Akto Agentic Red Teaming vs Project Moonshot
Akto Agentic Red Teaming
akto.ioProject Moonshot
aiverifyfoundation.sgSide by side
| Figure | Akto Agentic Red Teaming | Project Moonshot |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · AI Security Testing Tools | 8.2 (#9) | 8.3 (#8) |
| Custom tests | Akto says users can customize prebuilt probes to fit their agentic environment. | Users can build benchmark tests using custom datasets, optional prompt templates, evaluation metrics, and grading scales. |
| Integrations | Akto's connector page lists 200+ connectors across agent builders, models, AI gateways, browser extensions, IDE and desktop assistants, cloud services, and MCP connectors. | Users can configure connections to their LLMs and create custom connector endpoints through the Web UI or CLI guides. |
| Intended users | Akto describes its AI security platform as built for enterprise teams and modern AppSec teams. | The maker describes Moonshot as a tool for AI developers, compliance teams, and AI system owners evaluating LLMs and LLM applications. |
| Purpose | Agentic Red Teaming adversarially tests AI agents, copilots, RAG systems, and AI-powered applications for vulnerabilities. | Project Moonshot is an open-source toolkit for testing the safety and reliability of LLMs and LLM applications through benchmarking and red teaming. |
| Support | Akto documentation directs users to [email protected] or in-app Intercom for help and guidance. | The Moonshot FAQ directs users who need more help to raise an issue on GitHub. |
Plans
In their own words
Akto Agentic Red Teaming
Akto Agentic Red Teaming has no write-up on Specifiction yet; its figures are above.
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.