Data AnalysisAugments Human LaborVerified
Reviewed and published by trentmaziarz, March 18, 2026. Discovered and drafted by our automated research pipeline.
Amazon GuardDuty is AWS's cloud security service that uses AI and machine learning to automatically monitor customer cloud environments for hacking attempts, credential theft, malware, and multi-step cyberattacks. It processes billions of signals at once and alerts security teams to critical threats without human review of every event.
Details
GuardDuty Extended Threat Detection uses artificial intelligence and machine learning algorithms trained at AWS scale and automatically correlates security signals from across AWS services to detect critical threats, including attack sequences such as credential compromise followed by data exfiltration. This capability launched in general availability in December 2024 and is automatically enabled at no additional cost for all GuardDuty customers. GuardDuty is capable of analyzing tens of billions of events across multiple AWS data sources, including AWS CloudTrail logs, Amazon VPC Flow Logs, and DNS logs.
Products affected
Amazon GuardDutyAWS Security Hub
Sources & Evidence
Company Disclosure
Other practices by AWS (Amazon Web Services)
OtherAWS has embedded AI agents directly into its security tooling, including a service that automatically reviews application code for vulnerabilities throughout the development process and another that accelerates incident investigation and response. These services allow security teams to scale their threat-response work without proportionally growing headcount.ModerationAmazon Rekognition is an AWS service that other businesses license to automatically scan images and videos for inappropriate content — including explicit material, violence, hate symbols, drugs, and gambling. It allows platforms with large amounts of user-generated content to flag unsafe material before a human ever sees it.Data AnalysisAmazon SageMaker is AWS's unified platform for data scientists and engineers to build, train, and deploy machine learning models at enterprise scale. It allows organizations to run predictive analytics, anomaly detection, and AI-driven insights across massive datasets without managing the underlying infrastructure.
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