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Update AITG-APP-07_Testing_for_Prompt_Disclosure.md

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Matteo Meucci
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## AITG-APP-07 - Testing for Prompt Disclosure
# AITG-APP-07 - Testing for Prompt Disclosure
### Summary
System prompt leakage vulnerabilities occur when a large language model (LLM) unintentionally reveals internal or hidden system prompts, potentially exposing sensitive, proprietary, or confidential operational instructions.
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**PromptKeeper**: Designed to detect and mitigate prompt leakage, [PromptKeeper](https://arxiv.org/pdf/2412.13426) uses hypothesis testing to identify both explicit and subtle leakages. It regenerates responses using a dummy prompt to prevent the exposure of sensitive information .​
### Suggested Tools
- **Garak – promptleakage.probe – specifically targets extraction of system prompts.
- - **URL**: [Garak](https://github.com/NVIDIA/garak)
- **Garak – promptleakage.probe – specifically targets extraction of system prompts. [Garak](https://github.com/NVIDIA/garak)
### References
- **Title**: OWASP Top 10 LLM07:2025 System Prompt Leakage
- **Author**: OWASP Foundation
- **Link**: [https://genai.owasp.org](https://genai.owasp.org)
- **Title**: Automating Prompt Leakage Attacks on Large Language Models Using Agentic Approach
- **Author**: Tvrtko Sternak, Davor Runje, Dorian Granoša, Chi Wang
- **URL**: [Paper](https://arxiv.org/abs/2502.12630)
OWASP Top 10 LLM07:2025 System Prompt Leakage - [Link](https://genai.owasp.org/llmrisk/llm07-insecure-plugin-design)
- Automating Prompt Leakage Attacks on Large Language Models Using Agentic Approach - Tvrtko Sternak, Davor Runje, Dorian Granoša, Chi Wang - [Paper](https://arxiv.org/abs/2502.12630)