OWASP Top 10 Risk & Mitigations for LLMs and Gen AI Apps 2025
- OWASP Top 10 for LLMs (2025) addresses evolving threats in AI security
- Prompt Injection Vulnerability: Manipulates LLM behavior, mitigation includes prompt safeguards
- Data Sanitization: Scrub sensitive info, strengthen input validation, limit data access
- Federated Learning: Use decentralized data, adopt differential privacy
- User Education: Train safe interactions, promote transparent data policies
- Supplier Validation and Secure Model Integration are crucial for supply chain integrity
- Data Poisoning: Manipulate datasets to introduce vulnerabilities, use poison detection techniques
- Improper Output Handling: Validate LLM outputs, prevent XSS, CSRF, SSRF
- Excessive Agency: Prevent harmful actions triggered by LLM outputs
- System Prompt Leakage: Avoid exposing sensitive info through LLM instructions
- Vector and Embedding Security: Risks in RAG implementation, misinformation, and overreliance
- Unbounded Consumption: Risks of excessive model inferences, enforce input validation and rate limiting
私の考え: AIの進化は多くの産業で革新的な機能をもたらしていますが、それに伴いセキュリティ上の課題も増加しています。OWASP Top 10 for LLMs (2025)は、これらの新たな脅威に対処するための重要なガイドラインです。プロンプトインジェクションやデータ汚染などの脅威に対処するためには、適切な対策や教育が必要です。今後もAIシステムのセキュリティは重要性を増すでしょう。