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What Is Risk Scoring? Models, Frameworks, and Limits
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AIVigil is an AI-native Attack Surface Monitoring platform that continuously discovers, monitors, and secures exposed AI infrastructure, MCP servers, leaked AI credentials, vector databases, agentic workflows, and shadow AI across the internet.
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Global Enterprises and Fortune 500 companies trust CloudSEK to fortify their cybersecurity posture.
AIVigil helps organizations discover, monitor, and secure AI attack surfaces across models, prompts, APIs, and AI integrations. Built for modern AI environments with continuous AI threat detection and real-time AI security monitoring.
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Discover MCP servers,
vector stores, agentic workflows, AI Models.
Trigger alerts, reporting, and response
from a unified AI asset view.
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Score exposure using agent agency, auth state, blast radius, and live signals.
AIVigil continuously discovers, analyzes, and monitors AI attack surfaces across models, prompts, APIs, and AI integrations. Built to deliver real-time AI threat detection, AI risk visibility, and continuous AI security monitoring.
AIVigil continuously discovers, analyzes, and monitors AI attack surfaces across models, prompts, APIs, and AI integrations. Built to deliver real-time AI threat detection, AI risk visibility, and continuous AI security monitoring.
Discover MCP servers, vector stores in, agentic workflows, AI Models.
Function: Finding the Shadow AI.
MCP-Specific Scanning, Agentic Workflow Analysis, Supply Chain Scanning, Active AI Red Teaming.
Function: Contextualizing the Vulnerability.
Real-Time Threat Intel Pipeline, Unified Asset Inventory (AI BOM), Automated Reporting & Remediation.
Function: Operationalizing the Posture.
See, monitor, and secure your entire AI attack surface from a single platform.
The latest helpful guides from CloudSEK.
AI attack surface management is the continuous discovery, fingerprinting, and monitoring of an organization's internet-exposed AI infrastructure - including self-hosted engines, MCP servers, vector databases, agentic workflows, leaked AI credentials, and shadow AI. It identifies AI-layer initial access vectors - such as exposed AI servers, leaked API keys, and MCP tool poisoning - before attackers can exploit them and chain them into an executable attack path.
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, and more. 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 shadow AI, MCP tool poisoning, leaked AI credentials, or poisoned open-source models because these risks live in AI infrastructure and supply chains - not the code layer. AIVigil is purpose-built for the AI attack surface, continuously monitoring 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.
AIVigil is built for CISOs, heads of AI security, security operations teams, and AI/ML engineering teams at enterprises deploying AI systems at scale. It gives security leaders the visibility to answer the questions boards and regulators are now asking: what AI systems are we running, what are the initial access vectors, and how are we monitoring and managing AI-layer risk?
