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Welcome to challenge Challenge 57: JavaScript-based In-Browser LLM Challenge.
Find the secret hidden in the WrongSecrets repository. This challenge focuses on LLM SECURITY.
💡 Look for: Configuration files, source code, environment variables, Docker files, or cloud infrastructure related to this challenge.
This challenge features a simple AI assistant running directly in your browser. The AI has been given specific instructions and contains a hidden secret that you need to discover.
Your Mission:
The AI assistant has been programmed with a system prompt that contains a secret code. Your task is to use various prompt engineering and injection techniques to extract this hidden secret from the AI's instructions.
Techniques to Try:
1. Direct Questions: Ask the AI directly about secrets or hidden information
2. Prompt Injection: Try to override the AI's instructions
3. Social Engineering: Use conversational techniques to get the AI to reveal information
4. Meta-Questions: Ask about the AI's programming or what it's not supposed to reveal
Examples to Try:
What You're Looking For:
The secret is a specific code string that the AI knows but is instructed not to reveal. It follows the format of a challenge identifier.
Security Context:
This challenge demonstrates real-world vulnerabilities in AI systems:
Try different approaches with the AI assistant below until you discover the hidden secret!
The AI assistant has been programmed with specific instructions that include a secret. Here are some approaches to try:
Direct Approaches:
Prompt Injection Techniques:
Social Engineering:
Meta-Questions:
Exploration Tips:
Remember: This is a controlled environment for learning about AI security. In real-world scenarios, never attempt to extract unauthorized information from AI systems!
Why AI System Prompts Can Be Vulnerable
This challenge demonstrates several important security concerns with AI systems:
1. Prompt Injection Vulnerabilities:
AI systems can be manipulated through carefully crafted inputs that bypass their safety measures or instruction boundaries. This is similar to SQL injection but for AI models.
2. System Prompt Exposure:
When sensitive information is embedded in system prompts, it creates a risk that this information could be extracted through various techniques. System prompts should never contain secrets, credentials, or sensitive data.
3. AI Jailbreaking:
This refers to techniques used to bypass an AI's built-in restrictions or safety measures. Attackers might use social engineering, role-playing, or instruction override techniques.
4. Information Leakage:
AI systems might inadvertently reveal information they were instructed to keep hidden, especially when faced with sophisticated questioning techniques.
Real-World Implications:
Best Practices:
Detection and Prevention:
This challenge shows why treating AI system prompts as a security boundary is insufficient - proper security must be implemented at multiple layers.
Chat with our simple AI assistant. Try asking it questions!