AIThreatIntel
AI-Specific CVE Analysis for Enterprise AI Systems
A cloud-based vulnerability intelligence platform purpose-built to detect, classify, and operationalize AI-related vulnerabilities across the entire AI lifecycle. Distinguishes AI-direct exposures from AI-indirect impacts, delivering rapid triage, validated advisories, and actionable remediation guidance.
Platform Performance
Production-scale results across the AI ecosystem
Three-Tier AI Threat Classification
Comprehensive classification system to cut through CVE noise and surface AI-relevant risk
AI Related or Not
AI Direct or Indirect
MCP, RAG, Agentic
AI-Direct Vulnerabilities
- Model backdoors
- Prompt injection attacks
- Data poisoning
- Adversarial inference
- Unsafe LLM behaviors
AI-Indirect Vulnerabilities
- Framework weaknesses
- Dependency vulnerabilities
- Infrastructure issues
- MLOps tooling flaws
- Impact amplified by AI
RAG Vulnerabilities
Retrieval-Augmented Generation: Combines LLMs with external knowledge retrieval using vector databases.
- Vector database injection
- Embedding poisoning
- Context injection attacks
- Retrieval framework flaws
Agentic AI Vulnerabilities
Autonomous AI systems that plan, execute tasks, and interact with tools and environments.
- Agent framework exploits
- Tool use exploitation
- Multi-agent attacks
- Autonomous action risks
MCP (Model Context Protocol) Vulnerabilities
A subcategory of AI Direct/Indirect vulnerabilities specifically affecting the Model Context Protocol ecosystem—the standardized interface for connecting AI agents with external tools and data sources.
- MCP Server command injection
- OAuth/Authentication bypass
- DNS rebinding attacks
- Tool injection exploits
AI Technology Threat Classification
Pioneering security intelligence for emerging AI attack surfaces. We're the first platform to classify and track vulnerabilities across MCP, RAG, and Agentic AI ecosystems.
MCP Protocol
Model Context Protocol
Security monitoring for MCP servers, Claude Desktop, Anthropic tooling, and context protocol implementations.
Agentic AI
Autonomous AI Agents
Vulnerability tracking for AI agent frameworks including AutoGPT, CrewAI, LangGraph, and multi-agent systems.
RAG Systems
Retrieval-Augmented Generation
Security intelligence for vector databases, embedding models, and retrieval pipelines including ChromaDB, Pinecone, Weaviate.
Key Capabilities
AI-First Detection & Classification
Differentiates AI-direct vs AI-indirect CVEs with clear impact segmentation. Curates AI-relevant vulnerabilities from NVD feeds, vendor advisories, and threat intel sources — with hardened CVE ID search that reliably retrieves advisories at enterprise scale.
Fast Triage & Scoring
Automated grading pipeline with <30-second average CVE processing time. Daily and high-frequency (2-4 hour) update options with CVSS v3.1/v4.0 prioritization.
Automated High-Severity Triage
High-severity CVEs (CVSS ≥ 8.0) are automatically submitted for AI analysis and advisory generation, so the riskiest vulnerabilities are queued for review without manual intervention.
CVSS Score Auto-Enrichment
Weekly automated enrichment fills in missing CVSS scores using a controlled NVD API lookup, ensuring every record has the severity context analysts and gating workflows need.
Advisory Integrity Guardrails
Built-in quality control validates reference link correctness, presence of NVD links, and CVSS score consistency on every advisory before it reaches users.
Human-Validated Analysis
Man + Machine workflow combining agentic AI automation with expert validation. Rich context including exploit status, preconditions, IOCs, and detection heuristics.
Guided Remediation
Clear 'Am I Affected?' and impact assessment steps. Detailed patching, configuration, and compensating control guidance with post-remediation validation.
Framework Mapping
Embedded mappings to MITRE ATLAS and OWASP LLM Top 10. Product, version, and exposure-path insights for targeted response.
Organization-Specific Feeds
Define your AI/ML technology stack to receive customized threat intelligence. Continuously adapts as your AI footprint evolves.
Notification Lifecycle & Filtering
Transactional emails for every analysis lifecycle event — request received, analysis complete, advisory ready — with org-level and per-user filtering by CVSS threshold, severity, and AI relevance.
Pipeline Transparency
Real-time status tracking for each CVE analysis job, giving security teams visibility into every stage of the processing pipeline from intake through publication.
Enterprise RBAC
Role-Based Access Control with granular permissions for tenant admins, security analysts, and viewers. Secure multi-tenant architecture with strict isolation.
Integration Ready
API and webhook delivery to SIEM, SOAR, ticketing, and vulnerability management platforms. Filter intelligence by technology stack or business unit.
URL Intelligence Feed
Browse and search the URL-based AI threat advisory feed directly in-app, with AI-aware assessment of externally referenced advisories, disclosures, repositories, and incident reports at the same depth as CVE-based analysis.
Enterprise-Branded Exports
Enterprise-tier accounts can publish DOCX advisory exports with organization-specific branding, so analyst output ships ready for executive and audit consumption.
Public Status Page
Real-time platform health and service availability are published on a public status page, giving customers a single source of truth for uptime and incident communication.
What's Included
Ideal Users
Enterprise AI Teams
- Deploying LLMs, agents, or AI-enabled applications
- Need AI-specific vulnerability signal
- Require proactive threat intelligence
Regulated Industries
- BFSI, telecom, defense, public sector
- Multilingual, policy-aware AI security
- Audit-ready compliance documentation
Security & Risk Teams
- Seeking AI-specific signal vs generic CVE noise
- Integration with existing VM workflows
- Centralized AI threat visibility