Evaluación, observabilidad y seguridad

garak — LLM vulnerability scanning

NVIDIA/garak

the LLM vulnerability scanner

Abrir repositorio oficial ↗ Página de inicio del proyecto ↗
★ 8,8KEstrellas
⑂ 1,2KBifurcaciones
391Problemas abiertos
PythonIdioma
Apache-2.0Licencia
Q@project.QualityScorePuntuación editorial

Capturas de pantalla del proyecto

Captura de pantalla de garak — LLM vulnerability scanning Captura de pantalla de garak — LLM vulnerability scanning

Resumen

NVIDIA/garak is an open-source project in ToolAI's Evaluation and safety category. the LLM vulnerability scanner The page is intended to help technical readers decide whether the project is worth a closer review; it is not an endorsement. The Python implementation and the repository owner NVIDIA are recorded from the catalog metadata.

Características principales

  • Official repository maintained by NVIDIA; the repository description identifies it as llm vulnerability scanning.
  • Primary language recorded for this editorial entry: Python.
  • Repository statistics and links are shown as a dated metadata snapshot, so readers can re-check them before adoption.
  • The official README, releases and issue tracker remain the source of truth for installation and compatibility details.

Requisitos, instalación y guía rápida

Requirements depend on the current official documentation. Start with the repository's README and pin a reviewed release before production use.

git clone https://github.com/NVIDIA/garak
cd garak

Use the project's documented environment manager, model weights and optional accelerators. Do not copy commands from an unverified mirror; check the release notes and lock compatible dependencies first.

Uso

This page is an objective orientation for llm vulnerability scanning. Read the official quick-start example, run it in an isolated environment, and record the exact commit or release used. For an agent or model workflow, keep tool permissions narrow, validate external inputs, and measure latency and quality on a representative test set. The repository's README and examples should be consulted for API details that may change.

Compatibilidad de modelos y casos de uso

The repository metadata describes the project scope but does not guarantee compatibility with every model, provider, checkpoint or accelerator. Confirm supported model identifiers, tokenizer versions, hardware requirements and license terms in the official documentation before connecting it to an LLM, agent, MCP server or RAG pipeline.

Notas sobre la licencia y los riesgos

GitHub metadata reports the repository license as Apache-2.0. Review the repository LICENSE and any separate model, dataset, weight or third-party dependency terms before redistribution or commercial use. A missing or NOASSERTION license is not a grant of permission.

Editorial verification 2026-08-02: official repository URL, owner, description, license field and repository statistics were reviewed. License metadata: Apache-2.0. Re-check README, releases and dependency/model terms before production use.

Lanzamiento y mantenimiento

Snapshot: 8,576 stars, 1,119 forks and 369 open issues; repository creation is not stated and last pushed date is 2026-07-24 when supplied by the catalog. Check the official releases page for the current version rather than treating these numbers as a guarantee of maintenance or quality.