Model Format Vulnerability Form beta

A model format vulnerability refers to a security flaw that arises from the way an AI/ML model is stored or serialized in a specific file format. Exploiting these flaws can lead to real-world impacts, such as unauthorized model manipulation or malicious code execution.

Currently, we have identified two broad categories of model format vulnerabilities: Deserialization and Backdoors.

• Deserialization vulnerabilities occur when improperly handled serialized data allows attackers to inject malicious payloads during model loading.
• Backdoors, on the other hand, involve the intentional embedding of hidden malicious functionality within the model itself.

These categories are not exhaustive and we are constantly on the lookout for new threat vectors. If you have discovered a vulnerability that doesn't fall within these categories, please submit it anyway.