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CyberStrikeAI

OrganizationPopular
AIPentest

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

PublisherAIPentest
RepositoryCyberStrikeAI
LanguageGo
Forks
1.2K
Stars
7K
Available tools
0
Transport typestdio
Categories
LicenseApache-2.0
Links
  • Connect tools to AI workflows

    CyberStrikeAI exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    7K stars and 1.2K forks from the linked repository.

CyberStrikeAI

中文 | English

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

CyberStrikeAI connects planning, execution, human oversight, evidence, and replay in one auditable workspace. Built in Go, it combines Eino-powered agents, MCP-native tools, RAG knowledge, visual workflows, and attack-chain modeling and analysis for authorized security operations.

Start here: Quick start · Documentation · Security hardening

[!IMPORTANT] Use CyberStrikeAI only on systems you own or are explicitly authorized to test. For shared or production environments, review the security model and hardening guide before enabling high-risk tools, WebShell, or C2 capabilities.

Interface & Integration Preview

System Dashboard Overview

The dashboard provides a comprehensive overview of system runtime status, security vulnerabilities, tool usage, and knowledge base, helping users quickly understand the platform's core features and current state.

Core Features Overview

Highlights

Agents and orchestration

  • 🤖 Agentic execution translates natural-language intent into governed, auditable security actions.
  • 🧩 Eino orchestration supports single-agent execution plus Deep, Plan-Execute, and Supervisor multi-agent modes.
  • 🔀 Graph workflows combine Agents, tools, conditions, approvals, and outputs into reusable flows.
  • 🎭 Role-based testing provides focused prompts and tool policies for common security scenarios.

Tools and knowledge

  • 🧰 Security tools include 100+ curated YAML recipes with custom extensions and role-scoped access.
  • 🔌 MCP integration supports HTTP, stdio, SSE, external federation, and dynamic tool discovery.
  • ⏱️ Resilient tool execution runs blocking MCP/tool calls in workers with bounded agent waits, resumable execution_id polling, cancellation, per-server circuit breakers, concurrency limits, and unified output caps.
  • 🎯 Agent Skills follow the standard Skill layout and support progressive, on-demand loading.
  • 📚 Knowledge base combines query rewriting, vector retrieval, reranking, and result post-processing.
  • 🖼️ Vision analysis uses a separate vision model for screenshots, captchas, and UI while retaining text summaries only.

Governance and audit

  • 🧑‍⚖️ Human in the loop provides approval modes, tool allowlists, audit-agent review, and traceable decisions.
  • 🛡️ Call blocking under Security adds configurable regex checks before MCP execution, reminder templates, and dry runs, with government-domain protection enabled by default. See Tool call blocking.
  • 🔐 Platform RBAC supports multiple users, system and custom roles, scoped permissions, ownership, and explicit assignments.
  • 🔒 Security and audit provide authenticated access, audit logs, SQLite persistence, and operational evidence retention.
  • 📄 Result governance stores the same capped tool result seen by the agent, protects resume paths from oversized historical output, and adds UI safeguards for large detail views. See Tool Execution Governance.

Security operations

  • 📁 Conversation management provides pinning, renaming, and batch organization.
  • 📂 Projects and attack chains connect cross-session facts, risk scoring, graph views, and step-by-step replay.
  • 🗂️ Asset management normalizes and deduplicates domains, IP addresses, ports, and services; supports XLSX/CSV import and export, advanced filters and saved views, ownership and business metadata, cross-page bulk maintenance, and duplicate merging; and tracks scan coverage, linked vulnerabilities, and risk state. See the Asset Management guide.
  • 🛡️ Vulnerability management provides severity classification, lifecycle tracking, filtering, and statistics.
  • 📋 Batch tasks provide queued execution, editing, status tracking, and retained results.
  • 📱 Chatbots connect Personal WeChat, WeCom, DingTalk, Lark, Telegram, Slack, Discord, and QQ Bot.

Authorized security operations

  • 🐚 WebShell management provides connection management, a virtual terminal, file operations, and AI-assisted workflows.
  • 📡 Built-in C2 provides listeners, encrypted beacons, sessions, task queues, payload helpers, and live events.

WebShell, C2, and other high-risk capabilities are for systems you own or are explicitly authorized to test. See the security model and hardening guide.

Plugins

CyberStrikeAI includes optional integrations under plugins/.

  • Burp Suite extension: plugins/burp-suite/cyberstrikeai-burp-extension/
    Build output: plugins/burp-suite/cyberstrikeai-burp-extension/dist/cyberstrikeai-burp-extension.jar
    Docs: plugins/burp-suite/cyberstrikeai-burp-extension/README.md
  • Browser extension (Chrome / Edge): plugins/browser-extension/cyberstrikeai-browser-extension/
    Capture Network traffic in DevTools and send it to CyberStrikeAI for AI-assisted security testing—aligned with the Burp plugin.
    Install: chrome://extensions/ → Load unpacked → F12 → CyberStrikeAI tab
    Package output: plugins/browser-extension/cyberstrikeai-browser-extension/dist/cyberstrikeai-browser-extension.zip
    Docs: plugins/browser-extension/cyberstrikeai-browser-extension/README.md / README.zh-CN.md

