احصل على رؤية للمجهول باستخدام AIVigil: AI Attack Surface Monitoring

Prompt injection is an attack technique where malicious inputs override an AI model's system instructions to extract data, execute unauthorized actions, or bypass safety controls. There are two main types: direct prompt injection (user-supplied inputs that override system prompts) and indirect prompt injection (malicious content embedded in documents or external data sources that the AI model processes). AIVigil continuously monitors LLM endpoints, AI APIs, and agentic workflows for both types — identifying prompt injection vulnerabilities before they are exploited.

AIVigil discovers every component of your AI attack surface, including: MCP (Model Context Protocol) servers, vector stores and embedding databases, agentic workflows and AI agents, large language model (LLM) endpoints, AI-integrated applications and APIs, model registries, GPU clusters and AI inference services, and training data pipelines. Discovery is continuous and includes shadow AI deployments — AI systems running without security team awareness.

Traditional SAST, DAST, and vulnerability scanners were built for code-level defects in conventional software. They cannot detect prompt injection, model abuse, agent hijacking, or vector database exposures because these risks operate at the AI model and inference layer — not the code layer. AIVigil is purpose-built for the AI attack surface, monitoring the unique initial access vectors that AI systems introduce.

AIVigil identifies AI-layer initial access vectors and feeds them into Nexus AI, CloudSEK's attack path intelligence layer. Nexus AI correlates AI risks with external threat signals from XVigil (dark web, threat actor activity) and third-party supply chain risks from SVigil to produce a validated attack graph — showing exactly how attackers will chain an AI vulnerability with a leaked credential or vendor exposure into a real, executable attack path.