Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Editor's note: This guest article by Tanium Senior Sirector, Product Management, Julia Grunewald was originally published in SC Media Exposure management has emerged as a powerful alternative to traditional vulnerability management for good reason. A proactive, always‑on security discipline that continuously identifies an organization’s exposures and prioritizes them based on risk helps us know where to best focus our limited resources.

Maxime Lamothe-Brassard, founder and CEO of LimaCharlie, sought answers on AI’s current capabilities in the SecOps space. Plenty of benchmarks exist to test AI's knowledge of cybersecurity, but none test whether a model actually does the work. There's a significant difference between an AI that can answer trivia questions about CVEs and one that can pick up an alert, investigate it, and produce an incident report.That gap matters more now than ever.

If you’ve been in security operations for more than a few years, you’ve lived through the automation hype cycle at least twice. First, it was SIEM that was going to solve everything. Then SOAR was supposed to fix what SIEM couldn’t. Now, AI SOC platforms are delivering what SOAR always promised but never actually could.

A blanket “no AI” policy is not the answer for most organizations. Prohibiting something people find genuinely useful just drives it further underground.

CMMC enforcement is here. With DFARS clauses 7021 and 7025 now active across the defense industrial base (DIB), contractors face enforceable obligations that extend beyond prime contractors to every tier of the supply chain. While primes have received significant attention, subcontractors encounter distinct challenges in managing CMMC risk from pre-award decisions through contract execution and ongoing compliance maintenance.

Most security teams are being asked to "enable AI" before they have any real sense of which tools are safe to use. That gap is costing them. Cyberhaven's research found that the majority of AI tools in active enterprise use today fall into high or critical risk categories, and more than 80% of enterprise data flowing into AI is going to those risky tools, not to platforms built with serious security in mind. To help security teams cut through the noise, we built the Cyberhaven AI App Risk Checker.

The automotive industry is changing faster than ever, with smarter factories, connected vehicles, digital supply chains, and software-driven everything. But as the industry accelerates into this new era, something else is racing alongside it: cyber threats. Over the past year, Bitsight Threat Intelligence data has shown a sharp rise in ransomware activity targeting companies across the auto ecosystem. And what’s striking is how often the same names keep appearing.

Today, we’re launching System Prompt Hardening, Mend.io’s new capability that defends the hidden instructions that control how your AI systems behave. Unlike user-facing prompts, system prompts live behind the scenes, and when attackers manipulate them, the result can be data leaks, policy bypasses, or unsafe model behavior. System prompt hardening stops those attacks at the source and gives security, engineering, and risk teams a practical, auditable way to secure AI in production.

Law firm economics are unforgiving. According to the Clio Legal Trends Report, the average attorney bills only 2.5 hours per 8-hour workday. When IT systems fail, that already-thin margin disappears entirely. Consider a 20-attorney firm with average billing rates of $350 per hour.

OAuth and OpenID Connect are the backbone of modern cloud-native identity and access management. From SaaS platforms and internal APIs to Kubernetes microservices, these protocols are responsible for verifying who is allowed to access what. When a vulnerability appears in a widely used authentication library, the impact can cascade across entire application ecosystems.