A.I.G (AI Infra Guard) vs EQK: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of A.I.G (AI Infra Guard) and EQK — 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.
EQK
kuja.dev (Aakashdhruv Vashisht)
Per-app macOS equalizer with on-device AI song analysis and 3,985 bundled headphone correction profiles — nothing leaves your Mac.
Key features
- Per-App Patchbay Routing: Route individual music and video apps through independent equalizers so mixed browser audio never contaminates the signal chain.
- AI Song Live Analysis: An on-device engine analyzes each track as it starts and reshapes tone in real time over the per-app EQ and headphone correction.
- 3,985 Headphone Correction Profiles: Bundled AutoEq correction curves for a wide catalog of headphones, earphones, and IEMs are read by the AI to compensate for gear response.
- User Tweaks Stay On Top: Manual EQ adjustments always sit on top of AI and correction lanes, so listener taste is never overwritten.
- Fully On-Device Privacy: All analysis happens locally with no signup, no cloud, and no accounts — nothing leaves the Mac.
- Apple-Notarized macOS App: Distributed as a notarized native app for macOS 15.6+ with a free player tier that remains free forever.
- Buy-Once License: A one-time ₹1,000 Premium purchase activates on up to two Macs and includes free updates for the EQK 1.x line.
Best for
- Audiophile Listening on Mac: Music enthusiasts pair headphone correction with AI song analysis to hear a corrected, tone-matched signal on their exact gear.
- Content Creator Monitoring: Editors and streamers route their DAW or video app through EQK to preview mixes against a corrected reference.
- Isolating App Audio: Users tune podcasts, music, or video separately so switching apps does not mean re-EQing every time.
- Privacy-Conscious Listeners: Anyone unwilling to send listening data to the cloud gets AI-driven EQ that runs entirely on device.
- IEM and Headphone Reviewers: Reviewers with many pairs compare gear against consistent AutoEq baselines and their own taste tweaks.
- Free Player for Casual Users: Users who want basic per-app EQ without AI keep the free player tier indefinitely.