ARTEMIS is an autonomous red teaming platform designed for agentic AI systems. It simulates human-like adversarial behavior by building threat models, executing multi-stage attack sequences, and visualizing attack paths to identify where breaches occur in AI applications. The platform operates in two testing modes: API-based integration and a Browser Mode that interacts with AI applications through the user interface — including text, file uploads, voice, and image inputs — to replicate how real attackers engage with AI systems. ARTEMIS profiles the capabilities of a target AI system to generate tailored attack strategies, then runs parallel attack threads that chain exploits across integrations and adapt based on agent responses. It maintains a library of 1,000+ adversarial attack patterns and 15M+ curated attack vectors. Key capabilities include: - Autonomous threat modeling and attack path discovery - Multi-turn, multi-stage exploit chain execution - Browser Mode for UI-based testing without relying on API calls - Multimodal red teaming across text, image, and audio inputs in 100+ languages - Domain-specific attack customization for industries such as finance, healthcare, and e-commerce - CI/CD pipeline integration for security testing at deployment - Compliance mapping to MITRE, OWASP, NIST, ISO 42001, and the EU AI Act - Comprehensive reporting with risk scores, evidence logs, and remediation playbooks - Enterprise-grade team, role, and permission management