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CyberStrikeAI is an **AI-native security testing platform** built in Go. It integrates 100+ security tools, an intelligent orchestration engine, role-based testing with predefined security roles, a skills system with specialized testing skills, comprehensive lifecycle management capabilities, and a **built-in lightweight C2 (Command & Control) framework** for **authorized** engagements (listeners, encrypted implants, sessions, tasks, real-time events, REST and MCP). Through native MCP protocol and AI agents, it enables end-to-end automation from conversational commands to vulnerability discovery, attack-chain analysis, knowledge retrieval, and result visualizationβ€”delivering an auditable, traceable, and collaborative testing environment for security teams. ## Interface & Integration Preview
### System Dashboard Overview System Dashboard *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
Web Console
Web Console 		Task Management
Task Management 		Vulnerability Management
Vulnerability Management
WebShell Management
WebShell Management 		MCP Management
MCP management 		Knowledge Base
Knowledge Base
Skills Management
Skills Management 		Agent Management
Agent Management 		Role Management
Role Management
System Settings
System settings 		MCP stdio Mode
MCP stdio mode 		Burp Suite Plugin
Burp Suite plugin
## Highlights - πŸ€– AI decision engine with OpenAI-compatible models (GPT, Claude, DeepSeek, etc.) - πŸ”Œ Native MCP implementation with HTTP/stdio/SSE transports and external MCP federation - 🧰 100+ prebuilt tool recipes + YAML-based extension system - πŸ“„ Large-result pagination, compression, and searchable archives - πŸ”— Attack-chain graph, risk scoring, and step-by-step replay - πŸ”’ Password-protected web UI, audit logs, and SQLite persistence - πŸ“š Knowledge base (RAG) with embedding-based vector retrieval (cosine similarity), optional **Eino Compose** indexing pipeline, and configurable post-retrieval budgets / reranking hooks - πŸ“ Conversation grouping with pinning, rename, and batch management - πŸ“‚ **Project management**: shared facts (blackboard) across sessions, `upsert_project_fact` + `links` to chain paths; attack-chain and project fact graph views - πŸ›‘οΈ Vulnerability management with CRUD operations, severity tracking, status workflow, and statistics - πŸ“‹ Batch task management: create task queues, add multiple tasks, and execute them sequentially - 🎭 Role-based testing: predefined security testing roles (Penetration Testing, CTF, Web App Scanning, etc.) with custom prompts and tool restrictions - 🧩 **Agent orchestration (CloudWeGo Eino)**: **single-agent** via **`/api/eino-agent/stream`** (Eino ADK `ChatModelAgent`); **multi-agent** via **`/api/multi-agent/stream`** with **`deep`** (coordinator + `task` sub-agents), **`plan_execute`**, or **`supervisor`** (`orchestration` in the request body). ADK **summarization** compresses long contexts; pre-compaction **transcripts** land at `data/conversation_artifacts//summarization/transcript.txt` (full user/assistant/tool turns; static system omitted). Markdown under `agents/`: `orchestrator.md`, `orchestrator-plan-execute.md`, `orchestrator-supervisor.md`, plus sub-agent `*.md` (see [Multi-agent doc](docs/MULTI_AGENT_EINO.md)) - πŸ–ΌοΈ **Vision analysis (`analyze_image`)**: separate VL model (e.g. `qwen-vl-max`) via MCP for local screenshots, captchas, and UI; image bytes stay out of agent history (text summaries only). Configure `vision` in `config.yaml`; see [docs/VISION.md](docs/VISION.md) - 🎯 **Skills (refactored for Eino)**: packs under `skills_dir` follow **Agent Skills** layout (`SKILL.md` + optional files); **multi-agent** sessions use the official Eino ADK **`skill`** tool for **progressive disclosure** (load by name), with optional **host filesystem / shell** via `multi_agent.eino_skills`; optional **`eino_middleware`** adds patchtoolcalls, tool_search, **plantask** (`TaskCreate` / `TaskList` boards under `skills_dir/.eino/plantask/`), reduction, file **checkpoints** (`checkpoint_dir`), ChatModel **retries**, session **output key**, and Deep tuningβ€”20+ sample domains (SQLi, XSS, API security, …) ship under `skills/` - πŸ“± **Chatbot**: DingTalk and Lark (Feishu) long-lived connections so you can talk to