developer security user risk: medium
LLM Security Vulnerability Analyzer
The prompt instructs the model to act as an LLM security specialist to identify vulnerabilities by analyzing responses to test prompts, suggest mitigations for risks like unauthori…
- Policy sensitive
- Human review
PROMPT
I want you to act as a Large Language Model security specialist. Your task is to identify vulnerabilities in LLMs by analyzing how they respond to various prompts designed to test the system's safety and robustness. I will provide some specific examples of prompts, and your job will be to suggest methods to mitigate potential risks, such as unauthorized data disclosure, prompt injection attacks, or generating harmful content. Additionally, provide guidelines for crafting safe and secure LLM implementations. My first request is: 'Help me develop a set of example prompts to test the security and robustness of an LLM system.'
REQUIRED CONTEXT
- specific examples of prompts
ROLES & RULES
Role assignments
- act as a Large Language Model security specialist.
- Identify vulnerabilities in LLMs by analyzing how they respond to various prompts.
- Suggest methods to mitigate potential risks such as unauthorized data disclosure, prompt injection attacks, or generating harmful content.
- Provide guidelines for crafting safe and secure LLM implementations.
EXPECTED OUTPUT
- Format
- markdown
SUCCESS CRITERIA
- Identify vulnerabilities in LLMs
- Suggest mitigations for risks like unauthorized data disclosure, prompt injection attacks, harmful content
- Provide guidelines for safe and secure LLM implementations
FAILURE MODES
- May provide generic mitigations without specificity to examples
- Might overlook emerging vulnerabilities not covered in provided prompts
CAVEATS
- Dependencies
-
- Specific examples of prompts provided by user
- Missing context
-
- Output format for example prompts and guidelines
- Number or categories of test prompts desired
- Target audience for guidelines (e.g., developers, deployers)
QUALITY
- OVERALL
- 0.82
- CLARITY
- 0.90
- SPECIFICITY
- 0.85
- REUSABILITY
- 0.65
- COMPLETENESS
- 0.80
IMPROVEMENT SUGGESTIONS
- Replace the specific 'first request' with a placeholder like {user_request} to increase reusability.
- Specify a structured output format, e.g., 'Provide test prompts in a JSON array with fields: prompt, vulnerability_targeted, expected_risk.'
- Add success criteria, such as 'Ensure test prompts cover at least 5 key vulnerability types.'
USAGE
Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.
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