Darkhunt AI Security vs ProofLayer
Darkhunt AI Security
darkhunt.aiProofLayer
proof-layer.comSide by side
| Figure | Darkhunt AI Security | ProofLayer |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 2 |
| Spec score · AI Red Teaming Tools | 7.9 (#8) | 7.5 (#16) |
| Red teaming | Automated red teaming tests agents with their real tools, permissions, and data access for attacks including prompt injection, jailbreaks, and data exfiltration. | Autonomous attack campaigns test LLM applications, multi-agent systems, RAG pipelines, and MCP servers; verified breaches include replay traces and audit-ready evidence. |
| Runtime protection | Findings can become inline runtime policies, and an MCP gateway proxies requests and responses. | MCP runtime security tests for tool poisoning, prompt injection, excessive permissions, unsafe tool execution, data exfiltration, and supply-chain risk. |
Plans
Darkhunt AI Security
- FreeFree
- Custom AnnualPrice not published
- Pay as you goPriced on request
In their own words
Darkhunt AI Security
Darkhunt AI Security continuously tests, monitors, and protects AI agents in production. It discovers models, agents, and MCP servers across SaaS, cloud, endpoints, and code, including sanctioned and shadow AI. Its observability tools log and replay activity, making agent prompts, responses, and tool calls searchable. Automated red teaming tests agents with their actual tools, permissions, and data access for prompt injection, jailbreaks, and data exfiltration. The platform also checks decision integrity, including manipulated figures, suppressed alerts, RAG poisoning, and confident hallucinations, and traces answers to source data points. Findings can become inline runtime policies, while an MCP gateway proxies requests and responses. Listed integrations include OpenAI, Anthropic, Azure, AWS Bedrock, Gemini, and self-hosted systems. Deployment options are cloud, hybrid, and self-hosted. Findings or controls can map to several named frameworks, including the EU AI Act and NIST AI RMF. The free plan costs nothing and includes full platform access, a free credit allotment, and community support. Paid options have unlisted prices.
ProofLayer
ProofLayer scans AI code before deployment, red-teams agents continuously, and protects MCP traffic at runtime, turning findings into audit-ready evidence. Its open-source scanner checks coding agents, MCP servers, prompts, skills, code, and packages from a developer workstation, CI, or as an MCP tool. It flags risks including prompt injection, hallucinated packages, exposed secrets, unsafe MCP tools, and vulnerable generated code. Autonomous attack campaigns test LLM applications, multi-agent systems, RAG pipelines, and MCP servers for issues such as jailbreaks, data exfiltration, tool abuse, RAG poisoning, and memory injection. Verified breaches include replay traces and audit-ready evidence. Runtime protections test MCP traffic for tool poisoning, excessive permissions, unsafe tool execution, and supply-chain risk. Listed targets and integrations include OpenAI, Anthropic, Azure OpenAI, self-hosted Qwen, Llama, and Mistral, plus LangGraph, LangChain, ChromaDB, and MCP servers. ProofLayer says it generates evidence for SOC 2, NIST AI RMF, the EU AI Act, and ISO/IEC 42001. The free Community plan includes a CLI and MCP scanner, 1,700+ detection rules, prompt injection probes, MCP tool testing, a community rule library, and an MIT license.