Cybersecurity
CrowdStrike Launches On-Device AI for Real-Time Sensitive Data Classification
CrowdStrike has added an on-device AI capability to Falcon Data Security, enabling real-time classification of sensitive data using language models running on dedicated Intel hardware. The update allows security teams to detect and label confidential information at the endpoint without sending data to the cloud. Defenders should review the new feature in their Falcon console, enable the data classification policy, and monitor for classification alerts.
What Happened
CrowdStrike, in partnership with Intel, released a new on‑device AI feature for Falcon Data Security that classifies sensitive data in real time. The capability uses language models that run locally on dedicated AI hardware, eliminating the need to transmit data to external services.
Who Is Affected
Organizations that deploy Falcon Data Security as part of their endpoint protection stack will receive the update automatically. The feature is available for all Falcon Enterprise and Falcon XDR customers with the latest agent version (≥ 10.0).
Technical Details
- Language model: proprietary Falcon Data AI model optimized for on‑device inference.
- Hardware: Intel Xeon scalable processors with integrated AI acceleration (e.g., Intel® Xeon® Scalable Processor with Intel® Deep Learning Boost).
- Data types: PII, PHI, PCI‑DSS, GDPR‑protected data, and custom keyword lists.
- Policy integration: Classification results feed into Falcon Data Security policies and can trigger alerts, quarantines, or data‑loss‑prevention actions.
What to Do
- Verify that your Falcon agent is updated to the latest version and that the on‑device AI feature is enabled in the Data Security settings.
- Define or adjust classification policies to include the new data categories and set appropriate response actions.
- Review alert logs for classification events and validate that sensitive data is being correctly identified.
- Coordinate with compliance teams to ensure that the new classification rules align with internal data‑handling policies.
Benefits & Considerations
By keeping the inference on the endpoint, the feature reduces latency, preserves privacy, and lowers bandwidth usage. However, it requires that endpoints meet the hardware prerequisites; older CPUs without AI acceleration may not support the feature.
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