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alokemajumder/AegisClaw

AegisClaw

Autonomous Security Validation Platform

Continuously validate your security controls with safe, ATT&CK-mapped emulations.
Prove outcomes with audit-grade receipts. Keep all data and LLM reasoning local.

Quick StartHow It WorksArchitectureDeploymentSecurity ModelContributing


Why AegisClaw?

Security teams run periodic red/blue exercises and hope their controls hold in between. AegisClaw replaces hope with proof — it runs safe, bounded adversary emulations continuously and autonomously, then verifies whether your controls actually observe, detect, alert, and ticket as expected.

Every validation run produces a cryptographically signed receipt. Every finding is backed by evidence. All data stays in your network.

NVIDIA-Accelerated AI Security

AegisClaw integrates deeply with the NVIDIA AI agent ecosystem to deliver enterprise-grade LLM reasoning and sandboxed agent execution:

  • NVIDIA NIM — Optimized inference microservices for Nemotron models with configurable thinking budgets and OpenAI-compatible tool-calling
  • NVIDIA OpenShell — Apache 2.0 runtime for sandboxed agent execution with Landlock LSM, seccomp, network namespacing, and a Privacy Router for secure LLM inference
  • NeMoClaw — Always-on assistant stack powering AegisClaw's multi-agent orchestration with 34+ hosted models
  • NVIDIA Morpheus — GPU-accelerated security analytics via Triton Inference Server for real-time threat detection

Quick Start

git clone https://github.com/alokemajumder/AegisClaw.git
cd AegisClaw

cp .env.example .env
# Set AEGISCLAW_AUTH_JWT_SECRET to a strong random value (openssl rand -hex 32)

docker compose -f deploy/docker-compose.yml up -d
make migrate && make seed

# UI: http://localhost:3000  (admin@aegisclaw.local / admin)
# API: http://localhost:8080

See the Deployment Guide for production setup, hardening, and Kubernetes.

How It Works

  Trigger (schedule / manual / API)
              |
              v
  ┌───────────────────────────┐
  │     Orchestrator          │
  │  Policy + Run Lifecycle   │
  └─────┬───────────┬────────┘
        |           |
  ┌─────v─────┐ ┌───v──────┐
  │ Emulation │ │Validation│    12 agents across 4 squads
  │  (Red)    │ │ (Blue)   │    execute a 3-phase pipeline
  │ Plan+Exec │ │Verify+Eval│   on every run
  └─────┬─────┘ └───┬──────┘
        |           |
        v           v
  ┌───────────────────────────┐
  │   Improvement (Purple)    │
  │ Coverage + Drift + Regr.  │
  └─────────────┬─────────────┘
                v
  ┌───────────────────────────┐
  │    Evidence Vault         │
  │ Findings  Receipts  Rpts  │
  └───────────────────────────┘

Governance Tiers control what runs autonomously:

Tier Scope Approval
0 - Passive Telemetry health, config posture Autonomous
1 - Benign Safe atomic tests (EICAR, allowlisted commands, SIEM/EDR queries) Autonomous
2 - Sensitive Auth-adjacent, operational impact Human approval required
3 - Prohibited DoS, exfil, destructive Always blocked

Key Capabilities

Continuous Validation — Schedule ATT&CK-mapped emulations with cron expressions, blackout windows, rate limits, and concurrency caps. The orchestrator runs 12 agents through plan, execute, and verify phases automatically.

Audit-Grade Evidence — Every run produces HMAC-SHA256 signed receipts capturing scope, steps, evidence, and outcomes. Findings are deduplicated via SHA256 clustering. All artifacts stored in an immutable MinIO vault.

12 Connectors — Query telemetry from your SIEM, verify detections in your EDR, create tickets in your ITSM, run GPU-accelerated analytics, and send notifications — all through a settings-driven UI with no code changes required.

Category Connectors
SIEM Sentinel, Splunk, Elastic Security
EDR/XDR Defender for Endpoint, CrowdStrike Falcon
ITSM ServiceNow, Jira Service Management
Analytics NVIDIA Morpheus (GPU-accelerated threat detection via Triton)
Notifications Teams, Slack
Identity Entra ID, Okta

Flexible LLM Backend — Runs on any hardware from a $200 used GPU to NVIDIA DGX Spark:

  • Ollama (default) — Free, open-source, runs on consumer GPUs (RTX 3060+) or CPU-only
  • NVIDIA NIMNemotron 3 models (Nano 30B, Super 120B, Ultra 253B) with hybrid Mamba-Transformer MoE architecture, 1M context windows, configurable thinking budgets, and OpenAI-compatible tool-calling for agent function invocation
  • NeMo Guardrails — Optional content safety, jailbreak detection, and topic control NIMs for LLM prompt safety
  • NVIDIA OpenShell — Sandboxed agent execution with 4-layer isolation (Landlock LSM, seccomp, network namespacing, Privacy Router) and tier-based policy generation

All reasoning stays within your infrastructure. See the NVIDIA Deployment Guide for GPU sizing and cost optimization.

