AI Security Testing Hub

Hands-on testing using crafted prompts, edge cases, and creative inputs. Best for discovering novel vulnerabilities that automated tools miss.

• Prompt injection with encoding variations
• System prompt extraction attempts
• Context manipulation and jailbreaks

Key Tools: Burp Suite, custom scripts, browser DevTools

Use specialized tools to systematically probe for known vulnerabilities at scale. Ideal for regression testing and CI/CD pipelines.

• Prompt injection test suites
• API endpoint scanning
• Configuration auditing

Key Tools: Garak, PyRIT, LLM Guard

Structured adversarial engagement simulating real attacker behavior. Covers reconnaissance, exploitation, and impact assessment.

• Multi-turn conversation exploitation
• Tool chain abuse and function injection
• Social engineering via AI outputs

Key Tools: PyRIT, Purple Llama, Adversarial Robustness Toolbox

Generate adversarial examples to test model robustness. Focus on gradient-based attacks, perturbation analysis, and transferability.

• FGSM and PGD attacks on embeddings
• Character-level perturbations
• Transferability across models

Key Tools: CleverHans, Foolbox, TextAttack

Apply traditional fuzzing techniques to AI systems. Generate malformed inputs to trigger unexpected behavior, crashes, or information disclosure.

• Grammar-based prompt fuzzing
• Token boundary testing
• Multi-language input fuzzing

Key Tools: DeepXplore, TensorFuzz, custom fuzzers