LibreAI / AI Agents / open-kritt
// agents · Kritt-ai/open-kritt

open-kritt

Self-hosted AI vulnerability research: agents find, validate, deduplicate, and rank real security issues.

★ 2.2k stars⑂ 383 forksAGPL-3.0updated 2026-10
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

open-kritt is an open-source ai agents project by Kritt-ai (Kritt-ai/open-kritt on GitHub). It has 2,236 GitHub stars and 383 forks, is released under the AGPL-3.0 license, and was last updated on GitHub on 5 October 2026.

GitHub stars
2,236
Forks
383
License
AGPL-3.0
Last updated on GitHub
5 October 2026
Category
AI Agents
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Clarify your goal

    Decide which codebase you want researched and how findings should be validated before they reach your team.

  2. Get the project

    Clone the repository and follow the getting-started guide in the project documentation for the current self-hosted setup.

  3. Install and configure

    Configure the deployment with the model access and validation settings your environment requires.

  4. Run your first task

    Point an agent run at your code, then review the deduplicated, ranked findings it produces.

// features

Why people love it

Agent-orchestrated vulnerability research

Multiple focused agents analyse code for security issues rather than relying on a single pattern-matching pass.

Finding validation

Candidate issues are validated with configurable checks, reducing the noise of unverified AI-generated reports.

Deduplication and ranking

Results are merged and ranked so reviewers see unique, prioritised findings instead of repeated alerts.

Enrichment of findings

Findings can be enriched with additional context to support triage and remediation.

Self-hosted deployment

The platform runs on your own infrastructure, keeping proprietary source code inside your environment.

Built for research workflows

Positioned for vulnerability research and bug bounty style work, with a companion research paper and documentation site.

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// run it

Run it yourself

  1. Clone the repository

    Get the source and its documentation locally.

    git clone https://github.com/Kritt-ai/open-kritt.git
    cd open-kritt
  2. Follow the documented setup

    The README directs users to the official getting-started guide for the current install steps.

    # see README for the exact command - getting started: https://docs.kritt.ai
  3. Run your first research task

    Configure the deployment per the docs, then start an agent run against a target repository. # see README for the exact command

    # see docs.kritt.ai getting started for run commands
// use cases

What you can build

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// faq

Questions, answered

Who maintains it?

It is maintained by Kritt-ai, the team behind kritt.ai.

Is it free to use?

The code is AGPL-3.0 licensed, so it is free to use and self-host, with copyleft obligations if you modify and distribute or serve it. Model usage for the agents is billed by your provider.

Does it need a paid API key?

Yes in practice: the agents that perform the research run on LLM access that you configure and pay for.

How does it compare to a well-known alternative?

Traditional SAST scanners match known patterns deterministically; Open Kritt orchestrates reasoning agents that search for and validate issues, which can surface logic flaws pattern tools miss, at the cost of model spend.

How do I get started?

Clone the repository and follow the getting-started guide at docs.kritt.ai, which the README designates as the canonical setup path.

// keep exploring

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// alternatives

Alternatives in AI Agents

The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if open-kritt is not the right fit.

Get open-kritt

Free and open — grab the source, star the repo, and start creating.