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About
Senior Software Engineer specializing in cybersecurity, AI-powered detection, and large-scale cloud infrastructure, with over 10 years of industry experience across Microsoft and Amazon Web Services. I design and deliver production-grade security platforms for software supply chain protection across ecosystems such as NPM, Visual Studio etc, and cloud security pipelines for Azure. My work focuses on low-latency distributed decision systems, horizontally scalable processing architectures, and resilient release-gate mechanisms for high-risk artifacts in enterprise environments.
Nirwan Dogra
Published content
expert panel
Artificial intelligence has fundamentally changed cybersecurity—not just for defenders but also for attackers. AI can now generate convincing phishing campaigns, rapidly mutate malware and automate reconnaissance at a scale that would have required large teams only a few years ago. As attack velocity accelerates, many organizations are discovering that even mature detection and response capabilities struggle to keep pace.That shift is forcing security leaders to rethink longstanding assumptions. Members of the Senior Executive Cybersecurity Think Tank, a community of experienced cybersecurity executives and practitioners, argue that future-ready organizations will succeed not by responding faster, but by preventing more attacks from succeeding in the first place.According to IBM's Cost of a Data Breach Report, organizations that combine AI-driven security with proactive risk reduction significantly reduce both breach costs and response times, reinforcing the business value of moving security "left" before attackers gain a foothold.Below, Think Tank members share practical strategies for moving beyond reactive security, highlighting the technologies, processes and leadership mindset needed to stay ahead of these AI-powered threats.