Giskard vs ProofLayer
Giskard
giskard.aiProofLayer
proof-layer.comSide by side
| Figure | Giskard | ProofLayer |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | — |
| Web | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 2 |
| Spec score · AI Red Teaming Tools | 8.7 (#3) | 7.5 (#16) |
| What it does | Giskard tests AI agents for security vulnerabilities, quality failures and compliance risks before and after deployment. | ProofLayer scans AI code before deployment, red-teams agents continuously, and protects MCP traffic at runtime, turning findings into audit-ready evidence. |
Plans
Giskard
- FreeFree
- Open-sourceFree
- EnterprisePriced on request
- ProfessionalPriced on request
In their own words
Giskard
Giskard provides tools for assessing AI agents before production, with coverage for prompt injection, data disclosure, inappropriate content, hallucinations, contradictions, and omissions. Its Hub performs black-box testing of conversational text-to-text agents available through an API endpoint. An assessment produces a structured report with a deploy-or-fix verdict, ranked vulnerabilities, and functional scenarios; passing agents receive a Giskard Label. Giskard describes a remediation process in which its team qualifies findings, discusses severity, prioritizes issues, opens workflow tickets, and reruns tests to check fixes. Enterprise evaluation options include adversarial probes, domain-specific datasets, RAG quality metrics, customizable metrics, and human review interfaces. Deployment choices include on-premise, private cloud, and SaaS. Giskard lists EU or US data residency, access controls, audit trails, identity-provider integration, encryption, and a zero-training policy, alongside GDPR, SOC 2 Type II, and HIPAA compliance. The free plan includes a local open-source library, basic vulnerability scanning and RAG evaluation, community support, and best-effort maintenance.
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.