DeepKeep

Automatically scans deployed AI models to identify security vulnerabilities, model drift, data poisoning risks, and adversarial attack surfaces before they can be exploited in production environments.

Automatically applies fixes and patches to detected AI vulnerabilities without requiring manual intervention, reducing response time and minimizing human error in security incident handling.

Continuously monitors multiple AI models in production simultaneously, tracking security metrics, model performance degradation, and emerging threats across an entire AI portfolio in real-time.

Identifies when AI models are deviating from expected behavior patterns or experiencing performance degradation, which can indicate security issues, data quality problems, or model staleness.

Automatically generates security audit trails, compliance reports, and documentation of all detected vulnerabilities and remediation actions for regulatory requirements and internal governance.

Analyzes AI models to identify potential adversarial attack vectors and surfaces where malicious actors could manipulate model behavior through crafted inputs or data poisoning.

Evaluates the risk that training or inference data has been compromised or manipulated to degrade model performance or introduce malicious behavior.

Detects unusual or anomalous behavior in model predictions and outputs that deviate from established patterns, which may indicate security breaches, model compromise, or unexpected model behavior.

Assigns risk scores to detected vulnerabilities and prioritizes them based on severity, exploitability, and business impact to guide remediation efforts.