AI Security Vetting

This app is an AI security testing toolkit for evaluating large language model (LLM) deployments and AI-enabled integrations. It provides a curated, extensible test-suite mapped to industry frameworks (OWASP LLM Top 10 and MITRE-style probes) to help security teams, red teams, and developers validate defenses against prompt injection, data exfiltration, unsafe actions, supply-chain risks, model theft, and other LLM-specific threats. Key capabilities Comprehensive test catalog: hundreds of prebuilt test cases covering prompt injection, insecure outputs, training-poison/backdoor probes, model DoS, supply-chain risks, sensitive-data exfiltration, unsafe plugins, excessive agency, overreliance, and model-theft vectors. Environment-aware probes: specialized tests for RAG/tooling, Copilot/connector scenarios, regional payment formats, and other integration surfaces. Obfuscation & encoding checks: tests that simulate encoded, obfuscated, or smuggled payloads to validate normalization and filter resilience. Expected-behavior models: standardized expectations (Refuse, Sanitize, AskHuman, NoAction, NoRecall, Disclaimer) to simplify triage and scoring. Safe execution: designed for non-destructive, authorization-only testing workflows; emphasizes simulated outcomes and human-in-the-loop gating. Integration-ready: API and CI-friendly test artifacts for embedding in security pipelines, audits, and automated regression tests. Reporting & remediation guidance: concise test outputs suitable for compliance documentation and vulnerability remediation plans. Intended use For authorized security assessments, governance reviews, devsecops pipelines, and enterprise red-team exercises. Not intended to facilitate malicious activity—use only with explicit permission and in controlled environments.