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An intentionally vulnerable case management system designed for security training that provides MCP tools for SOC analyst workflows like case handling and indic
An intentionally vulnerable case management system designed for security training that provides MCP tools for SOC analyst workflows like case handling and indicator search. It enables users to explore and demonstrate common security weaknesses such as prompt injection, SQL injection, and broken authorization in an MCP-integrated environment.
MIT License Python GitHub stars
ThreatByte-MCP is a deliberately vulnerable, MCP-based case management web app. It mirrors a realistic SOC analyst workflow with a server-rendered UI and a real MCP server. The MCP tools are intentionally vulnerable for training and demonstration.
[!NOTE] For educational use in controlled environments only.
ThreatByte-MCP is a split architecture:
The MCP server exposes JSON-RPC at POST http://localhost:5002/mcp (Streamable HTTP). The web UI calls the MCP server through a server-side proxy to keep auth consistent with the SOC session; the proxy streams agent responses to the browser via SSE. A sample mcp.json manifest is included at the repo root.
All direct MCP calls must include MCP-Protocol-Version: 2025-11-25 and Accept: application/json, text/event-stream.
Architecture (simplified):
Browser
|
v
+------------------+ X-TBMCP-Token + X-TBMCP-User +-------------------+
| SOC Web App | ---------------------------------------> | MCP Server |
| (Flask, :5001) | /mcp-proxy (server-side) | (FastMCP, :5002) |
+------------------+ +-------------------+
| |
v v
SQLite DB Tool registry
Agent + tool handlers
Architecture (detailed):
Browser (Analyst)
|
v
SOC Web App (Flask, :5001)
| - Auth session (cookie)
| - Dashboards, cases, notes, files UI
| - /mcp-proxy forwards JSON-RPC
|
+--> SQLite DB
| - users, cases, notes, files, indicators
|
+--> Uploads (app/uploads)
|
v
MCP Server (FastMCP, :5002)
| - /mcp JSON-RPC (Streamable HTTP)
| - X-TBMCP-Token + X-TBMCP-User headers
|
+--> Tool registry (mcp_tools)
| - schema-based tools (poisonable)
|
+--> Agent runtime
| - prompt builder (hardcoded tokens)
| - LLM API call
|
+--> Persistence
- agent_contexts (prompt store)
- agent_logs (full request/response)
The web app proxies MCP calls with these headers:
X-TBMCP-Token: shared secret from TBMCP_MCP_SERVER_TOKEN (configured on both servers).X-TBMCP-User: current user id from the authenticated SOC session.Direct MCP calls require the same headers.
Supported tools:
cases.createcases.listcases.list_allcases.getcases.renamecases.set_statuscases.deletenotes.createnotes.listnotes.updatenotes.deletefiles.upload (base64)files.listfiles.get (base64)files.read_pathindicators.searchagent.summarize_caseagent.run_tasktools.registry.listtools.builtin.listtools.registry.registertools.registry.deleteThe following weaknesses are intentionally present for teaching:
files.read_pathcd ThreatByte-MCP
python -m venv venv_threatbyte_mcp
source venv_threatbyte_mcp/bin/activate
pip install -r requirements.txt
python db/create_db_tables.py
python run_http_server.py
python run.py
Open: http://localhost:5001
MCP Server: http://localhost:5002/mcp
The repository includes a Dockerfile and startup script that initialize the DB and run both services in one container:
:5001:5002Build the image:
# Docker
docker build -t threatbyte-mcp .
# Podman
podman build -t threatbyte-mcp .
Run the container:
# Docker
docker run --rm -p 5001:5001 -p 5002:5002 threatbyte-mcp
# Podman
podman run --rm -p 5001:5001 -p 5002:5002 threatbyte-mcp
Run with optional environment variables:
# Docker
docker run --rm -p 5001:5001 -p 5002:5002 \
-e TBMCP_MCP_SERVER_TOKEN=tbmcp-mcp-token \
-e OPENAI_API_KEY=your_api_key \
-e TBMCP_OPENAI_MODEL=gpt-4o-mini \
threatbyte-mcp
# Podman
podman run --rm -p 5001:5001 -p 5002:5002 \
-e TBMCP_MCP_SERVER_TOKEN=tbmcp-mcp-token \
-e OPENAI_API_KEY=your_api_key \
-e TBMCP_OPENAI_MODEL=gpt-4o-mini \
threatbyte-mcp
Persist SQLite data between runs (optional):
# Docker
docker run --rm -p 5001:5001 -p 5002:5002 \
-v "$(pwd)/db:/app/db" \
-v "$(pwd)/app/uploads:/app/app/uploads" \
threatbyte-mcp
# Podman
podman run --rm -p 5001:5001 -p 5002:5002 \
-v "$(pwd)/db:/app/db:Z" \
-v "$(pwd)/app/uploads:/app/app/uploads:Z" \
threatbyte-mcp
python db/populate_db.py --users 8 --cases 20 --notes 40 --files 20
This creates random users, cases, notes, and file artifacts. All user passwords are Password123!.
The agent task endpoint requires a real LLM. Without an API key, the agent returns an error indicating it is unavailable.
Environment variables:
TBMCP_OPENAI_API_KEY or OPENAI_API_KEYTBMCP_OPENAI_MODEL (default: gpt-4o-mini)Keep API keys server-side only and never expose them in the browser.
The SOC web app proxies MCP calls to the MCP server using a shared token.
Environment variables:
TBMCP_MCP_SERVER_URL (default: http://localhost:5002/mcp)TBMCP_MCP_SERVER_TOKEN (shared secret between the SOC app and MCP server)http://localhost:5002/mcp (JSON-RPC). The UI calls them through /mcp-proxy.Добавь это в claude_desktop_config.json и перезапусти Claude Desktop.
{
"mcpServers": {
"threatbyte-mcp": {
"command": "npx",
"args": []
}
}
}Query your database in natural language
Read-only database access with schema inspection.
Interact with Redis key-value stores.
Database interaction and business intelligence capabilities.