Ed1s0nZ/CyberStrikeAI

Health v2 · maintenance only

Adoption not part of the score

5991 stars · 959 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

CyberStrikeAI is a Go-based AI-native cybersecurity platform that combines LLM-powered agents, MCP-native tools, RAG knowledge bases, and visual workflows for authorized penetration testing and CTF operations. It provides an auditable workspace with planning, human oversight, evidence capture, and replay so every security operation improves the next.

Use cases

• run AI-assisted penetration tests on systems I'm authorized to test
• orchestrate MCP security tools through an agent with human approval
• solve CTF challenges with AI agents
• keep an auditable evidence trail of security operations
• manage webshells and attack chains in one console
• build a security knowledge base with RAG for pentesting
• model and analyze attack chains automatically

When to choose

• you want an all-in-one AI-driven pentesting workspace with governance and audit trails
• you need MCP-native tool integration with human-in-the-loop oversight
• you're doing authorized red-team work or CTFs and want evidence replay and knowledge accumulation

When to avoid

• you need a passive vulnerability scanner or compliance auditor rather than an active operations platform
• you lack explicit authorization to test target systems
• you want a lightweight single-purpose tool instead of a full platform with web console and knowledge base

Facets

application · maturity active

agent-framework mcp rag penetration-testing security chat-interface workflow-automation security penetration-testing artificial-intelligence developer-tools go self-hosted cli ai-cybersecurity pentesting ctf-tools red-team vulnerability-management attack-chain-analysis evidence-replay human-in-the-loop ai-agents docker web-server

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Ed1s0nZ/CyberStrikeAI")