Enterprise Safety Controls — Fail-closed policy enforcement, hard target allowlists, circuit breakers on all connector calls, global kill switch (NATS-propagated, persistent across restarts), RBAC on all 59 API endpoints, persistent token blacklisting, and account lockout.

Tech Stack

Component Technology
Backend Go 1.25+ (8 microservices + CLI)
Frontend Next.js 15, React 19, Tailwind, shadcn/ui
Database PostgreSQL 16 (16 tables, golang-migrate)
Messaging NATS + JetStream (5 streams)
Evidence MinIO (S3-compatible)
LLM Ollama (local, free) or NVIDIA NIM + Nemotron 3 (high-perf, 1M context, tool-calling)
LLM Safety NeMo Guardrails (content safety, jailbreak detection)
Agent Sandbox NVIDIA OpenShell (Landlock + seccomp + netns isolation)
Analytics NVIDIA Morpheus (GPU-accelerated security analytics)
Observability OpenTelemetry, Prometheus, Grafana, Jaeger

Documentation

Document Description
Architecture Services, agent squads, data flows, NATS streams, database schema
Security Model Governance tiers, safety controls, auth, RBAC, threat model
Deployment Guide Docker Compose, production hardening, backup/restore, CLI, troubleshooting
NVIDIA GPU Deployment GPU sizing, NIM setup, Nemotron 3 models, OpenShell sandboxing, cost optimization
Connector Development Build custom connectors using the Connector SDK
Playbook Authoring Create validation playbooks (YAML format)

Project Structure

AegisClaw/
├── cmd/           Service entrypoints (9 binaries)
├── internal/      Shared packages (config, auth, database, nats, policy, receipt, evidence, ...)
├── pkg/           Public SDKs (connectorsdk, agentsdk)
├── agents/        12 agents across 4 squads
├── connectors/    12 connector implementations
├── playbooks/     13 validation playbooks (Tier 0-2)
├── web/           Next.js frontend (15 pages)
├── deploy/        Docker Compose, Dockerfiles, scripts
├── docs/          Documentation
└── configs/       Default YAML configuration

Roadmap

Complete

  • Core platform with 8 Go microservices + CLI + Next.js frontend
  • Full end-to-end validation pipeline (12 agents, 3-phase RunEngine)
  • 12 connectors (SIEM, EDR, ITSM, Analytics, Notifications, Identity) including NVIDIA Morpheus
  • 13 playbooks with real execution (SIEM queries, EDR health, EICAR markers, detection verification)
  • Evidence vault, finding dedup, HMAC-SHA256 receipt signing
  • JWT auth, RBAC, token blacklisting, account lockout, kill switch
  • Docker Compose with health checks, resource limits, graceful shutdown
  • Production audit: 22 security fixes, connection pool hardening, input validation
  • NVIDIA NIM integration with Nemotron 3 model family (Nano 30B, Super 120B, Ultra 253B — hybrid Mamba-Transformer MoE, 1M context)
  • NeMo Guardrails integration (content safety, jailbreak detection, topic control)
  • GPU deployment profiles for consumer GPUs (RTX 3060-5090) through DGX Spark
  • NVIDIA OpenShell agent sandboxing — Gateway v1 API client, tier-based policy generation, Privacy Router for secure LLM inference
  • SSE (Server-Sent Events) real-time updates — NATS-to-browser bridge with global and per-run event streams
  • NeMoClaw multi-agent orchestration with configurable thinking budgets and tool-calling

In Progress

  • PDF report renderer
  • Kubernetes Helm chart
  • Integration and end-to-end tests

Planned

  • Full ATT&CK coverage heatmap visualization
  • SSO/OIDC integration
  • HA and backup/restore automation
  • Vertical-specific playbook packs
  • Compliance-ready exports (SOC 2, ISO 27001)

Contributing

See CONTRIBUTING.md for setup instructions and coding standards.

git checkout -b feature/your-feature
make lint && make test
# Submit a pull request

License

Apache License 2.0 — see LICENSE.

Security

Report vulnerabilities responsibly. See SECURITY.md for our disclosure policy.


Built for security teams who believe in proving their defenses work.

About

AegisClaw is an open-source, enterprise-grade platform that continuously validates whether your security controls actually work. Instead of periodic manual red/blue exercises, AegisClaw runs safe, bounded adversary emulations autonomously and verifies .

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