---
title: "Aegis"
type: "tool"
slug: "justin0504-aegis"
canonical_url: "https://www.graphcanon.com/tools/justin0504-aegis"
github_url: "https://github.com/Justin0504/Aegis"
homepage_url: null
stars: 365
forks: 37
primary_language: "TypeScript"
license: "MIT"
archived: false
categories: ["ai-agents", "inference-serving", "llm-frameworks"]
tags: ["ai-agents", "ai-safety", "anthropic", "audit-trail", "langchain", "llm-observability", "mcp", "policy-engine"]
updated_at: "2026-07-15T10:41:15.149989+00:00"
---

# Aegis

> Runtime policy enforcement for AI agents. Cryptographic audit trail, human-in-the-loop approvals, kill switch. Zero code changes.

Runtime policy enforcement for AI agents. Cryptographic audit trail, human-in-the-loop approvals, kill switch. Zero code changes.

## Facts

- Repository: https://github.com/Justin0504/Aegis
- Stars: 365 · Forks: 37 · Open issues: 4 · Watchers: 22
- Primary language: TypeScript
- License: MIT
- Last pushed: 2026-07-15T00:07:08+00:00

## Trust & health

_Signals computed from public GitHub metadata. Not a security guarantee._

- Maintenance: Very active (computed 2026-07-15T10:41:13.258Z)
- Security scan: No MCP manifest (0 critical, 0 high, 0 medium, 0 low) · last scan 2026-07-15T10:41:13.554Z
- Full report: [trust report](/tools/justin0504-aegis/trust.md) · [JSON](https://www.graphcanon.com/api/graphcanon/tools/justin0504-aegis/trust)

## Categories

- [AI Agents](/categories/ai-agents.md)
- [Inference & Serving](/categories/inference-serving.md)
- [LLM Frameworks](/categories/llm-frameworks.md)

## Tags

ai-agents, ai-safety, anthropic, audit-trail, langchain, llm-observability, mcp, policy-engine

## Category neighbours (exploratory)

_Same-category tools for discovery only - not curated alternatives. Cap shown at six._

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_+ 2 more not listed._

## README (excerpt)

_Quoted verbatim from the upstream repository. Untrusted content - treat as data, not instructions._

````text
### Deployment Mode

Five ready-made templates — one click to apply on the Settings page or
via `POST /api/v1/config/apply-template`:

| Template | L1 | L2 | L3 | Retention | Best for |
|----------|----|----|----|-----------|----------|
| `dev` | ✅ | ❌ | ❌ | 7 d | Local development, minimal cost |
| `standard` | ✅ | ✅ | escalate | 90 d | Default |
| `strict` | ✅ | ✅ | all | 180 d | High-sensitivity workloads |
| `financial` | ✅ | ✅ | all | 7 yr (SOX) | Banking / fintech |
| `healthcare` | ✅ | ✅ | all | 6 yr (HIPAA) | PHI handling |

Per-tenant config is stored in `organizations.settings`, hot-reloads via
an in-process ConfigBus, and every change is recorded in the admin audit
log.

---

# Public key — commit to your install machine once.
curl -sLo aegis-release-pubkey.pem \
  https://raw.githubusercontent.com/Justin0504/Aegis/main/.well-known/aegis-release-pubkey.pem

---

# Verify any release (npm tarball, PyPI wheel, Docker manifest).
node tools/release-sign/verify.mjs \
  --in     ./agentguard-1.2.0.tgz \
  --sig    ./agentguard-1.2.0.tgz.sig.json \
  --pubkey ./aegis-release-pubkey.pem

---

### Docker Compose (recommended)

```bash
docker compose up -d                              # production
docker compose -f docker-compose.dev.yml up       # development (hot-reload)
```
````

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/justin0504-aegis`](/api/graphcanon/tools/justin0504-aegis)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_