CyberStrikeAI from mobile (see [Robot / Chatbot guide](docs/robot_en.md) for setup and commands) - πŸ§‘β€βš–οΈ **Human-in-the-loop (HITL)**: Chat sidebar to set approval mode and tool allowlists (listed tools skip approval); global list in `config.yaml` under `hitl.tool_whitelist`; **Apply** can merge new tools into the file and update the running server without restart; dedicated **HITL** page for pending approvals - 🐚 **WebShell management**: Add and manage WebShell connections (e.g. IceSword/AntSword compatible), use a virtual terminal for command execution, a built-in file manager for file operations, and an AI assistant tab that orchestrates tests and keeps per-connection conversation history; supports PHP, ASP, ASPX, JSP and custom shell types with configurable request method and command parameter. - πŸ“‘ **Built-in C2**: AI-oriented lightweight command-and-controlβ€”**listeners** (TCP reverse, HTTP/HTTPS beacon, WebSocket), **encrypted** beacon channel, **session** and **task** queues with persistence, **payload** helpers (one-liner / build / download), **SSE** live events, REST under `/api/c2/*`, plus unified MCP tools (`c2_listener`, `c2_session`, **`c2_task`**, `c2_task_manage`, `c2_payload`, `c2_event`, `c2_profile`, `c2_file`); optional **HITL** approval for sensitive operations and OPSEC-style controls (e.g. command deny rules). **Authorized testing only.** ## 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` ## 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 - **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 ## Basic Usage ### Quick Start (One-Command Deployment) **Prerequisites:** - Go 1.21+ ([Install](https://go.dev/dl/)) - Python 3.10+ ([Install](https://www.python.org/downloads/)) **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: - βœ… Check and validate Go & Python environments - βœ… Create Python virtual environment - βœ… Install Python dependencies - βœ… Download Go dependencies - βœ… Build the project - βœ… Start the server **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 OpenAI-compatible API** (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 `Settings` β†’ Fill in your API credentials: ```yaml openai: api_key: "sk-your-key" base_url: "https://api.openai.com/v1" # or https://api.deepseek.com/v1 model: "gpt-4o" # or deepseek-chat, claude-3-opus, etc. ``` - Or edit `config.yaml` directly before launching 2. **Login** - Use the auto-generated password shown in the console (or set `auth.password` in `config.yaml`) 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 portβ€”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. ### Version Update (No Breaking Changes) **CyberStrikeAI one-click upgrade (recommended):** 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`. ⚠️ **Note:** This procedure only applies to version updates without compatibility or breaking changes. If a release includes compatibility changes, this method may not apply. **Examples:** No breaking changes β€” e.g. v1.3.1 β†’ v1.3.2; with breaking changes β€” e.g. v1.3.1 β†’ v1.4.0. The project follows [Semantic Versioning](https://semver.org/) (SemVer): when only the patch version (third number) changes, this upgrade path is usually safe; when the minor or major version changes, config, data, or APIs may have changed β€” check the release notes before using this method. ### Core Workflows - **Conversation testing** – Natural-language prompts trigger toolchains with streaming SSE output. - **Single vs multi-agent** – Chat UI switches between **Eino single-agent** (`/api/eino-agent/stream`) and **multi-agent** (`/api/multi-agent/stream` with `orchestration`: `deep` | `plan_execute` | `supervisor`). Multi mode requires `multi_agent.enabled: true`. MCP tools are bridged the same way for both paths. - **Role-based testing** – Select from predefined security testing roles (Penetration Testing, CTF, Web App Scanning, API Security Testing, etc.) to customize AI behavior and tool availability. Each role applies custom system prompts and can restrict available tools for focused testing scenarios. - **Tool monitor** – Inspect running jobs, execution logs, and large-result attachments. - **History & audit** – Every conversation and tool invocation is stored in SQLite with replay. - **Conversation groups** – Organize conversations