Automate AppSec Triage With Machine Learning eBook

Applying machine learning to AppSec triage

One of the most significant problems facing application security (AppSec) teams is the amount of time it takes to manage the results returned from automated testing tools. Tests may return thousands of potential vulnerabilities, but most AppSec professionals know that only a small fraction of them are worth the time and effort to remediate. AppSec teams comb through these results and triage them—flagging the ones that should be fixed and weeding out the false positives. This process is extraordinarily time-consuming, repetitive, and tedious—but necessary.

Identifying exploitable vulnerabilities is important, and adopting SAST and DAST tools are proven ways of doing so. At the same time, development teams are dealing with constantly shortening deadlines for delivering new functionality. Even moderate levels of issues, false positives, and insignificant results that don’t warrant remediation can prevent developers from adopting these testing tools.

This eBook takes you through how Machine Learning offers a solution to this problem and how Synopsys implements machine learning that can be applied to automate the triage process and examines solutions already on the market.

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