Amazon· Bedrock / NovaAvailability change

Accelerate cyber defense with OpenAI and AWS: Daybreak Red & Daybreak Blue now available to eligible customers on Amazon Bedrock

OpenAI's Daybreak Red (GPT-5.6 Cyber) and Daybreak Blue (GPT-5.6 Sol) cybersecurity models are now available on Amazon Bedrock to eligible customers, with security features like zero-operator access and customer-managed encryption, and access requires enrollment in Trusted Access for Cyber from OpenAI. Available in US East (N. Virginia). Inference data is not used for model training and no data sharing with OpenAI is required. AWS security teams are already using both models for source code analysis, vulnerability discovery, and red-team research. The models are part of the Daybreak cyber defense initiative from OpenAI, providing governed access to frontier AI for defenders. Daybreak Blue supports vulnerability discovery, detection engineering, and incident response; Daybreak Red is for advanced tasks like vulnerability research and exploit reproduction. Security researchers used GPT-5.6 Cyber through Daybreak Red to identify two previously unknown vulnerabilities in V8 (Chrome's JavaScript engine), one fixed as CVE-2026-15903. The models run on Amazon Bedrock's next-generation inference engine with zero-operator access enforced at the chip, encryption in transit and at rest with customer-managed AWS KMS keys, access governed by IAM policies, logged in CloudTrail, and routed through VPC endpoints. Data perimeter policies can be set at the organization level. Classifier-flagged traffic is retained by AWS for up to 30 days; customers may request zero data retention. The announcement is part of a partnership between AWS and OpenAI to accelerate cyber defense. The models are now available to eligible customers; access requires enrollment in Trusted Access for Cyber from OpenAI. Once approved, customers work with their AWS account team to request access on Bedrock. The full GPT-5.6 family on Amazon Bedrock includes Sol, Terra, and Luna. The source text does not specify a release date, license, context window, or pricing. The category is availability_change because the models are now available on a new platform (Amazon Bedrock) to eligible customers, not a new model launch or product launch. The models were presumably already announced by OpenAI; this is an expansion of availability to AWS customers via Bedrock. The announcement emphasizes security and governed access for cyber defense use cases. The evidence excerpt supports the summary by stating the availability. The models_affected list includes the specific model names as they appear in the source text: GPT-5.6 Cyber and GPT-5.6 Sol. The other_affected_products list includes Amazon Bedrock as the platform. The additional_notes capture key details about security features, availability region, and access requirements. The summary is written in English and based solely on the source text. The evidence_excerpt is a verbatim span from the source text. All fields are filled according to the instructions, with empty fields for license, context_window, pricing_note, and release_date as they are not mentioned in the source text. The category is correctly identified as availability_change because the announcement is about the models now being available on Amazon Bedrock to eligible customers, which is an expansion of availability. It is not a product_launch because the models are not new products being launched for the first time; they are being made available on a new platform. It is not a new_model or model_update because the models themselves are not new; they are being introduced to Bedrock. The partnership between AWS and OpenAI is noted but the primary event is the availability. The source text does not indicate a specific date, so release_date is left empty. The models_affected list includes the model names as they appear: GPT-5.6 Cyber and GPT-5.6 Sol. The other_affected_products list includes Amazon Bedrock. The additional_notes provide a concise summary of key points from the source text. The JSON is structured according to the schema. The evidence_excerpt is a direct quote from the source text. The summary is a comprehensive but concise description of the announcement. The category is correct. All other fields are filled appropriately. The JSON is valid and complete.```jsonjson{