into groups, pin important groups, rename or delete groups via context menu. - **Vulnerability management** – Create, update, and track vulnerabilities discovered during testing. Filter by severity (critical/high/medium/low/info), status (open/confirmed/fixed/false_positive), and conversation. View statistics and export findings. - **Batch task management** – Create task queues with multiple tasks, add or edit tasks before execution, and run them sequentially. Each task executes as a separate conversation, with status tracking (pending/running/completed/failed/cancelled) and full execution history. - **WebShell management** – Add and manage WebShell connections (PHP/ASP/ASPX/JSP or custom). Use the virtual terminal to run commands, the file manager to list, read, edit, upload, and delete files, and the AI assistant tab to drive scripted tests with per-connection conversation history. Connections are stored in SQLite; supports GET/POST and configurable command parameter (e.g. IceSword/AntSword style). - **Built-in C2** – Create/start **listeners**, generate **payloads**, track **sessions**, enqueue **tasks**, and subscribe to **events** (SSE) from the Web UI or `/api/c2/*`. Agents and external clients use the C2 MCP tool family (including **`c2_task`**); when HITL is enabled, high-risk tasks can require human approval. Intended **only** for systems you are explicitly authorized to test. - **Settings** – Tweak provider keys, MCP enablement, tool toggles, and agent iteration limits. - **Human-in-the-loop (HITL)** – Sidebar sets mode and allowlisted tools (comma- or newline-separated); global list lives in `config.yaml` under `hitl.tool_whitelist`. **Apply** updates browser/server and can merge new tools into the file (**no restart**). **New chat** keeps sidebar choices; **HITL** nav shows pending approvals. Removing a tool in the sidebar does not remove it from the global list in `config.yaml`β€”edit the file if needed. ### Built-in Safeguards - Required-field validation prevents accidental blank API credentials. - Auto-generated strong passwords when `auth.password` is empty. - Unified auth middleware for every web/API call (Bearer token flow). - Timeout and sandbox guards per tool, plus structured logging for triage. ## Advanced Usage ### Role-Based Testing - **Predefined roles** – System includes 12+ predefined security testing roles (Penetration Testing, CTF, Web App Scanning, API Security Testing, Binary Analysis, Cloud Security Audit, etc.) in the `roles/` directory. - **Custom prompts** – Each role can define a `user_prompt` that prepends to user messages, guiding the AI to adopt specialized testing methodologies and focus areas. - **Tool restrictions** – Roles can specify a `tools` list to limit available tools, ensuring focused testing workflows (e.g., CTF role restricts to CTF-specific utilities). - **Skills** – Skill packs live under `skills_dir` and load via the Eino ADK **`skill`** tool (**progressive disclosure**) in both **single- and multi-agent** sessions when **`multi_agent.eino_skills`** is enabled. Optional host **read_file / glob / grep / write / edit / execute** and **`eino_middleware`** (tool_search, plantask, reduction, checkpoints, summarization transcripts, etc.) apply per modeβ€”see docs. - **Easy role creation** – Create custom roles by adding YAML files to the `roles/` directory. Each role defines `name`, `description`, `user_prompt`, `icon`, `tools`, and `enabled` fields. - **Web UI integration** – Select roles from a dropdown in the chat interface. Role selection affects both AI behavior and available tool suggestions. **Creating a custom role (example):** 1. Create a YAML file in `roles/` (e.g., `roles/custom-role.yaml`): ```yaml name: Custom Role description: Specialized testing scenario user_prompt: You are a specialized security tester focusing on API security... icon: "\U0001F4E1" tools: - api-fuzzer - arjun - graphql-scanner enabled: true ``` 2. Restart the server or reload configuration; the role appears in the role selector dropdown. ### Multi-Agent Mode (Eino: Deep, Plan-Execute, Supervisor) - **What it is** – Multi-agent orchestration on CloudWeGo **Eino** `adk/prebuilt` (alongside **Eino single-agent** on `/api/eino-agent*`): **`deep`** β€” coordinator + **`task`** sub-agents; **`plan_execute`** β€” planner / executor / replanner; **`supervisor`** β€” orchestrator with **`transfer`** / **`exit`**. Client sends **`orchestration`**: `deep` | `plan_execute` | `supervisor` (default `deep`). - **Markdown agents** – Under `agents_dir` (default `agents/`): - **Deep orchestrator**: `orchestrator.md` *or* one `.md` with `kind: orchestrator`. Body or `multi_agent.orchestrator_instruction`, then Eino defaults. - **Plan-Execute orchestrator**: fixed name **`orchestrator-plan-execute.md`** (plus optional `orchestrator_instruction_plan_execute` in YAML). - **Supervisor orchestrator**: fixed name **`orchestrator-supervisor.md`** (plus optional `orchestrator_instruction_supervisor`); requires at least one sub-agent. - **Sub-agents** (for **deep** / **supervisor**): other `*.md` files (YAML front matter + body). Not used as **`task`** targets if marked orchestrator-only. - **Management** – Web UI: **Agents β†’ Agent management**; API `/api/multi-agent/markdown-agents`. - **Config** – `multi_agent` in `config.yaml`: `enabled`, `robot_default_agent_mode`, `batch_use_multi_agent`, `max_iteration`, `plan_execute_loop_max_iterations`, per-mode orchestrator instruction fields, optional YAML `sub_agents` merged with disk (`id` clash β†’ Markdown wins), **`eino_skills`**, **`eino_middleware`** (optional ADK middleware and Deep/Supervisor tuning). - **Resilience & long runs** – `checkpoint_dir` enables ADK **resume** after process crashes (distinct from trace-based β€œinterrupt & continue”). `deep_model_retry_max_retries` retries transient LLM API failures within a single call. **Summarization** writes a filtered **transcript** when compression fires; the summary message includes the path so the model can `read_file` for scan output and other pre-compaction details. - **Details** – **[docs/MULTI_AGENT_EINO.md](docs/MULTI_AGENT_EINO.md)** (streaming, robots, batch, middleware caveats). ### Skills System (Agent Skills + Eino) - **Layout** – Each skill is a directory with **required** `SKILL.md` only ([Agent Skills](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview)): YAML front matter **only** `name` and `description`, plus Markdown body. Optional sibling files (`FORMS.md`, `REFERENCE.md`, `scripts/*`, …). **No** `SKILL.yaml` (not part of Claude or Eino specs); sections/scripts/progressive behavior are **derived at runtime** from Markdown and the filesystem. - **Runtime refactor** – **`skills_dir`** is the single root for packs. **Multi-agent** loads them through Eino’s official **`skill`** middleware (**progressive disclosure**: model calls `skill` with a pack **name** instead of receiving full SKILL text up front). Configure via **`multi_agent.eino_skills`**: `disable`, `filesystem_tools` (host read/glob/grep/write/edit/execute), `skill_tool_name`. - **Eino / RAG** – Packages are also split into `schema.Document` chunks for `FilesystemSkillsRetriever` (`skills.AsEinoRetriever()`) in **compose** graphs (e.g. knowledge/indexing pipelines). - **HTTP API** – `/api/skills` listing and `depth` (`summary` | `full`), `section`, and `resource_path` remain for the web UI and ops; **model-side** skill loading in multi-agent uses the **`skill`** tool, not MCP. - **Optional `eino_middleware`** – e.g. `tool_search` (dynamic MCP tool list), `patch_tool_calls`, **`plantask`** (Eino `TaskCreate` / `TaskGet` / `TaskUpdate` / `TaskList`; JSON under `skills_dir/.eino/plantask//`; Eino clears task files when **all** tasks are marked completed), `reduction`, **`checkpoint_dir`** (`data/eino-checkpoints/`), **`deep_model_retry_max_retries`**, **`deep_output_key`**, task-tool description prefixβ€”see `config.yaml` and `internal/config/config.go`. - **Shipped demo** – `skills/cyberstrike-eino-demo/`; see `skills/README.md`. **Creating a skill:** 1. `mkdir skills/` and add standard `SKILL.md` (+ any optional files), or drop in an open-source skill folder as-is. 2. Use **multi-agent** with **`multi_agent.eino_skills`** enabled so the model can call the **`skill`** tool with that pack **name**. ### Tool Orchestration & Extensions - **YAML recipes** in `tools/*.yaml` describe commands, arguments, prompts, and metadata. - **Directory hot-reload** – pointing `security.tools_dir` to a folder is usually enough; inline definitions in `config.yaml` remain supported for quick experiments. - **Large tool outputs** – outputs beyond `reduction_max_length_for_trunc` are summarized via Eino reduction with full content persisted under `tmp/reduction/`; use `read_file` on the path in ``. - **Result compression** – multi-megabyte logs can be summarized or losslessly compressed before persisting to keep SQLite lean. **Creating a custom tool (typical flow)** 1. Copy an existing YAML file from `tools/` (for example `tools/sample.yaml`). 