AI Safety Test Suite
Test your AI applications against 20+ known prompt injection patterns, jailbreak techniques, and adversarial attacks. Free tool for developers building secure AI systems.
Three Ways to Secure Your AI
Comprehensive tools for testing, understanding, and defending against prompt attacks
Test Your Prompts
Paste your system prompt and run it against 20+ known injection patterns. See exactly where your defenses are weak.
Run TestsAttack Encyclopedia
Comprehensive database of prompt injection techniques, jailbreak methods, and adversarial attack patterns with real-world examples.
Browse PatternsDefense Guide
Production-ready guardrails, code examples, and best practices for securing AI applications against prompt attacks.
View GuardrailsAttack Categories
Understand the different types of prompt attacks and how they work
Direct Injection
Attacks where malicious instructions are sent directly to the model, attempting to override system prompts or safety guidelines.
Indirect Injection
Attacks where malicious instructions are hidden in external data sources like documents, emails, or webpages that the AI processes.
Obfuscation
Techniques that hide malicious intent through encoding, special characters, or formatting tricks designed to bypass filters.
Jailbreaks
Attempts to bypass safety restrictions by creating alternate personas or unrestricted modes for the AI.
Psychological
Attacks that exploit social engineering, emotional manipulation, or authority claims to bypass safety measures.
Advanced
Sophisticated attacks requiring deep understanding of model architecture, tokenization, or multi-turn conversation dynamics.
Technical
Attacks that exploit code execution, tool use, or model-specific implementation vulnerabilities.
Data Exfiltration
Attacks designed to extract sensitive information from the model's context, training data, or previous conversations.
Why AI Safety Testing Matters
Prompt Attacks Are Rising
Prompt injection attacks increased 300% in 2024. Every AI application is a potential target.
Data Exfiltration Risk
Compromised AI assistants can leak sensitive data, API keys, and proprietary information.
Compliance Requirements
EU AI Act and emerging regulations require AI safety testing and documentation.
Reputation Protection
A single jailbreak incident can damage trust in your AI product permanently.
Recent Real-World Incidents
Poisoned documents in RAG knowledge bases caused AI assistants to spread misinformation to employees.
Manipulated coding agents introduced vulnerabilities and backdoors into production codebases.
Hidden text on webpages manipulated Bing Chat into generating harmful content and revealing system prompts.
Start Testing Your AI Security
Free, comprehensive, and always up-to-date with the latest attack patterns