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Check Point uses OpenAI Daybreak to cut vulnerability research time

Check Point has integrated OpenAI's Daybreak platform into its vulnerability research workflow, significantly reducing the time required to analyze security threats. According to Jonathan Zanger, Check Point's CTO, the process that previously took hours now takes minutes. This acceleration allows the company to translate new vulnerability intelligence into customer defenses more rapidly.

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Key points

  • Check Point reduces vulnerability research time from hours to minutes using OpenAI Daybreak.
  • Daybreak models analyze vulnerabilities, attack paths, and code gaps to speed up defense creation.
  • Check Point is developing an Agentic Network Security Orchestration solution with OpenAI.

Daybreak provides access to OpenAI's frontier cyber models, which analyze vulnerabilities, reason through attack paths, and identify gaps in code and configurations. Check Point, which secures over 100,000 organizations, uses these capabilities to automate parts of its expert-led research. The models help analysts understand complex code and identify how systems might be exposed to attacks, enabling the faster development of security signatures and indicators of compromise.

Beyond immediate research, Check Point is collaborating with OpenAI to develop an Agentic Network Security Orchestration solution. This future approach aims to combine continuous monitoring with human approval for significant actions, allowing customers to set security objectives while the system explains findings and risks. The company views this as a step toward more autonomous defenses that can prevent threats in real time.

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How Check Point accelerates vulnerability research with Daybreak

OpenAI · 21 October 2026

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This text was published by OpenAI. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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