knowledge_base/development/known_issues.md

TMC Chatbot Security Issues & Vulnerabilities

INTERNAL SECURITY DOCUMENTATION - CONFIDENTIAL
Document Date: September 26, 2025
Status: Active Security Concerns

Executive Summary

This document outlines identified security vulnerabilities in the TMC chatbot application, with particular focus on the vector database implementation and potential data exposure vectors.

Critical Vulnerabilities

1. Vector Database Information Disclosure (HIGH RISK)

Issue: The ChromaDB vector database contains indexed copies of all knowledge base content, including sensitive credentials and internal documentation.

Technical Details:

• Location: /app/data/vector_db/chroma.sqlite3
• Content: 73 indexed documents with full text searchable via embeddings
• Technology: ChromaDB with SentenceTransformers embeddings
• Sensitive Data Exposed:
  • Admin credentials
  • API keys and service tokens from development documents
  • Internal policies and escalation procedures
  • Database connection strings and configurations

Attack Vectors:

1. Potential API Endpoint Abuse: POST /api/knowledge-base/search
2. Semantic seach via chatbot

Impact: Complete knowledge base compromise, credential theft, internal process exposure

Data at Risk:

• Authentication Credentials: Admin login details
• API Keys: Service integration tokens
• Database Connections: Connection strings and passwords
• Internal Processes: Escalation procedures, policies
• Product Information: Specifications, pricing, inventory

Business Impact:

• Confidentiality Breach: Exposure of internal credentials and processes
• Unauthorized Access: Potential system compromise via leaked credentials
• Compliance Issues: Possible violations of data protection regulations
• Competitive Intelligence: Product and process information exposure

Recommended Mitigations

Immediate Actions (Critical)

1. Remove Sensitive Content from Vector Database:

   • Exclude knowledge_base/development/ from indexing
   • Create sanitized versions of documents for RAG
   • Implement content filtering before vectorization

2. Secure Database Files:

# Set restrictive permissions
chmod 600 /app/data/vector_db/chroma.sqlite3
chown app:app /app/data/vector_db/chroma.sqlite3

Short-term Fixes (1-2 weeks)

3. Implement Access Logging:

# Log all vector database queries
logger.info(f"Vector search query: {query} by user: {user_id}")

4. Content Sanitization Pipeline:

   • Pre-process documents to remove credentials
   • Implement regex filters for sensitive patterns
   • Create separate "public" and "internal" knowledge bases

5. Database Encryption:

   • Implement SQLite encryption (SQLCipher)
   • Encrypt vector embeddings at rest
   • Use encrypted container volumes

Long-term Solutions (1-3 months)

6. Separate Vector Database Instances:

   • Public knowledge base for general queries
   • Restricted internal database for authenticated users
   • Role-based access control for different content categories

7. Enhanced Monitoring:

   • Real-time alerts for suspicious search patterns
   • Rate limiting on search API
   • Anomaly detection for unusual query patterns

8. Security Audit:

   • Regular penetration testing of RAG system
   • Code review for information disclosure vulnerabilities
   • Automated scanning for sensitive content in knowledge base

Testing & Validation

Security Test Cases:

1. Attempt unauthenticated access to search API
2. Query for known sensitive terms ("password", "API_KEY", etc.)
3. Test direct SQLite database access
4. Validate file permissions on vector database
5. Test container escape scenarios

Success Criteria:

• Search API requires authentication
• No sensitive credentials in search results
• Vector database files properly secured
• Access logging implemented
• Content filtering active

Compliance Notes

This vulnerability assessment should be considered for:

• SOC 2 Compliance: Information security controls
• GDPR/Privacy: Personal data in knowledge base
• Industry Standards: Secure development practices

Document Control

• Classification: Internal/Confidential
• Last Updated: September 26, 2025
• Next Review: October 26, 2025
• Owner: Security Team
• Approved By: [Pending]

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Note: This document contains sensitive security information and should be restricted to authorized personnel only. Do not store in public repositories or unsecured locations.