Secure Your AI Models Before They Run
Vigilnz Model Scan inspect AI model artifacts to uncover malicious code, hidden payloads, and supply-chain risks before they reach your AI system
Hidden Risks Inside AI Models
AI models downloaded from public repositories or shared internally may contain unsafe serialized code, hidden execution paths, or malicious payloads that execute when the model loads.
Malicious Serialized Code
AI model files may contain unsafe serialized objects that execute code when the model loads.
Hidden Payloads
Models can include embedded commands that compromise systems during execution
Unsafe Execution Paths
Unexpected execution triggers inside models can perform unauthorized actions.
Model Supply Chain Risks
Identify vulnerabilities introduced through third-party models, dependencies, and external sources across the AI supply chain.
What Model Scan Detects
Deep analysis of AI model artifacts to uncover hidden threats and risks before deployment.
Unsafe Serialized Objects
Identify insecure or harmful serialized components (like pickle files) embedded within AI model files that could execute unintended actions.
Embedded Malicious Code
Detect hidden scripts, payloads, or executable code injected into model artifacts that may compromise systems during runtime.
Backdoor Execution Paths
Uncover hidden triggers or logic within models that activate under specific conditions, leading to unauthorized behavior.
Tampered Model Artifacts
Ensure the integrity of AI models by identifying unauthorized modifications in both third-party and internally shared models.
Suspicious Model Metadata
Analyze metadata for abnormal configurations, hidden instructions, or risky parameters that may indicate potential threats.
AI Model Supply Chain Risks
Detect vulnerabilities introduced through external or untrusted sources across the AI model lifecycle and supply chain.
Scan Your AI Models for Hidden Threats
Identify vulnerabilities, backdoors, and malicious code before they impact your systems.