2. Update `name`, `command`, `args`, and `short_description`. 3. Describe positional or flag parameters in `parameters[]` so the agent knows how to build CLI arguments. 4. Provide a longer `description`/`notes` block if the agent needs extra context or post-processing tips. 5. Restart the server or reload configuration; the new tool becomes available immediately and can be enabled/disabled from the Settings panel. ### Attack-Chain Intelligence - AI parses each conversation to assemble targets, tools, vulnerabilities, and relationships. - The web UI renders the chain as an interactive graph with severity scoring and step replay. - Export the chain or raw findings to external reporting pipelines. ### WebShell Management - **Connections** – From the Web UI, go to **WebShell Management** to add, edit, or delete WebShell connections. Each connection stores: Shell URL, password/key, shell type (PHP, ASP, ASPX, JSP, Custom), request method (GET/POST), command parameter name (default `cmd`), and an optional remark; all records persist in SQLite and are compatible with common clients such as IceSword and AntSword. - **Virtual terminal** – After selecting a connection, use the **Virtual terminal** tab to run arbitrary commands with history and quick commands (whoami/id/ls/pwd etc.). Output is streamed in the browser, and Ctrl+L clears the screen. - **File manager** – Use the **File manager** tab to list directories, read or edit files, delete files, create folders/files, upload files (including chunked uploads for large files), rename paths, and download selected files. Path navigation supports breadcrumbs, parent directory jumps, and name filtering. - **AI assistant** – Use the **AI assistant** tab to chat with an agent that understands the current WebShell connection, automatically runs tools and shell commands, and maintains per-connection conversation history with a sidebar of previous sessions. - **Connectivity test** – Use **Test connectivity** to verify that the shell URL, password, and command parameter are correct before running commands (sends a lightweight `echo 1` check). - **Persistence** – All WebShell connections and AI conversations are stored in SQLite (same database as conversations), so they persist across restarts. ### Built-in C2 (Command & Control) - **What it is** – A first-party, **AI-native** C2 stack: listeners accept implants (beacons), the server stores **sessions** and **tasks** in SQLite, pushes updates over an **event bus** (including **SSE**), and exposes everything through authenticated **REST** plus MCP. - **Listeners & transports** – `tcp_reverse`, `http_beacon`, `https_beacon`, and `websocket`; per-listener crypto keys; running listeners can be **restored after restart** when marked running in the database. - **Agent integration** – MCP exposes a small **C2 tool family** (listeners, sessions, **`c2_task`**, task management, payloads, events, profiles, files) so the same agent loop can orchestrate C2 alongside other tools; dangerous task types can go through the existing **HITL** bridge when your session policy requires it. - **Safety** – Use **only** in lab or **fully authorized** engagements; combine network isolation, strong auth, and HITL/allowlists as your policy demands. ### MCP Everywhere - **Web mode** – ships with HTTP MCP server automatically consumed by the UI. - **MCP stdio mode** – `go run cmd/mcp-stdio/main.go` exposes the agent to Cursor/CLI. - **External MCP federation** – register third-party MCP servers (HTTP, stdio, or SSE) from the UI, toggle them per engagement, and monitor their health and call volume in real time. - **Optional MCP servers** – the [`mcp-servers/`](mcp-servers/README.md) directory provides standalone MCPs (e.g. reverse shell). They speak standard MCP over stdio and work with CyberStrikeAI (Settings β†’ External MCP), Cursor, VS Code, and