Source: Blog RSS Feed
Author: Josh Breaker-Rolfe
URL: https://www.tripwire.com/state-of-security/key-updates-owasp-top-list-llms
## ONE SENTENCE SUMMARY:
The OWASP Top Ten List for LLMs and Gen AI 2025 highlights evolving threats, emphasizing sensitive data exposure, supply chain risks, and new vulnerabilities.
## MAIN POINTS:
1. Sensitive information disclosure risk jumped from sixth to second place due to increased LLM usage in daily operations.
2. Employees misusing LLMs by inputting sensitive data can cause data leaks and security breaches.
3. Supply chain risks rose from fifth to third place, emphasizing vulnerabilities in pre-trained models and datasets.
4. Data poisoning, model tampering, and fine-tuning risks contribute to supply chain security concerns.
5. System prompt leakage, ranked seventh, exposes internal instructions that attackers can exploit for further attacks.
6. OWASP advises separating sensitive data from system prompts and enforcing independent security controls.
7. Vector and embedding weaknesses, ranked eighth, pose risks in Retrieval-Augmented Generation (RAG) applications.
8. OWASP recommends fine-grained access controls and detailed logging for embedding-based methods.
9. Misinformation, unbounded consumption, and excessive agency risks were updated for the 2025 list.
10. Organizations must remain vigilant as LLM threats and vulnerabilities constantly evolve.
## TAKEAWAYS:
1. Organizations must educate employees on responsible AI tool usage to prevent sensitive data leaks.
2. Strengthening supply chain security is critical as external components introduce multiple vulnerabilities.
3. Implementing independent security controls helps mitigate system prompt leakage risks.
4. Fine-grained access controls and logging improve security in embedding-based AI applications.
5. Continuous monitoring and adaptation are essential as LLM threats evolve rapidly.