Cursor Security Rules
This repository contains Cursor Security Rules designed to improve the security of both development workflows and AI agent usage within the Cursor environment. These rules aim to enforce safe coding practices, control sensitive operations, and reduce risk in AI-assisted development.
At a Glance Technical Specifications
01 // How It Works & Runtime Architecture
By leveraging Python SDK / OpenAI API, the application isolates runtime dependencies while maintaining low-latency execution traces across multi-step LLM operations.
02 // Real-World Workflows & Use Cases
Deterministic AST code analysis, symbol indexing, and cross-file reference discovery
Autonomous test generation, test execution feedback loops, and automated patch creation
Safe repository refactoring and automated codebase modernization without context leakage
03 // Prerequisites & Compatibility
04 // Client Configuration (claude_desktop_config.json)
{
"mcpServers": {
"cursor-security-rules": {
"command": "python",
"args": [
"-m",
"cursor_security_rules"
]
}
}
}
Paste into your client configuration file (e.g. ~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%/Claude/claude_desktop_config.json on Windows).
05 // Step-by-Step Installation
Verified Process- 1
Clone matank001/cursor-security-rules from GitHub
- 2
Install dependencies with pip install -r requirements.txt (or uv sync)
- 3
Copy .env.example to .env and add your API keys
- 4
Run the skill server and connect your AI client via stdio or HTTP
06 // Execution Boundaries & Security Safeguards
Keeps heavy parsing and raw file structures external to the LLM. Only sanitized excerpts and structured returns are injected into agent memory turns.
Enforce explicit directory allowlists and permission scopes in client configuration to ensure autonomous tool calls never breach system boundaries.
Executes in an isolated local child process communicating strictly over JSON-RPC via stdio with explicit process timeouts.
07 // Frequently Asked Questions
FAQ Schema IncludedWhat is Cursor Security Rules and how does it empower AI agents?
Cursor Security Rules is an open-source coding capability designed for AI clients and autonomous agents. This repository contains Cursor Security Rules designed to improve the security of both development workflows and AI agent usage within the Cursor environment. These rules aim to enforce safe coding practices, control sensitive operations, and reduce risk in AI-assisted development.
How do I install and configure Cursor Security Rules?
Follow the step-by-step installation: 1) Verify your runtime (Python 3.10+), 2) Add the configuration snippet into your AI client settings (e.g. claude_desktop_config.json), 3) Restart the client to initialize tool execution.
Which AI clients and developer harnesses support Cursor Security Rules?
Cursor Security Rules is compatible with all AI tools supporting tool-calling and the Model Context Protocol (MCP), including Claude Desktop, Cursor, Claude Code CLI, Windsurf, OpenCode, and custom agent runtimes.
What security boundaries and sandboxing safeguards does Cursor Security Rules enforce?
Cursor Security Rules executes locally with strict directory allowlists and permission scopes. Heavy parsing and raw file structures stay external to the LLM context window to prevent memory saturation and unauthorized access.
Is Cursor Security Rules free and open source?
Yes, Cursor Security Rules is published under the MIT open-source license. You can inspect the source code and contribute on GitHub at https://github.com/matank001/cursor-security-rules.
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