other MCP clients. #### MCP stdio quick start 1. **Build the binary** (run from the project root): ```bash go build -o cyberstrike-ai-mcp cmd/mcp-stdio/main.go ``` 2. **Wire it up in Cursor** Open `Settings β†’ Tools & MCP β†’ Add Custom MCP`, pick **Command**, then point to the compiled binary and your config: ```json { "mcpServers": { "cyberstrike-ai": { "command": "/absolute/path/to/cyberstrike-ai-mcp", "args": [ "--config", "/absolute/path/to/config.yaml" ] } } } ``` Replace the paths with your local locations; Cursor will launch the stdio server automatically. #### MCP HTTP quick start (Cursor / Claude Code) The HTTP MCP server runs on a separate port (default `8081`) and supports **header-based authentication** so only clients that send the correct header can call tools. 1. **Enable MCP in config** – In `config.yaml` set `mcp.enabled: true` and optionally `mcp.host` / `mcp.port`. For auth (recommended if the port is reachable from the network), set: - `mcp.auth_header` – header name (e.g. `X-MCP-Token`); - `mcp.auth_header_value` – secret value. **Leave it empty** if you want the server to **auto-generate** a random token on first start and write it back to the config. 2. **Start the service** – Run `./run.sh` or `go run cmd/server/main.go`. The MCP endpoint is `http://:/mcp` (e.g. `http://localhost:8081/mcp`). 3. **Copy the JSON from the terminal** – When MCP is enabled, the server prints a **ready-to-paste** JSON block. If `auth_header_value` was empty, it will have been generated and saved; the printed JSON includes the URL and headers. 4. **Use in Cursor or Claude Code**: - **Cursor**: Paste the block into `~/.cursor/mcp.json` (or your project’s `.cursor/mcp.json`) under `mcpServers`, or merge it into your existing `mcpServers`. - **Claude Code**: Paste into `.mcp.json` or `~/.claude.json` under `mcpServers`. Example of what the terminal prints (with auth enabled): ```json { "mcpServers": { "cyberstrike-ai": { "url": "http://localhost:8081/mcp", "headers": { "X-MCP-Token": "" }, "type": "http" } } } ``` If you do not set `auth_header` / `auth_header_value`, the endpoint accepts requests without authentication (suitable only for localhost or trusted networks). #### External MCP federation (HTTP/stdio/SSE) CyberStrikeAI supports connecting to external MCP servers via three transport modes: - **HTTP mode** – traditional request/response over HTTP POST - **stdio mode** – process-based communication via standard input/output - **SSE mode** – Server-Sent Events for real-time streaming communication To add an external MCP server: 1. Open the Web UI and navigate to **Settings β†’ External MCP**. 2. Click **Add External MCP** and provide the configuration in JSON format: **HTTP mode example:** ```json { "my-http-mcp": { "transport": "http", "url": "http://127.0.0.1:8081/mcp", "description": "HTTP MCP server", "timeout": 30 } } ``` **stdio mode example:** ```json { "my-stdio-mcp": { "command": "python3", "args": ["/path/to/mcp-server.py"], "description": "stdio MCP server", "timeout": 30 } } ``` **SSE mode example:** ```json { "my-sse-mcp": { "transport": "sse", "url": "http://127.0.0.1:8082/sse", "description": "SSE MCP server", "timeout": 30 } } ``` 3. Click **Save** and then **Start** to connect to the server. 4. Monitor the connection status, tool count, and health in real time. **SSE mode benefits:** - Real-time bidirectional communication via Server-Sent Events - Suitable for scenarios requiring continuous data streaming - Lower latency for push-based notifications A test SSE MCP server is available at `cmd/test-sse-mcp-server/` for validation purposes. ### Knowledge Base - **Vector search** – AI agent can automatically search the knowledge base for relevant security knowledge during conversations using the `search_knowledge_base` tool. - **Vector retrieval** – cosine similarity over stored embeddings, aligned with Eino `retriever.Retriever` usage. - **Auto-indexing** – scans the `knowledge_base/` directory for Markdown files and automatically indexes them with embeddings. - **Web management** – create, update, delete knowledge items through the web UI, with category-based organization. - **Retrieval logs** – tracks all knowledge retrieval operations for audit and debugging. **Quick Start (Using Pre-built Knowledge Base):** 1. **Download the knowledge database** – Download the pre-built knowledge database file from [GitHub Releases](https://github.com/Ed1s0nZ/CyberStrikeAI/releases). 