LLMMap vs Project Moonshot
LLMMap
github.comProject Moonshot
aiverifyfoundation.sgSide by side
| Figure | LLMMap | Project Moonshot |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 1 |
| Spec score · AI Security Testing Tools | 7.5 (#19) | 8.3 (#8) |
| Intended users | The project describes LLMMap as a security testing tool for authorized use and says to test only systems owned by the user or covered by explicit written authorization. | The maker describes Moonshot as a tool for AI developers, compliance teams, and AI system owners evaluating LLMs and LLM applications. |
| Purpose | LLMMap tests LLM-integrated applications for prompt injection by discovering HTTP injection points, generating targeted prompts, and checking findings for reliability. | Project Moonshot is an open-source toolkit for testing the safety and reliability of LLMs and LLM applications through benchmarking and red teaming. |
Plans
In their own words
Project Moonshot
Project Moonshot is an open-source toolkit for evaluating the safety and reliability of large language models and applications. It runs benchmark tests using open-source datasets and metrics, and generates adversarial prompts to probe possible vulnerabilities and misuse. Users can build custom evaluations with their own datasets, optional prompt templates, metrics, and grading scales. Results appear in interactive HTML reports and downloadable raw JSON. Moonshot provides a Web UI, interactive command-line interface, library APIs, and Web APIs, with configurable connections to model providers including OpenAI, Anthropic, Together, and Hugging Face. Users can also create connectors for other models or applications hosted on custom servers. The toolkit implements benchmarks recommended in IMDA’s Starter Kit for safety testing LLM-based applications. Moonshot is free beta software under Apache License 2.0. Installation uses pip and requires Python 3.11; the Web UI additionally requires Node.js 20.11.1 LTS or later, and test assets are needed to run tests. The installation guide recommends Chrome for the Web UI and notes possible installation difficulties on x86 Macs with moonshot-data dependencies.