In an age where digital products are evolving every hour, cybersecurity must evolve just as fast. The rise of sophisticated cyber threats has placed product security management at the forefront of engineering priorities. As building new products and services, businesses are working on software faster than ever and integrating machine learning is no longer a luxury, it’s a necessity.
Rushil Shah, Security Engineering Lead at Intrinsic and a Certified Information Systems Security Professional (CISSP), believes the next big move in cybersecurity will definitely be in building intelligent, scalable systems that proactively identify and prioritize threats in time. “Traditional penetration testing is still important, but the kinds of threats we face today require security methods that are more intelligent, faster, and work all the time, not just occasionally,” says Rushil.
Artificial intelligence in Product Security
Tools that with Artificial intelligence can be used to scale product security threat models and vulnerability detection. While traditional setups and tools can flag issues based on preset rules, innovative use of Large language models and machine learning can be used to detect novel patterns, recognize false positives and even help with remediation of security issues.Rushil, a judge at the Globee Awards for Disruptors, “Artificial intelligence helps us move from reactive to proactive security. Instead of waiting and manually finding issues, we can detect them early on and prevent them in advance.”
Critical Risk Focus
One of the biggest challenges in product security engineering isn’t just detecting vulnerabilities, it’s knowing which ones matter most.Rushil who is a Senior Member of IEEEshared, “Not all security issues are equally serious. A major flaw in a system used by customers’ needs to be fixed right away, while a less serious issue in an internal tool may not be as urgent. Machine learning helps us understand the context of each issue and focus on the ones that are more likely to be exploited and use our time and resources more effectively.”
Boosting Workflow Efficiency
Secure development lifecycle management improves workflow efficiency. Instead of giving developers security recommendations after the product is built, security teams now use tools and processes that catch issues early while design, development, testing, or deploying, making the process smoother and faster.A contributor of scholarly articles at Sarcouncil Journal of Applied Sciences Rushil stated, “We’re bringing security earlier into the development process. By adding security scanning and vulnerability detection directly into the build and deployment steps, developers can fix issues faster when it’s easier and less costly to do so”.
