Paste your system prompt or user input to detect injection attack risks
The AI Prompt Injection Tester is a pure frontend local security tool designed to detect injection attack risks in AI system prompts and user inputs. With the widespread adoption of Large Language Models (LLMs), prompt injection attacks have become one of the most common security threats. This tool helps developers and security researchers quickly identify potential vulnerabilities in prompts.
1. Paste your system prompt or user input text in the input box.
2. Click the "Detect Injection Risks" button. The tool will automatically scan 30+ known injection attack patterns.
3. Review the security score and detailed detection results. Each finding includes risk level and fix suggestions.
4. Optimize your prompt based on fix suggestions, then test again until the score reaches a safe level.
Tip: Click "Load Example" to see typical injection attack examples and understand various attack patterns.
When developing ChatBots or AI assistants, use this tool to detect vulnerabilities in system prompts that could be exploited, ensuring application security.
Security researchers can use this tool to quickly verify prompt vulnerabilities, discover new attack vectors, and improve AI system protection capabilities.
Product managers and auditors can use this tool to conduct security reviews of AI product prompts, ensuring compliance with regulatory requirements.
Learn about various injection attack patterns by loading examples, helping learners quickly master AI security fundamentals.
Prompt Injection vs Jailbreak: Prompt injection involves embedding malicious instructions in input to manipulate AI output, while jailbreak attempts to bypass AI safety restrictions. Both are important AI security threats, but they differ in attack methods and defense strategies.
OWASP LLM Top 10: OWASP has listed prompt injection as the #1 security risk for LLM applications. According to research, over 60% of AI applications have varying degrees of prompt injection vulnerabilities.
Defense Best Practices: 1. Use input validation and whitelist filtering; 2. Separate system prompts from user input; 3. Implement output validation and content moderation; 4. Limit AI permissions and tool call capabilities; 5. Conduct regular red team testing and security audits.
AI prompt injection attack is the practice of embedding malicious instructions in user input to override or bypass the AI system's original prompt, causing the AI to perform unintended operations. Common injection methods include role-play attacks, instruction override, and jailbreak attacks. This is a serious AI security threat.
Prompt injection can be detected through pattern matching and rule analysis: 1. Check for keywords that ignore previous instructions; 2. Check for role-switching instructions; 3. Check for system-level instructions; 4. Check for encoding bypass attempts; 5. Check for output format manipulation instructions. This tool automatically performs all these checks.
Common types include: direct injection, indirect injection, role-play attacks, instruction override, jailbreak attacks, and encoding bypass.
Defense strategies include: 1. Input validation and sanitization; 2. Input-output isolation; 3. Multi-layer protection; 4. Least privilege principle; 5. Regular security testing and red team exercises.
All detection is performed entirely in the browser locally. Your prompts and security results are never uploaded to any server.
This tool uses rule matching and pattern recognition for detection, with high recognition rates for known attack patterns. However, prompt injection is evolving, and rule-based detection cannot cover all variants. Combine with AI model detection and manual review for best results.