Aegis — security grade SAFE, quality 67/100

Security audit verdict: SAFE · quality 67/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by Justin0504 · MCP Server · ★ 337

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is Aegis safe to install? View the security audit →

About Aegis

AEGIS The firewall for AI agents. Every tool call. Intercepted. Classified. Blocked — before it executes. Download → · Roadmap → · Security → · Commercial → · Contributing → Your agent just called becau

ai-agentsai-safetyanthropicaudit-traillangchainllm-observabilitymcppolicy-engine

Quick Facts

Stars337
Forks38
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score67.0261193398254/100
Open Issues3
Last Updated2026-09-06
Created2026-03-04
Platformsmcp, node
Est. Tokens~22k

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Frequently Asked Questions

What is Aegis?

Aegis is Runtime policy enforcement for AI agents. Cryptographic audit trail, human-in-the-loop approvals, kill switch. Zero code changes.. It is categorized as a MCP Server with 337 GitHub stars.

What programming language is Aegis written in?

Aegis is primarily written in TypeScript. It covers topics such as ai-agents, ai-safety, anthropic.

How do I install or use Aegis?

You can find installation instructions and usage details in the Aegis GitHub repository at github.com/Justin0504/Aegis. The project has 337 stars and 38 forks, indicating an active community.

What license does Aegis use?

Aegis is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to Aegis?

The top alternatives to Aegis on Agent Skills Hub include asqav-sdk, rampart, tradememory-protocol. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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