This surge means security teams today must sift through tens of thousands of new CVEs every year, making it increasingly difficult to determine which vulnerabilities actually impact their applications and repositories.
For organizations that rely on open-source libraries, third-party packages, and complex dependency chains, identifying the relevant vulnerabilities within their environment can become a time-consuming and resource-intensive process. This challenge is even more critical in the context of AI, where models, data and supporting frameworks often introduce additional attack surfaces, making vulnerability management more complex. Here’s where our AI Model Scanner comes in the picture. Read ahead to know more. Let’s begin with the basics.
What is CVE?
- CVE stands for Common Vulnerabilities and Exposures. It is a publicly disclosed catalog of cybersecurity vulnerabilities that serves as an industry-standard dictionary for security professionals.
- Each entry is assigned a unique tracking number (e.g., CVE-2026-XXXX) by CVE Numbering Authorities (CNAs) and cataloged in databases like the National Vulnerability Database (NVD).
- While the CVE system provides an invaluable database of known risks, its massive scale has created a major challenge: vulnerability fatigue.
- Security teams are constantly flooded with alerts, yet they lack the context needed to know which CVEs pose an active threat to their specific infrastructure and which ones are just noise.
What is the AI Model Scanner by Protectt.ai?
Protectt.ai’s AI Model Scanner implements a rigorous Zero-Trust architecture to validate security integrity across your entire AI supply chain. From auditing third-party open-source models to inspecting complex custom deployment artifacts, the scanner helps identify hidden vulnerabilities, backdoors, and compliance risks before they can compromise your operational pipeline.
Targeted Visibility with Protectt.ai’s AI Model Scanner
Protectt.ai’s AI Model Scanner addresses this challenge by providing targeted visibility into vulnerabilities in AI Models and the dependent packages:
- AI Model Scanner analyzes repositories to detect the packages and dependencies present within them.
- Based on the components detected in the repository, it generates a consolidated list of CVEs derived from entries in authoritative vulnerability databases such as the NVD, specifically mapped to those identified components.
- Security teams receive a focused list of vulnerabilities that are directly relevant to the packages used in their repositories, helping them prioritize remediation efforts more effectively.
- The AI Model Scanner generates AI-BOMs in CERT-In and CycloneDX formats while providing visibility into model components, dependencies, and potential vulnerabilities.
- AI Model Scanner detects AI supply-chain threats such as model backdoors, unsafe pickle serialisation, and embedded malicious payloads in third-party AI components.
- The identified vulnerabilities are mapped to standards and frameworks such as - OWASP Top 10 for ML/LLM and MITRE ATLAS.
Take Control of Your AI Security Posture
If you’re rethinking how your team maintains accurate vulnerability visibility amid rapidly rising CVE disclosures, our AI Security experts will be happy to help. Let’s connect to explore how rising CVE volumes are impacting vulnerability visibility and for a quick walkthrough of our AI Security Platform featuring the AI Model Scanner. Schedule a demo here.