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In the ever-evolving world of cybersecurity, staying ahead of malicious campaigns is crucial for developers. Recently, security firm Koi released eye-opening research on a sophisticated malware operation they've named "PhantomRaven." This campaign exploits "Remote Dynamic Dependencies" (RDDs) in NPM packages to hide and deploy malware invisibly.

Just look at the numbers – IBM's latest report pegs the average data breach cost at a whopping $4.44 million worldwide, with U.S. companies getting slammed the hardest. And it's not just about the money; throw in downtime, lawsuits, and hefty fines, and you've got a recipe for disaster.

As software and artificial intelligence (AI) systems become foundational to national infrastructure, the security of their supply chains has emerged as a critical concern.

Traditional RMF is too slow for today's threats. NR Labs' modular, AI-driven approach enables continuous cyber resilience through automation, real-time monitoring, and seamless integration—proven in federal deployments.

While tools are critical, over-reliance on them without addressing underlying issues is like putting a bandage on a broken bone. In this post, we’ll share insights from our collective experience implementing robust security strategies for cloud and AI systems, emphasizing the need to fix root causes over leaning solely on tools.

At NR Labs, our team of cybersecurity specialists conducts rigorous penetration testing (pentesting) and threat analysis for organizations worldwide. We've observed and mitigated numerous exploits in Microsoft environments, and the recent global attack on SharePoint servers underscores a persistent risk we've encountered repeatedly.