数据与研究

securityclaw-autonomous-soc-agent

reason-machines/security-skills

Deploy and operate SecurityClaw, an autonomous SOC agent with RAG-based threat detection, LLM-powered anomaly analysis, and skill-based security automation

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安装命令

npx skills add https://github.com/reason-machines/security-skills --skill securityclaw-autonomous-soc-agent

SKILL.md

SecurityClaw Autonomous SOC Agent

Skill by ara.so — Security Skills collection.

SecurityClaw is a modular, skill-based autonomous Security Operations Center (SOC) agent that monitors OpenSearch/Elasticsearch data, builds RAG-based behavioral memory, and validates real-time anomalies using LLMs. It orchestrates security workflows through LangGraph, maintains conversation-based investigations, and provides both CLI and web interfaces for threat analysis.

Core Capabilities

  • Skill-based architecture: Each capability is an isolated module with Python logic + LLM instruction
  • RAG behavioral memory: Vector embeddings of network baselines stored in OpenSearch
  • Anomaly detection: Scheduled 1-minute watcher polls findings and escalates threats
  • LLM-powered analysis: Threat analyst validates anomalies using retrieval-augmented context
  • LangGraph orchestration: DECIDE→EXECUTE→EVALUATE supervisor loop with SQLite checkpointing
  • Web + CLI interfaces: React UI for chat investigations, CLI for automation
  • Provider agnostic: Swap OpenSearch↔Elasticsearch, Ollama↔other LLM providers

Installation

Prerequisites

SecurityClaw Autonomous SOC Agent

Skill by ara.so — Security Skills collection.

SecurityClaw is a modular, skill-based autonomous Security Operations Center (SOC) agent that monitors OpenSearch/Elasticsearch data, builds RAG-based behavioral memory, and validates real-time anomalies using LLMs. It orchestrates security workflows through LangGraph, maintains conversation-based investigations, and provides both CLI and web interfaces for threat analysis.

Core Capabilities

  • Skill-based architecture: Each capability is an isolated module with Python logic + LLM instruction
  • RAG behavioral memory: Vector embeddings of network baselines stored in OpenSearch
  • Anomaly detection: Scheduled 1-minute watcher polls findings and escalates threats
  • LLM-powered analysis: Threat analyst validates anomalies using retrieval-augmented context
  • LangGraph orchestration: DECIDE→EXECUTE→EVALUATE supervisor loop with SQLite checkpointing
  • Web + CLI interfaces: React UI for chat investigations, CLI for automation
  • Provider agnostic: Swap OpenSearch↔Elasticsearch, Ollama↔other LLM providers

Installation

Prerequisites