Project Moonshot
Project Moonshot: A beta, self-hosted toolkit for benchmark-driven LLM security testing. Ranked #19 of 29 in AI Security Testing Tools by our editors (7.3/10); pricing: Free plan; best for teams wanting benchmark-driven red teaming.
At a glance
- Editor score7.3 / 10
- PricingFree plan
- Best forTeams wanting benchmark-driven red teaming
- Free planYes
- Paid fromFree
- Prompt injection testsYes
- Founded2024
- Facts checked21 Sep 2026
Where it wins
- Combines manual and automated LLM red-teaming with attack modules.
- Supports custom datasets, benchmark tests, connectors, and endpoints.
- Offers Web UI, CLI, library APIs, Web APIs, and downloadable results.
Where it doesn't
- The project is documented as beta.
- It requires local installation and self-hosted deployment.
- Named integrations focus on four model providers and custom applications.
Our verdict on Project Moonshot
Project Moonshot is an open-source LLM evaluation toolkit for developers, compliance teams, and AI system owners. It combines benchmark testing with manual and automated red-teaming for LLMs and LLM applications. Testing spans capability, quality, and trust-and-safety categories, with support for prompt injection, jailbreak, data leakage, and unsafe output testing. Teams can work through the Web UI, interactive CLI, Python library, or Web APIs, while HTML reports and downloadable JSON results support review and sharing.
Its strongest differentiator is the combination of benchmark structure and adversarial testing. Moonshot includes benchmark cookbooks, recipes, datasets, metrics, and attack modules for adversarial prompt generation. Teams can also create custom datasets and custom benchmark tests, then connect custom LLM applications and endpoints. This makes it suitable for organizations that want repeatable evaluation alongside more exploratory red-teaming, rather than a tool focused only on one attack type or one model provider.
Moonshot is distributed as open source, with local installation and self-hosted deployment. It supports OpenAI, Anthropic, Together, Hugging Face, and custom LLM applications, giving teams several starting points for provider-connected testing. The project is documented as beta, so teams should weigh that status when selecting a tool for ongoing security programs. Project Moonshot fits teams that value configurable benchmarks, multiple interfaces, and control over deployment. Teams seeking a commercially priced service or a more mature, broadly integrated platform should consider alternatives.
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Project Moonshot pricing
Project Moonshot fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Prompt injection tests | Yes |
| Jailbreak tests | Yes |
| Data leakage tests | Yes |
| Unsafe output tests | Yes |
| Custom test cases | Yes |
| Deployment mode | Self_hosted |
| Deployment | Self-hosted |
| Platforms | Web, Windows, macOS |
| Support | Docs |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 5 integrations: OpenAI, Anthropic, Together, Hugging Face, Custom LLM applications |
| Pricing | Free plan |
| Website | aiverifyfoundation.sg |
| Facts checked | 21 Sep 2026 |
Project Moonshot integrations
Project Moonshot lists 5 integrations on its own site.
- OpenAI
- Anthropic
- Together
- Hugging Face
- Custom LLM applications
Alternatives to Project Moonshot
- PromptGuardBroad AI security testing with flexible deployment and a low-cost paid entry tier.9.3
- Akto Agentic Red TeamingBroad AI security testing for enterprise agent and API security teams.9.1
- MindgardA broad AI risk platform spanning discovery, testing, protection, and remediation.9.0
See all Project Moonshot alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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