AI-Infra-Guard
AI-Infra-Guard (A.I.G) is an AI red-teaming and security assessment platform that runs multiple scanners and evaluations, including OpenClaw security scanning, multi-agent workflow security scanning, MCP server/agent-skills scanning, AI infrastructure/component vulnerability scanning, and LLM jailbreak/prompt security evaluations. It exposes a web UI and a documented set of task-creation APIs (Swagger/docs) for running scans and retrieving results.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Security-relevant notes from README: explicitly states it currently lacks an authentication mechanism and should not be deployed on public networks. Mentions a bug fix to mask token fields in a GetTaskDetail API response to prevent credential leakage. No details provided on TLS enforcement, secret storage practices, rate limiting, or fine-grained access controls in the provided excerpt.
⚡ Reliability
Best When
You can run it in a trusted/internal environment (e.g., behind your network controls), and you want automated multi-component security scanning plus task-based APIs for integration into your internal security workflow.
Avoid When
When you cannot place it behind authentication/network controls, or when you need robust end-user security controls and strict compliance/data handling guarantees that are not clearly documented.
Use Cases
- • Scanning OpenClaw deployments for insecure configuration, skill risks, CVEs, and privacy leakage
- • Assessing security of agent workflows (e.g., Dify/Coze-style pipelines) against common attack classes
- • Scanning MCP servers and agent skills from source code or remote URLs for multiple vulnerability/risk categories
- • Inventorying AI infrastructure/framework components and matching known CVEs
- • Evaluating LLM/jailbreak robustness using curated attack datasets and comparing cross-model behavior
- • Running scheduled or on-demand security self-examinations for internal AI systems
Not For
- • Public internet deployment without compensating controls (the project states it lacks an authentication mechanism)
- • Applications requiring strong, standardized enterprise authn/authz out of the box
- • Environments that require guaranteed data residency/compliance guarantees not described in the provided docs
Interface
Authentication
README states the project currently lacks an authentication mechanism and should not be deployed on public networks. No auth methods, scopes, or OAuth are described in the provided content.
Pricing
Pro version requires an invitation code; pricing details are not provided in the given README excerpt.
Agent Metadata
Known Gotchas
- ⚠ README indicates no authentication mechanism; place behind internal network/WAF/reverse proxy with access controls
- ⚠ Task-based APIs may not be idempotent; repeated task creation could re-run expensive scans
- ⚠ Credential leakage concerns are noted (masking token fields in a specific API response), so agents should still treat scan outputs as sensitive
Alternatives
Full Evaluation Report
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Scores are editorial opinions as of 2026-03-29.