Back to directory

garak

An LLM vulnerability scanner that probes a model for hallucination, data leakage, prompt injection, misinformation, toxicity and jailbreaks, in the spirit of nmap or Metasploit but for language models.

garak

garak (Generative AI Red-teaming & Assessment Kit) is a vulnerability scanner for large language models. It probes a model for hallucination, data leakage, prompt injection, misinformation, toxicity generation, jailbreaks and other weaknesses, combining static, dynamic and adaptive probes, in a role its own documentation compares to nmap or the Metasploit Framework for LLMs.

It is a free, command-line tool that supports Hugging Face Hub models, Replicate, the OpenAI chat and completion APIs, AWS Bedrock, LiteLLM, GGUF models through llama.cpp, and most other model endpoints reachable over REST. A target model family and specific model are chosen through command-line options, and a full list of available probes can be listed from the tool itself.

It is written in Python and released under the Apache-2.0 license.

More in AI evals

See all 269
  • Provenance gate

    github.com

    A deterministic authorization gateway that sits between an AI agent and its tools, tracing where each parameter of a side-effect call came from, and blocking the call or asking a human when the source does not check out.

  • JevBench

    benchmarkheaven.com

    A reproducible benchmark from Benchmark Heaven that ranks Jev-class typed decision models on intelligence, calibration, speed, and cost, with a published harness, scoring rules, and results.

  • A co-evolutionary adversarial red-teaming tool for AI agents that uses quality-diversity evolutionary search to autonomously breed edge-case scenarios, testing whether an agent with tool access can be made to hallucinate, deadlock or leak funds.