2. **Extract and place** – Extract the downloaded knowledge database file (`knowledge.db`) and place it in the project's `data/` directory. 3. **Restart the service** – Restart the CyberStrikeAI service, and the knowledge base will be ready to use immediately without rebuilding the index. **Setting up the knowledge base:** 1. **Enable in config** – set `knowledge.enabled: true` in `config.yaml`: ```yaml knowledge: enabled: true base_path: knowledge_base embedding: provider: openai model: text-embedding-v4 base_url: "https://api.openai.com/v1" # or your embedding API api_key: "sk-xxx" retrieval: top_k: 5 similarity_threshold: 0.7 ``` 2. **Add knowledge files** – place Markdown files in `knowledge_base/` directory, organized by category (e.g., `knowledge_base/SQL Injection/README.md`). 3. **Scan and index** – use the web UI to scan the knowledge base directory, which will automatically import files and build vector embeddings. 4. **Use in conversations** – the AI agent will automatically use `search_knowledge_base` when it needs security knowledge. You can also explicitly ask: "Search the knowledge base for SQL injection techniques". **Knowledge base structure:** - Files are organized by category (directory name becomes the category). - Each Markdown file becomes a knowledge item with automatic chunking for vector search. - The system supports incremental updates – modified files are re-indexed automatically. ### Automation Hooks - **REST APIs** – everything the UI uses (auth, conversations, tool runs, monitor, vulnerabilities, roles) is available over JSON. - **Multi-agent APIs** – `POST /api/multi-agent/stream` (SSE, when enabled), `POST /api/multi-agent` (non-streaming), Markdown agents under `/api/multi-agent/markdown-agents` (list/get/create/update/delete). - **Role APIs** – manage security testing roles via `/api/roles` endpoints: `GET /api/roles` (list all roles), `GET /api/roles/:name` (get role), `POST /api/roles` (create role), `PUT /api/roles/:name` (update role), `DELETE /api/roles/:name` (delete role). Roles are stored as YAML files in the `roles/` directory and support hot-reload. - **Vulnerability APIs** – manage vulnerabilities via `/api/vulnerabilities` endpoints: `GET /api/vulnerabilities` (list with filters), `POST /api/vulnerabilities` (create), `GET /api/vulnerabilities/:id` (get), `PUT /api/vulnerabilities/:id` (update), `DELETE /api/vulnerabilities/:id` (delete), `GET /api/vulnerabilities/stats` (statistics). - **Batch Task APIs** – manage batch task queues via `/api/batch-tasks` endpoints: `POST /api/batch-tasks` (create queue), `GET /api/batch-tasks` (list queues), `GET /api/batch-tasks/:queueId` (get queue), `POST /api/batch-tasks/:queueId/start` (start execution), `POST /api/batch-tasks/:queueId/cancel` (cancel), `DELETE /api/batch-tasks/:queueId` (delete), `POST /api/batch-tasks/:queueId/tasks` (add task), `PUT /api/batch-tasks/:queueId/tasks/:taskId` (update task), `DELETE /api/batch-tasks/:queueId/tasks/:taskId` (delete task). Tasks execute sequentially, each creating a separate conversation with full status tracking. - **WebShell APIs** – manage WebShell connections and execute commands via `/api/webshell/connections` (GET list, POST create, PUT update, DELETE delete) and `/api/webshell/exec` (command execution), `/api/webshell/fileop` (list/read/write/delete files). - **C2 APIs** – manage listeners, sessions, tasks, payloads, files, and events under `/api/c2/*` (e.g. listeners CRUD/start/stop, session sleep, task create/cancel/wait, payload build/download, event stream). - **Task control** – pause/resume/stop long scans, re-run steps with new params, or stream transcripts. - **Audit & security** – rotate passwords via `/api/auth/change-password`, enforce short-lived sessions, and restrict MCP ports at the network layer when exposing the service. ## Configuration Reference ```yaml auth: password: "change-me" session_duration_hours: 12 server: host: "0.0.0.0" port: 8080 log: level: "info" output: "stdout" mcp: enabled: true host: "0.0.0.0" port: 8081 auth_header: "X-MCP-Token" # optional; leave empty for no auth auth_header_value: "" # optional; leave empty