the packaged install route in step 3 if the README offers one).

  3. Install and configure

    Follow the project's documented install commands — the Run section below lists the exact ones — and add any required API keys or models.

  4. Run your first task

    Work through the README's quickstart example end to end, then adapt it to your own project or data.

// fonctionnalités

Pourquoi on l'adore

Autonomous multi-agent testing

Specialized agents plan, execute and reflect on penetration-testing tasks end to end.

Intelligent task planning

Task decomposition and planning features (some marked Beta in the docs) structure long engagements.

Rich tooling environment

Agents run security tools inside the provided Docker environment rather than on your host.

Execution monitoring

A monitoring view (Beta) follows agent actions as a test unfolds.

Optional observability and memory

Compose overlays add Langfuse tracing and a Graphiti/Neo4j knowledge graph for long-term memory.

Self-hosted by design

Runs on your infrastructure with your own model keys — OpenAI, Anthropic and open models are configurable.

Advertisement
// lancez-le

Lancez-le vous-même

  1. Clone the repository

    Get the PentAGI source and compose files.

    git clone https://github.com/vxcontrol/pentagi.git
    cd pentagi
  2. Run the installer

    The README recommends the official installer (download, extract, run interactively) or a manual Docker Compose setup; add your user to the docker group as directed.

    # download and run the PentAGI installer per the README 'Quick Start', then:
    docker compose up -d
  3. Configure models and start a task

    Add your LLM provider keys in the UI, define an authorized target scope, and launch a supervised test.

    # configure provider keys in the PentAGI web UI after docker compose up -d
// cas d'usage

Ce que vous pouvez créer

Advertisement
// faq

Questions fréquentes

Who maintains pentagi?

pentagi is maintained by the vxcontrol organization/account on GitHub, together with open-source contributors, in the public repository vxcontrol/pentagi.

Is pentagi free to use?

Yes — the code is open source under the MIT license. You can use, modify and redistribute it under that license's terms.

Does pentagi need a paid API key?

PentAGI is free and MIT-licensed, but the agents need LLM access — your own OpenAI/Anthropic keys or local models — and you must only use it on systems you are authorized to test.

How does pentagi compare to manual pentest toolkits (Kali + scripts)?

Manual tooling gives total control; PentAGI adds autonomous planning and execution on top of similar tools, which demands closer supervision and clear authorization.

How do I get started with pentagi?

Clone the repository from GitHub, follow the install commands in the Run section (taken from the project's README), and complete the documented quickstart example before adapting it to your own use case.

// continuez l'exploration

Outils similaires

Agents IA

open-multi-agent

Open Multi Agent — a self-hosted TypeScript agent runtime with durable approvals and verifiable run records.

★ 7,0 k étoilesMIT
Voir le guide →
Agents IA

Rakazo

Rakazo — an open-source, self-hosted AI agent for persistent teammates: bring your own model and computer, run it on web, desktop, iPhone and Android

★ 4,1 k étoilesApache-2.0
Voir le guide →
Agents IA

CoreCoder

Self-hosted ai agents: minimal ai coding agent (~1,000 lines of python) inspir.

★ 1,8 k étoilesMIT
Voir le guide →
Agents IA

AutoGPT

The open-source platform for building and running autonomous AI agents, hosted or self-hosted

★ 187,5 k étoilesNOASSERTION
Voir le guide →
Agents IA

nanobot

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat…

★ 48,8 k étoilesMIT
Voir le guide →
Agents IA

redamon

Self-hosted AI pentesting agent that finds flaws and opens PRs to fix them.

★ 2,9 k étoilesMIT
Voir le guide →
// alternatives

Alternatives en Agents IA

Les autres projets de la catégorie Agents IA avec le plus d'étoiles du catalogue LibreAI — la sélection réaliste d'alternatives si pentagi ne vous convient pas.

// plus en agents

Plus en Agents IA

Projets de la catégorie Agents IA proches dans le catalogue, les plus proches en étoiles de pentagi — continuez à explorer de part et d'autre.

Obtenir pentagi

Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.