AWS Continuum: AI for Code Vulnerability Management

AWS Continuum for code vulnerabilities is now available in gated preview. This new system uses AI models to manage vulnerabilities from discovery to a fix. Here's the thing: It reasons over a customer’s environment, confirms real findings, and works towards resolution. What's interesting is it uses multiple AI models, assigning each to the task where it performs best. AWS designed it to incorporate newer models as they become available. Chet Kapoor, VP at AWS, notes that new cybersecurity models can find vulnerabilities and complex attack paths at machine speed, creating a growing backlog. Continuum operates in four phases. First, discovery, where it ingests existing backlogs and scans the environment for vulnerabilities. Next, prioritization, weighing findings against context like deployment status and business impact. Then, validation, filtering false positives and building exploit examples. Finally, mitigation and remediation, recommending changes like network adjustments or code patches. The system reasons over both structured data, like code, and unstructured data, such as documents and business priorities. It starts in a learn mode, with human review, and can move to an enforce mode for increased automation. This matters because it aims to streamline and automate the complex process of managing software vulnerabilities.