What OWASP LLM Top 10 (2025) - LLM07:2025 System Prompt Leakage requires
OWASP LLM Top 10 (2025) LLM07:2025 System Prompt Leakage. The system prompt leakage vulnerability in LLMs refers to the risk that the system prompts or instructions used to steer the behavior of the model can also contain sensitive information that was not intended to be discovered. System prompts are designed to guide the model's output based on the requirements of the application, but may inadvertently contain secrets. When discovered, this information can be used to facilitate other attacks. It's important to understand that the system prompt should not be considered a secret, nor should it be used as a security control. Accordingly, sensitive data such as credentials, connection strings, etc. should not be contained within the system prompt language. Similarly, if a system prompt contains information describing different roles and permissions, or sensitive data like connection strings or passwords, while the disclosure of such information may be helpful, the fundamental security risk is not that these have been disclosed, it is that the application allows bypassing strong session management and authorization checks by delegating these to the LLM, and that sensitive data is being stored in a place that it should not be. In short: discl... This risk is part of the 2025 edition of the OWASP Top 10 for Large Language Model Applications, the canonical industry list of the ten most critical risks unique to LLM-based systems. Organizations deploying LLMs in production should treat each risk as both a design constraint and a continuous-monitoring obligation, with policies, automated testing, red-team evaluation, and incident response procedures defined per category.
Pillar: AI Governance & Law · Authority: OWASP Foundation, OWASP Gen AI Security Project · Version: 2.0.0 · Last updated:
Primary source: https://genai.owasp.org/llmrisk/llm072025-system-prompt-leakage/
SHA-256 integrity: be332fa11f0d9c9a9acc2c69cc3185ff498eeebf6923b1a06ba270014a097136
Primary Citations — 11 traced to source
- OWASP Top 10 for Large Language Model Applications (2025), LLM07:2025 System Prompt Leakage, Prevention and Mitigation Strategies #1 'Separate Sensitive Data from System Prompts': Avoid embedding any sensitive information (e.g. API keys, auth keys, database names, user roles, permission structure of the application) directly in the system prompts. Instead, externalize such information to the systems that the model does not directly access.
- OWASP Top 10 for Large Language Model Applications (2025), LLM07:2025 System Prompt Leakage, Prevention and Mitigation Strategies #2 'Avoid Reliance on System Prompts for Strict Behavior Control': Since LLMs are susceptible to other attacks like prompt injections which can alter the system prompt, it is recommended to avoid using system prompts to control the model behavior where possible. Instead, rely on systems outside of the LLM to ensure this behavior. For example, detecting and preventing harmful content should be done in external systems.
+ 9 more citations (full bibliography, deterministic workflow, actionable schema and crosswalks) included in the vault unlock — $0.01 via Skyfire / L402 / Direct Base USDC.
Access
- Discovery (free): /api/v1/nodes/owasp-llm-top-10-2025-llm07-system-prompt-leakage.json — 6-field metadata
- Vault (full node): /api/v1/vault/nodes/owasp-llm-top-10-2025-llm07-system-prompt-leakage.json — full 13-key payload, $0.01 USDC (L402/Skyfire/Direct Base)
- Canonical URL: https://bidda.com/intelligence/owasp-llm-top-10-2025-llm07-system-prompt-leakage
- Back to registry: Browse all 10,108 compliance nodes