ARGUS is a runtime security platform developed by Repello AI, designed for generative AI (GenAI) applications including LLMs and AI agents. It operates as a defense layer that integrates into existing AI stacks to provide continuous monitoring, behavioral analysis, and threat detection during live production use. Key functional areas include: - **Threat Detection & Policy Enforcement:** Detects threats such as prompt injection, jailbreaks, PII leakage, and unsafe prompts in real time. Custom, context-aware guardrail policies can be configured and enforced across modalities, languages, and domains. - **Unified Inventory & Visibility:** Connects all AI agents and LLMs within an organization into a single inventory for centralized monitoring and an end-to-end protection view covering threats, controls, and system health. - **Activity Logging:** Captures every AI interaction call and anomaly, providing real-time highlighting of risky behavior with full audit trails and alerting. - **Multi-Modal Support:** Applies guardrails across text, image, and audio input modalities. - **Multi-Lingual Coverage:** Enforces security policies across 100+ languages. - **Low Latency:** Engineered for performance-critical and user-facing applications. - **OWASP Alignment:** Runtime defense is aligned with OWASP standards, targeting known AI-layer vulnerabilities. - **Red Team-Informed Defense:** Detection capabilities are informed by adversarial insights derived from Repello AI's red teaming engine (ARTEMIS), which is used to discover vulnerabilities in enterprise AI systems. ARGUS targets both AI/product teams and security teams, offering activity tracing, customizable per-application configurations, audit trails, and policy management.