π§ v2025.8.0.0 - OWASP LLM 2025 + CVE-2025-6514 Detection
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π§ AI Security Powerhouse Release
MEDUSA v2025.8.0.0 doubles down on AI security with OWASP Top 10 for LLM 2025 compliance, CVE-2025-6514 detection, and comprehensive documentation.
π What's New Since v2025.7
OWASP Top 10 for LLM Applications 2025
Updated OWASPLLMScanner to the November 2024 release of OWASP standards:
| Category | Status | Description |
|---|---|---|
| LLM07 | π NEW | System Prompt Leakage - credentials/secrets in prompts |
| LLM08 | π NEW | Vector and Embedding Weaknesses - RAG security |
| LLM10 | π Updated | Unbounded Consumption (was "Model Theft") - DoS/DoW attacks |
| LLM01-06, LLM09 | β Enhanced | Improved patterns for indirect injection, confused deputy |
CVE-2025-6514 Detection (MCP117)
Critical OAuth command injection vulnerability in mcp-remote (CVSS 9.6):
// CRITICAL: MEDUSA now detects this attack pattern
const authUrl = authorization_endpoint + userInput;
open(authUrl); // PowerShell subexpression injection on WindowsAffected: mcp-remote versions 0.0.5 - 0.1.15
Advanced Confused Deputy Detection (MCP118)
New patterns for privilege escalation via tool authorization:
- Service account execution abuse
- Auth header forwarding issues
- Permission override patterns
- Multi-hop authorization bypass
4 New GenAI Security Scanners (60 Total!)
| Scanner | Rules | Focus |
|---|---|---|
| ModelAttackScanner | 10 | Adversarial inputs, model extraction, membership inference |
| LLMOpsScanner | 10 | Insecure model loading, checkpoint exposure, drift detection |
| VectorDBScanner | 10 | Unencrypted storage, tenant isolation, PII in embeddings |
| OWASPLLMScanner | 10 | Full OWASP Top 10 2025 compliance |
π New Documentation
AI Security Guide (500+ lines)
Comprehensive documentation covering:
- What Gets Scanned - File types, content triggers, detection flow
- Practical Examples - LangChain, MCP servers, RAG pipelines, ML Ops
- Scanning Workflows - CI/CD, pre-commit, security audits
- Complete Rule Reference - All 150+ AI-specific rules
Example: Scanning a LangChain App
$ medusa scan my-chatbot/
CRITICAL (2)
app.py:45 [LLM01] Prompt Injection: User input in f-string
chains/agent.py:78 [LLM05] Improper Output: exec(llm_response)
HIGH (3)
app.py:12 [LLM02] Hardcoded API key
vectorstore/db.py:56 [VD002] Missing access controls
...π By The Numbers
| Metric | v2025.7 | v2025.8 | Change |
|---|---|---|---|
| AI Scanners | 12 | 16 | +33% |
| AI Rules | 50+ | 150+ | +200% |
| Total Scanners | 56 | 60 | +4 |
| Documentation | Basic | Comprehensive | +500 lines |
π‘οΈ Standards Compliance
- β OWASP Top 10 for LLM 2025 (November 2024)
- β MITRE ATLAS (AI threat landscape)
- β CWE-441 (Confused Deputy)
- β CVE-2025-6514 (mcp-remote RCE)
π Quick Start
pip install --upgrade medusa-security
# Scan your AI codebase
medusa scan .
# See AI-specific issues
medusa scan . --format htmlπ Supported AI Files
.py, .js, .ts, .tsx # LLM application code
mcp.json # MCP configurations
*.mcp.ts / *.mcp.py # MCP server implementations
.cursorrules # Cursor AI
CLAUDE.md # Claude Code
rag.json / *.yaml # RAG configurations
π Resources
Full Changelog: v2025.7.0.0...v2025.8.0.0
π€ Generated with Claude Code