SEC595: Applied Data Science and AI/Machine Learning for Cybersecurity Professionals

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Contact UsYear after year, attackers target application-level vulnerabilities. To address these vulnerabilities, application security teams have increasingly focused on shifting left - identifying and fixing vulnerabilities earlier in the software development life cycle. However, at the same time, development and operations teams have been accelerating the pace of software release, moving towards continuous delivery. As software is released more frequently, gaps remain in test coverage leading to the introduction of vulnerabilities in production. To prevent these vulnerabilities from being exploited, it is necessary that applications become self-defending. RASP is a means to quickly make both new and legacy applications self-defending. However, because most applications are custom-coded and therefore unique, RASP is not one-size-fits-all - it must be trialed to ensure that it meets performance and attack protection goals. In addition, RASP integrates with critical applications, whose stakeholders typically span the entire organization. To convince these varied stakeholders, it is necessary to both prove the benefits and show that RASP does not adversely affect application performance or stability. This paper helps organizations that may be evaluating a RASP solution by outlining activities that measure the effectiveness and performance of a RASP solution against a given application portfolio.