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SPECIFICTION
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DeepTeam vs garak

DeepTeam

trydeepteam.com

garak

garak.ai

Side by side

FigureDeepTeamgarak
Price fromFreeFree
Free planYesYes
Free trial——
Open source——
Windows—Yes
macOS—Yes
Linux—Yes
APIYes—
Self-hostedYesYes
Plans published11
Spec score · AI Red Teaming Tools7.8 (#10)7.9 (#9)
Spec score · AI Security Testing Tools7.7 (#16)7.8 (#15)
PurposeDeepTeam is an open-source framework for red teaming LLM systems and finding risks and vulnerabilities.garak is an LLM vulnerability scanner that probes language models and systems using them for security weaknesses.

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DeepTeam

  • Open-source frameworkFree

DeepTeam pricing →

garak

  • FreeFree

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In their own words

DeepTeam

DeepTeam is an open-source Python framework for red teaming large language model systems. It offers more than 50 ready-to-use vulnerability checks covering bias, toxicity, personal-information leakage, prompt leakage, and security risks. Simulated attacks include jailbreaks, prompt injection, automated evasion, data extraction, and response manipulation. Vulnerability-specific LLM-as-a-Judge metrics return a binary score with reasoning. Supported reference frameworks include OWASP, NIST AI RMF, MITRE ATLAS, the EU AI Act, BeaverTails, and Aegis. Listed model providers include OpenAI, Claude, Gemini, Azure OpenAI, AWS Bedrock, Vertex AI, Mistral, LiteLLM, and Portkey. CI/CD listings include GitHub Actions, GitLab CI, Jenkins, CircleCI, Buildkite, and Azure Pipelines. Installation uses pip in a Python virtual environment, and attacks are dynamically simulated without a prepared dataset. Results can be saved locally or sent to Confident AI for centralized viewing and production red teaming through a UI. The framework is Apache 2.0 licensed and supports self-hosted or API use.

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garak

garak is a command-line scanner for probing language models and systems that use them for security weaknesses. Its checks cover issues such as hallucination, data leakage, prompt injection, misinformation, toxicity generation, and jailbreaks. Probes try to elicit failures, while detectors inspect responses for patterns such as unsafe content or a failure to refuse. A standard scan can run without supervision and produce a report, with scan settings available for customization. Integrations include OpenAI, Hugging Face, Cohere, Replicate, AWS Bedrock, LiteLLM, REST-accessible models, and custom Python integrations. Hugging Face models can run locally or be accessed through an inference API or private endpoint. Output includes screen results, a detailed report log, a hit log, and a debug log. garak assesses text output only. It is developed in Linux and OSX and can be installed with pip or from source; listed platforms include Linux, macOS, Windows, and self-hosted use. It is free, with a free plan and no free trial. Listed capabilities include custom metrics, LLM-as-a-judge, and safety evaluations.

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