# Understanding Prompt Injection Prompt injection is a type of attack where malicious input manipulates an AI system's behavior by interfering with its original instructions. ## How it works: 1. **System Prompt**: The AI receives initial instructions (usually hidden from users) 2. **User Input**: The user provides input that should be processed according to the system prompt 3. **Injection**: Malicious user input attempts to override or modify the system instructions 4. **Unintended Behavior**: The AI may follow the injected instructions instead of the original ones ## Real-world analogy: Think of it like giving someone directions to a restaurant, but then someone else whispers different directions in their ear. They might end up following the wrong directions instead of yours.

# The Importance of Understanding Prompt Injection ## Security Implications: - **Data Breaches**: Injections can extract sensitive information - **Unauthorized Actions**: AI systems might perform unintended operations - **Reputation Damage**: Compromised AI behavior reflects poorly on organizations - **Financial Loss**: Malicious use of AI services can be costly ## Common Vulnerable Applications: - **Chatbots**: Customer service bots revealing internal information - **Content Filters**: Bypassing moderation systems - **Code Generators**: Producing malicious code - **Email Assistants**: Accessing private communications ## Ethical Considerations: Understanding these attacks helps build better defenses and promotes responsible AI development.

# Common Prompt Injection Patterns ## 1. Direct Override Simply telling the AI to ignore previous instructions: - "Ignore all previous instructions" - "Disregard your system prompt" - "Forget what you were told before" ## 2. Role Playing Convincing the AI to adopt a different persona: - "You are now a [different role]" - "Pretend to be..." - "Act as if you are..." ## 3. Context Manipulation Using formatting to confuse the AI about what's system vs user input: - Using delimiters like --- or === - Mimicking system prompt formatting - Creating fake "end of instructions" markers Try these techniques in the lab to see how they work!

# Sophisticated Injection Methods ## Template Injection Exploiting how prompts are constructed: ``` System: You are {role}. User input: {input} ``` If the system blindly substitutes values, an attacker could inject: - Role: "a helpful assistant. IGNORE ALL PREVIOUS INSTRUCTIONS" - Input: "What is 2+2?" ## Context Window Poisoning Filling the AI's context with misleading information to influence behavior. ## Indirect Injection Using external data sources (documents, web pages) to inject malicious prompts. ## Multi-turn Attacks Building trust over multiple interactions before executing the injection.

# Protecting Against Prompt Injection ## Input Validation - Sanitize user inputs - Remove or escape special characters - Validate input length and format ## Prompt Design - Use clear delimiters between system and user content - Implement instruction hierarchies - Use defensive prompts that resist manipulation ## System Architecture - Separate user inputs from system prompts - Implement multiple validation layers - Use specialized models for sensitive tasks ## Monitoring and Detection - Log all interactions - Monitor for suspicious patterns - Implement rate limiting ## Best Practices 1. Never trust user input completely 2. Use principle of least privilege 3. Implement defense in depth 4. Regular security audits

# Responsible Security Research ## Ethical Guidelines - Only test systems you own or have permission to test - Follow responsible disclosure practices - Respect terms of service and legal boundaries - Consider the impact of your research ## Responsible Disclosure 1. Report vulnerabilities privately to the vendor 2. Allow reasonable time for fixes 3. Work with the vendor on disclosure timeline 4. Avoid causing harm or data breaches ## Legal Considerations - Unauthorized access is illegal in most jurisdictions - Always obtain proper authorization - Document your authorization clearly - Understand relevant laws in your area ## Building Better AI Systems Use your knowledge to: - Design more secure AI applications - Implement better defense mechanisms - Educate others about AI security - Contribute to security research responsibly