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@aegis-kernel/cli

v1.4.0

Published

Developer CLI for Aegis Invariant Kernel: init, test, and report

Downloads

301

Readme

🛡️ @aegis-kernel/cli

Developer CLI & Shift-Left Invariant Auditing Tool for Aegis Invariant Kernel
Academic Benchmark Runner • Invariant Scanner • Compliance Dossier Verification • Live REPL

License: MIT TypeScript Node.js


📦 Installation

# Global installation
npm install -g @aegis-kernel/cli

# Or run directly via npx
npx aegis --help

🛠️ CLI Commands & Usage

1. Workspace & Diagnostic Commands

# Initialize aegis.config.yaml and local .aegis/ directory
npx aegis init

# Run system health diagnostics across all invariant subsystems
npx aegis doctor

# Scan workspace files, prompts, and MCP schemas for secrets & prompt injection
npx aegis scan .

2. Testing & Academic Benchmarks

# Run security bounds testbed & compute Agent Safety Scorecard
npx aegis test

# Run standardized academic evaluation suites (InjecAgent, AgentDojo, MCPTox)
npx aegis eval all --output ./academic-evidence.json

# Run academic evaluation with cryptographic double-blind attestation
npx aegis eval all --blinded

# Run 100-vector tricky adversarial stress testbed
npx aegis benchmark --tricky

3. Compliance & GRC Audit Verification

# Export audit-ready compliance dossier (SOC 2, ISO 42001, EU AI Act, HIPAA)
npx aegis compliance export --format markdown --output ./compliance-dossier.md

# Cryptographically verify Merkle root chains and signatures in an audit dossier
npx aegis verify-proof ./compliance-dossier.json --key "signing-key"

# Display threat coverage matrix mapped to OWASP GenAI Top 10 (2026) & MITRE ATLAS
npx aegis matrix

4. Interactive & Rule Pack Management

# Interactive terminal REPL for live tool clearance evaluation
npx aegis repl

# Deterministically replay historical audit logs against active policy rules
npx aegis replay ./audit-log.json

# Discover, install, and validate invariant rule packs
npx aegis pack list
npx aegis pack validate ./my-pack.yaml
npx aegis hub list

📄 License

Distributed under the MIT License. Copyright (c) 2026 Sneh Gabani.