A.I.G (AI Infra Guard) vs flue: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of A.I.G (AI Infra Guard) and flue — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
A.I.G (AI Infra Guard)
Tencent Zhuque Lab
Tencent's open-source AI red teaming platform for scanning agents, agent skills, MCP servers and AI infrastructure, plus LLM jailbreak evaluation.
Key features
- Agent Skills Scan: Audits agent skill packages against a nine-category risk taxonomy aligned with the public SkillTrustBench T01-T09 classification, including detection of .pyc bytecode bypasses and charset smuggling.
- MCP Server Scan: Inspects MCP servers for threats such as tool poisoning, credential exfiltration and command injection, with tool whitelisting to prevent remote code execution during dynamic scanning.
- AI Infrastructure Vulnerability Scanning: Checks deployed AI components against a library that has grown to roughly 130 components and over 2,000 CVE rules, covering frameworks such as llama.cpp.
- Jailbreak Evaluation: Runs single-turn jailbreak operators plus multi-turn attack techniques including Many-Shot, PAIR, GOAT and ActorAttack to measure a model's resistance.
- Agent Scan with OWASP Coverage: Assesses running agents using OWASP-derived skills and web exfiltration detection, with a dedicated agent red team skill for comprehensive assessment.
- Standalone Scanner CLIs: skill-scan, mcp-scan and agent-scan each install as an independent command-line tool so scans can be wired directly into enterprise CI/CD pipelines.
- Docker Deployment with Web UI: Deploy the full platform with Docker on 4GB+ RAM and reach the web interface at localhost:8088, or use a one-click install script or a source build.
- AI Security Skill Market: A catalog of official security scanning skills, with the frontend fully open-sourced and integration available from OpenClaw chat via the aig-scanner skill.
Best for
- Pre-Deployment Agent Audit: Scan an internally built agent and its skill bundle for prompt injection, exfiltration and privilege risks before it is released to staff.
- MCP Supply Chain Review: Vet third-party MCP servers for tool poisoning and credential exfiltration before connecting them to production assistants.
- CI/CD Security Gate: Run skill-scan as a standalone CLI on every pull request so risky agent skills fail the build rather than shipping.
- Model Safety Benchmarking: Measure how a deployed LLM holds up against single and multi-turn jailbreak techniques before and after guardrail changes.
- AI Infrastructure Patch Triage: Inventory AI serving components and match them against the CVE rule library to prioritise which hosts need patching.
- Security Research and Reporting: Use the open scan engines and SkillTrustBench alignment as a reproducible basis for internal or published AI security research.
f
flue
Astro
Open-source TypeScript agent harness framework for building autonomous agents and AI workflows.
Key features
- Agent Harness: A programmable TypeScript harness giving any model sessions, tools, skills, instructions, and filesystem access.
- Autonomous Agents: Build agents that keep context across conversations and events while working toward a goal.
- Workflows: Run structured automations where your code guides agent reasoning from input to finished result.
- Secure Sandboxes: Give agents an isolated environment to use tools, modify files, and complete real work safely.
- Durable Execution: Agents preserve progress and recover through failures and restarts.
- Subagents and Tools: Delegate tasks to specialized subagents and give agents typed actions for APIs and data.
- MCP and Observability: Connect tools via Model Context Protocol and monitor agents with OpenTelemetry and Braintrust.
Best for
- Building Autonomous Agents: Create Claude Code or Codex-style agents that complete open-ended tasks independently.
- Structured Workflows: Automate multi-step processes where code controls the agent's reasoning path.
- Safe Tool Use: Run agents in a secure sandbox so they can take real actions without risk to your systems.
- Local or Hosted Deployment: Run agents from the CLI during development, then deploy to a hosted runtime.
- Tool Integration: Connect agents to authenticated services through MCP servers.