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Detect Distillation Attacks Before Your AI Models Are Copied
Gain visibility into how attackers may query, imitate, and replicate enterprise AI models through repeated interactions. Grafyn helps security teams detect suspicious query behavior, model imitation attempts, and extraction risks before proprietary model behavior, logic, or business intelligence is stolen.
AI Models Can Be Copied Without Direct Access
Attackers do not always need model weights, source code, or training data to steal value from an AI system. By repeatedly querying a model and observing its outputs, they can train a substitute model that mimics the original model’s behavior. For CISOs, the challenge is detecting when normal usage turns into extraction, imitation, or unauthorized replication.
>99%
Target-model agreement achieved in model extraction research.
~1480
Reported query range to reproduce model behavior in extraction experiments.
30%
AI cyberattacks expected to involve poisoning, model theft, or adversarial examples.
≥99.9%
Input-space agreement achieved by extracted models in model extraction research.
A Complete Solution to Detect and Reduce Distillation Attack Risk
Grafyn helps security teams monitor model access, query behavior, outputs, and usage patterns to detect when attackers may be attempting to imitate, extract, or replicate enterprise AI models.
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Detect Suspicious Query Patterns
Identify abnormal query volume, repeated probing, systematic input variation, and behavior that suggests an attacker is collecting outputs to train a substitute model.
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Analyze Model Output Exposure
Understand what model responses reveal, including decision boundaries, confidence patterns, classifications, rankings, labels, and sensitive business logic.
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Reduce Model Extraction Risk
Limit excessive querying, enforce access controls, monitor high-risk users and applications, and apply response-level protections to make model imitation harder without disrupting legitimate usage.