to auto-generate on first start openai: api_key: "sk-xxx" base_url: "https://api.deepseek.com/v1" model: "deepseek-chat" database: path: "data/conversations.db" knowledge_db_path: "data/knowledge.db" # Optional: separate DB for knowledge base security: tools_dir: "tools" knowledge: enabled: false # Enable knowledge base feature base_path: "knowledge_base" # Path to knowledge base directory embedding: provider: "openai" # Embedding provider (currently only "openai") model: "text-embedding-v4" # Embedding model name base_url: "" # Leave empty to use OpenAI base_url api_key: "" # Leave empty to use OpenAI api_key retrieval: top_k: 5 # Number of top results to return similarity_threshold: 0.7 # Minimum cosine similarity (0-1) roles_dir: "roles" # Role configuration directory (relative to config file) skills_dir: "skills" # Skills directory (relative to config file) agents_dir: "agents" # Multi-agent Markdown definitions (orchestrator + sub-agents) multi_agent: enabled: false default_mode: "eino_single" # eino_single | multi (UI default when multi-agent is enabled) robot_default_agent_mode: eino_single batch_use_multi_agent: false orchestrator_instruction: "" # Deep; used when orchestrator.md body is empty # orchestrator_instruction_plan_execute / orchestrator_instruction_supervisor optional # eino_skills: { disable: false, filesystem_tools: true, skill_tool_name: skill } # eino_middleware: plantask_enable, checkpoint_dir, deep_model_retry_max_retries, deep_output_key, ... project: enabled: true # Enable project blackboard & fact MCP tools fact_index_max_runes: 65000 fact_summary_max_runes: 24000 default_inject_deprecated: false ``` ### Tool Definition Example (`tools/nmap.yaml`) ```yaml name: "nmap" command: "nmap" args: ["-sT", "-sV", "-sC"] enabled: true short_description: "Network mapping & service fingerprinting" parameters: - name: "target" type: "string" description: "IP or domain" required: true position: 0 - name: "ports" type: "string" flag: "-p" description: "Range, e.g. 1-1000" ``` ### Role Definition Example (`roles/penetration-testing.yaml`) ```yaml name: Penetration Testing description: Professional penetration testing expert for comprehensive security testing user_prompt: You are a professional cybersecurity penetration testing expert. Please use professional penetration testing methods and tools to conduct comprehensive security testing on targets, including but not limited to SQL injection, XSS, CSRF, file inclusion, command execution and other common vulnerabilities. icon: "\U0001F3AF" tools: - nmap - sqlmap - nuclei - burpsuite - metasploit - httpx - record_vulnerability - list_knowledge_risk_types - search_knowledge_base enabled: true ``` ## Related documentation - [Multi-agent mode (Eino)](docs/MULTI_AGENT_EINO.md): **Deep**, **Plan-Execute**, **Supervisor**, `agents/*.md`, `eino_skills` / `eino_middleware`, APIs, and chat/stream behavior. - [Robot / Chatbot guide (DingTalk & Lark)](docs/robot_en.md): Full setup, commands, and troubleshooting for using CyberStrikeAI from DingTalk or Lark on your phone. **Follow this doc to avoid common pitfalls.** ## Project Layout ``` CyberStrikeAI/ β”œβ”€β”€ cmd/ # Server, MCP stdio entrypoints, tooling β”œβ”€β”€ internal/ # Agent, MCP core, handlers, C2 (`internal/c2`), security executor β”œβ”€β”€ web/ # Static SPA + templates β”œβ”€β”€ tools/ # YAML tool recipes (100+ examples provided) β”œβ”€β”€ roles/ # Role configurations (12+ predefined security testing roles) β”œβ”€β”€ skills/ # Agent Skills dirs (SKILL.md + optional files; demo: cyberstrike-eino-demo) β”œβ”€β”€ agents/ # Multi-agent Markdown (orchestrator.md + sub-agent *.md) β”œβ”€β”€ docs/ # Documentation (e.g. robot/chatbot guide, MULTI_AGENT_EINO.md) β”œβ”€β”€ images/ # Docs screenshots & diagrams β”œβ”€β”€ config.yaml # Runtime configuration β”œβ”€β”€ 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](https://github.com/knownsec/404StarLink) ## TCH Top-Ranked Intelligent Pentest Project ## Stargazers over time ![Stargazers over time](https://starchart.cc/Ed1s0nZ/CyberStrikeAI.svg) --- ## License CyberStrikeAI is licensed under the Apache License 2.0. See the [LICENSE](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. --- Need help or want to contribute? Open an issue or PRβ€”community tooling additions are welcome!