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