Tool Overview

CyberStrikeAI ships with 100+ curated tools covering the whole kill chain:

  • Network Scanners – nmap, masscan, rustscan, arp-scan, nbtscan
  • Web & App Scanners – sqlmap, nikto, dirb, gobuster, feroxbuster, ffuf, httpx
  • Vulnerability Scanners – nuclei, wpscan, wafw00f, dalfox, xsser
  • Subdomain Enumeration – subfinder, amass, findomain, dnsenum, fierce
  • Network Space Search Engines – fofa_search, zoomeye_search, quake_search, shodan_search
  • API Security – graphql-scanner, arjun, api-fuzzer, api-schema-analyzer
  • Container Security – trivy, clair, docker-bench-security, kube-bench, kube-hunter
  • Cloud Security – prowler, scout-suite, cloudmapper, pacu, terrascan, checkov
  • Binary Analysis – gdb, radare2, ghidra, objdump, strings, binwalk
  • Exploitation – metasploit, msfvenom, pwntools, ropper, ropgadget
  • Password Cracking – hashcat, john, hashpump
  • Forensics – volatility, volatility3, foremost, steghide, exiftool
  • Post-Exploitation – linpeas, winpeas, mimikatz, bloodhound, impacket, responder
  • CTF Utilities – stegsolve, zsteg, hash-identifier, fcrackzip, pdfcrack, cyberchef
  • System Helpers – exec, create-file, delete-file, list-files, modify-file

See tools/README_EN.md for tool definitions, customization, and usage notes.

Basic Usage

Quick Start (One-Command Deployment)

Prerequisites:

One-Command Deployment:

bash
git clone https://github.com/Ed1s0nZ/CyberStrikeAI.git
cd CyberStrikeAI
chmod +x run.sh && ./run.sh

The run.sh script will automatically:

  • ✅ Check and validate Go & Python environments
  • ✅ Create Python virtual environment
  • ✅ Install Python dependencies
  • ✅ Download Go dependencies
  • ✅ Build the project
  • ✅ Start the server

Verify the startup:

  1. Confirm the terminal displays ● ONLINE followed by the actual Web UI URL.
  2. Open that URL; the default HTTPS mode uses a local self-signed certificate, so accept the browser warning once.
  3. On a new installation, store the one-time admin password shown under ADMIN SETUP REQUIRED, sign in, and change it immediately.

Networking defaults: run.sh starts the server with --https and the repo config.yaml (local self-signed TLS; better for many concurrent streams). Use ./run.sh --http for plain HTTP. In production, set server.tls_cert_path / server.tls_key_path in config.yaml (see comments there). For manual runs, add --https or CYBERSTRIKE_HTTPS=1; if -config is wrong, the binary prints a short usage hint on stderr.

First-Time Configuration:

  1. Configure AI channels (required before first use)

    • After launch, open https://127.0.0.1:8080/ (or https://localhost:8080/; replace 8080 with server.port in config.yaml) and accept the self-signed certificate warning once. If you used ./run.sh --http, use http:// instead.
    • Go to System SettingsBasic SettingsAI Channel Configuration, add or edit a channel, then fill in provider, Base URL, API key, model, and token limits. Click Save changes. The left channel list supports setting a default, copy, delete, and bulk probe.
      yaml
      ai:
        default_channel: openai-main
        channels:
          openai-main:
            name: OpenAI Main
            provider: openai_compatible
            api_key: "${OPENAI_API_KEY}"
            base_url: "https://api.openai.com/v1"  # or https://api.deepseek.com/v1
            model: "gpt-4o"  # or deepseek-chat, qwen3-max, etc.
            max_total_tokens: 120000
            max_completion_tokens: 16384
    • Or edit config.yaml directly before launching. ai.default_channel is used for new conversations and tasks that do not explicitly select a channel; the chat page can also select any saved channel per session.
  2. Login - On first startup the console prints an auto-generated initial admin password; create accounts from Platform permissions → User management

  3. Install security tools (optional) - Install tools from tools/ as needed; missing tools are skipped or substituted at runtime. Common examples:

    macOS (Homebrew):

    bash
    brew install nmap masscan sqlmap nikto gobuster ffuf hydra hashcat nuclei subfinder

    Linux (Kali / Debian / Ubuntu):

    bash
    sudo apt update
    sudo apt install -y nmap masscan sqlmap nikto gobuster hydra hashcat john binwalk
    # On some distros, install ffuf/nuclei/subfinder via go install or upstream docs

    See the tools/ directory for the full list; refer to each tool's official docs for install details.

Alternative Launch Methods:

bash
# Direct Go run (set up env yourself); add --https to match run.sh defaults
go run cmd/server/main.go --https

# Manual build
go build -o cyberstrike-ai cmd/server/main.go
./cyberstrike-ai --https

If server logs show client sent an HTTP request to an HTTPS server, a client is still using http:// on a TLS-only port—switch the URL to https://.

Note: The Python virtual environment (venv/) is automatically created and managed by run.sh. Tools that require Python (like api-fuzzer, http-framework-test, etc.) will automatically use this environment.

