garak vs Mindgard
garak
garak.ai
Mindgard
mindgard.aiSide by side
| Figure | garak | Mindgard |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | — | Yes |
| Self-hosted | Yes | — |
| Plans published | 1 | 0 |
| Spec score · AI Red Teaming Tools | 7.9 (#9) | 7.5 (#15) |
| Spec score · AI Security Testing Tools | 7.8 (#15) | 7.4 (#20) |
| Deployment | garak is a command-line tool developed in Linux and OSX and can be installed with pip or from source. | Mindgard says it can be operational in minutes through APIs, CI/CD pipelines, Burp Suite, or a single-click workflow. |
| Integrations | The project lists support for OpenAI, Hugging Face, Cohere, Replicate, AWS Bedrock, LiteLLM, REST-accessible models, and custom Python integrations. | Mindgard says it supports APIs, CI/CD, and Burp Suite, including a Burp Suite extension. |
| Purpose | garak is an LLM vulnerability scanner that probes language models and systems using them for security weaknesses. | Mindgard’s AI security platform finds, validates, and helps fix high-impact vulnerabilities in AI systems and agents. |
| Support | The project points users to its user guide, reference documentation, Discord, GitHub issues, and an NVIDIA email address for support. | The site invites visitors to contact its team and book a demo. |
Plans
In their own words
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.