Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Something fundamentally shifted in cybersecurity. Claude Mythos, Anthropic’s frontier AI model, signaled the arrival of what the Cloud Security Alliance called an “AI vulnerability storm,” a world where vulnerabilities are discovered and exploited at machine speed. This is a compression event, collapsing timelines, expanding attack surfaces, and forcing a rewrite of how organizations think about security operations, software development, risk, and ultimately, business survival.

Another ping. And another. Employees are urgently logging IT tickets, trying to figure out why their trusted SaaS writing assistant subscription has expired. Meanwhile, your InfoSec team is frantically looking through the avalanche of alerts across the network, scouring vendor policies, and digging into procurement records to determine exactly when the organization provisioned this SaaS tool. Spoiler alert: The organization didn’t.

Residential proxy services, also called RESIP, present a persistent operational hurdle for tracking and attributing malicious network activity, as they allow threat actors to mask their true origins behind seemingly benign, geographically diverse IP addresses. While often marketed for legitimate use cases, these networks are aggressively leveraged for fraud, credential abuse, and perimeter evasion.

Your risk committee meets Thursday. The agenda has a new item: AI agent risk posture. You open the register. The fraud detection agent shipped in March is on it. So is the customer service agent. Neither row is useful — “likelihood: medium, impact: high, control: service account scoped via IAM.” Three months ago that was approximately right. Last week the platform team added two MCP connections, the model was upgraded, and the agent now touches data classes the entry never anticipated.

In May 2025, a developer using Claude with the GitHub MCP server asked their AI assistant to do something entirely routine: review the open issues in a public repository. The repository contained a malicious GitHub issue planted by a researcher demonstrating a security vulnerability. The issue contained hidden instructions. The AI read them, followed them, accessed the developer's private repositories, and posted the contents in a publicly visible pull request. No credentials were stolen.

I’ve spent a lot of time recently thinking about what "innovation" actually means in an industry that moves as fast as cybersecurity. It’s a term that gets thrown around a lot, but as a product leader at Bitsight, I see it as something much deeper than just shipping new features. It's about a fundamental shift in how we help organizations stay resilient.

Artificial intelligence is rapidly becoming embedded across manufacturing environments, from engineering and design to supply chain optimisation and operations. What was once experimental is now being applied in day-to-day workflows, often driven by the need for speed, efficiency, and competitive advantage. Recent research shows that 73% of manufacturing organisations report rapid AI adoption, with 90% ranking AI as a top security priority for 2026. The direction of travel is clear.