mcpsec 2.4.1

Security scanner and protocol fuzzer for MCP (Model Context Protocol) servers. Found and reported vulnerabilities in official Anthropic and GitHub MCP implementations.

mcpsec

Security scanner and protocol fuzzer for MCP servers

Installation • Quick Start • Scanners • Fuzzing

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Why mcpsec?

MCP (Model Context Protocol) connects AI agents to external tools. Claude Desktop, Cursor, VS Code Copilot, and every major AI IDE uses it. Security is often an afterthought.

Most MCP security tools do static analysis. mcpsec connects to live servers and proves exploitation.

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Installation

pip install mcpsec

For AI-powered features:

pip install mcpsec[ai]

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Quick Start

Runtime Scanning

# Scan via stdio
mcpsec scan --stdio "npx @modelcontextprotocol/server-filesystem /tmp"

# Scan via HTTP with auth
mcpsec scan --http http://localhost:8080/mcp -H "Authorization: Bearer TOKEN"

# Enumerate attack surface
mcpsec info --stdio "python my_server.py"

Protocol Fuzzing

# Standard fuzzing (~200 cases)
mcpsec fuzz --stdio "python my_server.py"

# High intensity (~800 cases)
mcpsec fuzz --stdio "python my_server.py" --intensity high

# AI-powered payload generation
mcpsec fuzz --stdio "python my_server.py" --ai

Static Analysis

# Local source
mcpsec audit --path ./my-mcp-server

# GitHub repository
mcpsec audit --github https://github.com/user/mcp-server

# With AI validation
mcpsec audit --github https://github.com/user/mcp-server --ai

Advanced

# SQL Injection scanner with DB fingerprinting
mcpsec sql --stdio "npx @benborla29/mcp-server-mysql" --fingerprint

# Dangerous tool chain detection
mcpsec chains --stdio "npx @example/complex-server"

# Interactive exploitation REPL
mcpsec exploit --stdio "npx vulnerable-server"

# Rogue server for client-side testing
mcpsec rogue-server --port 9999 --attack all

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Scanners

Scanner	Description
prompt-injection	Hidden instructions in tool descriptions
command-injection	OS command injection with 138 payloads
path-traversal	Directory traversal with 104 payloads
ssrf	Server-Side Request Forgery with 81 payloads
sql	SQL Injection (Error, Time, Boolean, Stacked)
auth-audit	Missing authentication, dangerous tool combos
description-prompt-injection	LLM manipulation via descriptions
resource-ssrf	SSRF via MCP resource URIs
capability-escalation	Undeclared capability abuse
chains	Dangerous tool combination detection

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Fuzz Generators

22 generators organized by intensity level:

Low (~65 cases): malformed_json, protocol_violation, type_confusion, boundary_testing, unicode_attacks

Medium (~200 cases): + session_attacks, encoding_attacks, integer_boundaries

High (~800 cases): + injection_payloads, method_mutations, param_mutations, timing_attacks, header_mutations, json_edge_cases, protocol_state, protocol_state_machine, id_confusion, concurrency_attacks, regex_dos, deserialization

Insane (~1500+ cases): + resource_exhaustion, memory_exhaustion_v2

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Static Analysis (149 Semgrep Rules)

24 rule files covering:

• Injection: Command injection (JS, Go, Rust, .NET, Python, Python async), SQL injection (all drivers + ORM bypass), path traversal
• Network: SSRF patterns, resource URI issues
• Secrets: AWS keys, API tokens, JWT secrets, connection strings, private keys
• MCP-Specific: Dangerous tool names, empty schemas, input reflection, missing auth
• Code Quality: Security TODOs, empty catches, TLS disabled, CORS *, ReDoS patterns

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How It Works

┌─────────┐     MCP Protocol      ┌────────────┐
│ mcpsec  │ ◄──── JSON-RPC ────►  │   Target   │
│         │    (stdio / HTTP)     │   Server   │
└────┬────┘                       └────────────┘
     │
     ├── Connect & enumerate attack surface
     ├── Run 10+ security scanners  
     ├── Generate 800+ fuzz cases
     ├── Execute AI-powered payload mutations
     └── Report findings with PoC evidence

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Configuration

AI Provider Setup

mcpsec setup

Supports: OpenAI, Anthropic, Google, Groq, DeepSeek, Ollama

Output Formats

# JSON
mcpsec scan --stdio "server" --output results.json

# SARIF 2.1.0 (GitHub/GitLab/Azure DevOps CI/CD)
mcpsec fuzz --stdio "server" --output results.sarif

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Changelog

v2.4.0 (2026-02-28)

• SAST Rules Expansion: 87 new Semgrep rules → 149 total across 24 rule files
• Broad patterns for command injection, path traversal, SQL injection, SSRF, deserialization
• Secrets detection: AWS keys, AI API keys, GitHub/Slack tokens, JWT secrets
• MCP-specific rules: dangerous tool names, empty schemas, error leaks, input reflection
• Code smells: security TODOs, empty catches, TLS disabled, CORS *, ReDoS patterns

v2.3.0 (2026-02-28)

• Scanner Nuclear Expansion: Command injection (138), path traversal (104), SSRF (81) payloads
• Encoding bypasses, protocol smuggling, shell-specific evasion
• 5 new fuzz generators: integer boundaries, concurrency, memory exhaustion, regex DoS, deserialization
• SDK-specific Semgrep rules for Go, Rust, Python async, .NET

v2.2.0 (2026-02-28)

• SARIF 2.1.0 Output for CI/CD integration
• CWE mapping and severity scoring
• Audit report export with --output and --format flags

v2.1.0 (2026-02-27)

• AI Exploitation Assistant: select, run, next, verdict, auto REPL commands
• Expert controls: edit, aggressive, hint for complex bypasses
• AI learns from manual call commands and response history

v2.0.3 (2026-02-26)

• MCP Repeater: Interactive REPL for manual/semi-auto finding validation
• AI payload engine with context-aware recommendations
• Exploit playbooks for SQLi, RCE, SSRF, path traversal
• Automated evidence capture and PoC generation

Earlier versions

v2.0.2 (2026-02-26)

• Tool chain analysis for dangerous combinations
• Cross-platform Windows support improvements

v2.0.1 (2026-02-25)

• Advanced SQL scanner with modular detection
• DB fingerprinting for MySQL, Postgres, MSSQL, SQLite

v2.0.0 (2026-02-24)

• Fuzzing engine v2 with chained state-machine exploration
• AI-powered validation of security findings

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Disclaimer

For authorized security testing only. Only scan servers you own or have explicit permission to test.

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License

MIT

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Built by Manthan Ghasadiya