Upgrade and Compatibility

CyberStrikeAI one-click upgrade:

  1. (First time) enable the script: chmod +x upgrade.sh
  2. Upgrade with: ./upgrade.sh (optional flags: --tag vX.Y.Z, --no-venv, --yes). Local tools/, roles/, and skills/ are always preserved.
  3. The script will back up your config.yaml and data/, upgrade the code from GitHub Release, update config.yaml's version, then restart the server.

Recommended one-liner: chmod +x upgrade.sh && ./upgrade.sh --yes

If something goes wrong, you can restore from .upgrade-backup/ (or manually copy /data and config.yaml back) and run ./run.sh again.

Requirements / tips:

  • You need curl or wget for downloading Release packages.
  • rsync is recommended/required for the safe code sync.
  • If GitHub API rate-limits you, set export GITHUB_TOKEN="..." before running ./upgrade.sh.

⚠️ Before upgrading: review the target release notes for configuration, database, and API changes. Backups are required even for patch upgrades; a version number alone is not a compatibility guarantee.

Configuration

Use config.example.yaml as the authoritative configuration template and copy only the values required for your environment. At minimum, configure the server and one AI channel:

yaml
server:
  host: "127.0.0.1"
  port: 8080
ai:
  default_channel: openai-main
  channels:
    openai-main:
      provider: openai_compatible
      api_key: "${OPENAI_API_KEY}"
      base_url: "https://api.openai.com/v1"
      model: "your-model"

openai is a backward-compatible runtime field; maintain new model settings in ai.channels. Do not commit real credentials. Review the configuration reference, recommended profiles, and security hardening guide before exposing the service beyond localhost.

Related documentation

Project Layout

CyberStrikeAI/
├── cmd/                 # Server, MCP stdio entrypoints, tooling
├── internal/            # Agent, MCP core, handlers, C2 (`internal/c2`), security executor
├── web/                 # Static SPA + templates
├── tools/               # YAML tool recipes (100+ examples provided)
├── roles/               # Role configurations (12+ predefined security testing roles)
├── skills/              # Agent Skills dirs (SKILL.md + optional files; demo: cyberstrike-eino-demo)
├── agents/              # Multi-agent Markdown (orchestrator.md + sub-agent *.md)
├── docs/                # Topic docs (deployment, config, security, API, knowledge base, C2, WebShell, etc.)
├── images/              # Docs screenshots & diagrams
├── config.yaml          # Runtime configuration
├── run.sh               # Convenience launcher
└── README*.md

Basic Usage Examples

Scan open ports on 192.168.1.1
Perform a comprehensive port scan on 192.168.1.1 focusing on 80,443,22
Check if https://example.com/page?id=1 is vulnerable to SQL injection
Scan https://example.com for hidden directories and outdated software
Enumerate subdomains for example.com, then run nuclei against the results

Advanced Playbooks

Load the recon-engagement template, run amass/subfinder, then brute-force dirs on every live host.
Use external Burp-based MCP server for authenticated traffic replay, then pass findings back for graphing.
Compress the 5 MB nuclei report, summarize critical CVEs, and attach the artifact to the conversation.
Build an attack chain for the latest engagement and export the node list with severity >= high.

404Starlink

CyberStrikeAI has joined 404Starlink

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Community and Support

License

CyberStrikeAI is licensed under the Apache License 2.0.
See the LICENSE file for details.


⚠️ Disclaimer

This tool is for educational and authorized testing purposes only!

CyberStrikeAI is a professional security testing platform designed to assist security researchers, penetration testers, and IT professionals in conducting security assessments and vulnerability research with explicit authorization.

By using this tool, you agree to:

  • Use this tool only on systems where you have clear written authorization
  • Comply with all applicable laws, regulations, and ethical standards
  • Take full responsibility for any unauthorized use or misuse
  • Not use this tool for any illegal or malicious purposes

The developers are not responsible for any misuse! Please ensure your usage complies with local laws and regulations, and that you have obtained explicit authorization from the target system owner.

For vulnerability reporting and deployment hardening guidance, see SECURITY.md.


Need help or want to contribute? Open an issue or PR—community tooling additions are welcome!

Installation

TypingMind
{
  "mcpServers": {
    "cyberstrikeai": {
      "command": "./cyberstrikeai",
      "args": []
    }
  }
}

Use CyberStrikeAI MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once CyberStrikeAI is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add CyberStrikeAI as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the CyberStrikeAI MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "cyberstrikeai": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the CyberStrikeAI MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the CyberStrikeAI MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use CyberStrikeAI to help me with this task?
CyberStrikeAI
Sure. I read it.
Here is what I found using CyberStrikeAI.

Frequently asked questions

What is the CyberStrikeAI MCP server used for?

CyberStrikeAI is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use CyberStrikeAI MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use CyberStrikeAI with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use CyberStrikeAI MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With CyberStrikeAI connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect CyberStrikeAI MCP to TypingMind?

CyberStrikeAI runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does CyberStrikeAI MCP provide in TypingMind?

CyberStrikeAI exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use CyberStrikeAI MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If CyberStrikeAI requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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