# Ed1s0nZ/CyberStrikeAI

The system of action for AI-native cybersecurity—where intent becomes governed execution, evidence becomes operational memory, and every operation improves the next.

Repository: https://github.com/Ed1s0nZ/CyberStrikeAI
Canonical: https://ross.abutalabs.com/products/cyberstrikeai
Language: Go
License: Apache-2.0
License Family: permissive
Topics: ai, ai-agents, ai-cybersecurity, ai-penetration-testing, ai-security-tool, ctf-tools, mcp, ai-hacking, pentesting-tools
Last push: 2026-08-26T07:00:22+00:00

## Health v2 (maintenance only)
Score: 79/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 99, release rhythm 87, longevity 21
- inputs: {"age_days": 298, "days_push": 7, "days_rel": 9, "gap_med": 1, "n_releases_24m": 144}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5991, forks 959 (observed 2026-08-28T04:09:34.025378+00:00)

## What it is
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
- artifact type: application
- maturity: active
- function: agent-framework, mcp, rag, penetration-testing, security, chat-interface, workflow-automation
- domain: security, penetration-testing, artificial-intelligence, developer-tools
- platform: go, self-hosted, cli
- tags: 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
- Ed1s0nZ/CyberStrikeAI (main) score 79

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:34.025378+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:49:51.426990+00:00, confidence not recorded.
  - readme: https://github.com/Ed1s0nZ/CyberStrikeAI (fetched 2026-08-28T04:09:34.025378+00:00, sha c0a1218d0c21)
- Data as of 2026-08-30T08:39:29.467469+00:00.