GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
133views this month
Decision brief
AI-Infra-Guard is designed for organizations looking to secure their AI infrastructures comprehensively through various scanning and evaluation tools.
Good fit when
- If you need advanced LLM jailbreak evaluation capabilities specific to the vulnerabilities identified by Tencent's research, consider using AI-Infra-Guard.
- Suitable when your organization requires security assessments that go beyond just code but also cover skill assessments for AI-driven tasks or environments.
Avoid when
- Avoid if you are looking exclusively for a tool that focuses solely on the runtime behavior of LLMs without broader infrastructural scanning capabilities.
- Not recommended when your primary focus is on network-level security rather than comprehensive AI infrastructure security assessments and evaluations.
Observed Jul 17, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 20, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install AI-Infra-GuardSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Tencent/AI-Infra-Guard is a comprehensive security solution for AI ecosystems providing tools for agent scanning, skill assessment, and LLM jailbreak evaluation to ensure the integrity and safety of AI infrastructures.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Sep 20, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Sep 20, 2026
- Languages
- python
Source: github.language · Sep 20, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 20, 2026)
1. Start vLLM normally (e.g. `python -m vllm.entrypoints.api_server --model meta-llama/...`)Source link
Tags
README
🐳 Deploy A.I.G with Docker Docker RAM Disk Space : : : 20.10 or higher 4GB+ 10GB+ Once the service is running, you can access the A.I.G web interface at: <br Use from OpenClaw You can also call A.I.G directly from OpenClaw chat via the skill. Then configure to point to your runn...
For agents
This page has a .md twin and JSON over the API.