Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Risk management is evolving at a pace that compels organizations to adopt more advanced technologies. Among these, artificial intelligence is emerging as a leading force in transforming internal oversight practices, particularly in the realm of first-party risk management. The need to manage risks that originate within the organization has prompted leaders to reevaluate and innovate traditional strategies, making AI an indispensable component of modern risk frameworks.

We once had a mid-market fintech client come to us in the middle of a SOC 2 renewal panic. Their CTO described it as “death by screenshot” – a desperate scramble to gather Slack threads, access logs, and onboarding spreadsheets just to satisfy the auditor’s checklist. They had the right policies. They had the right intentions. What they didn’t have was time.

Data loss prevention, or DLP as most of us know it, began as a strategy to control how information was stored and moved within organizations. Ultimately the goal was to prevent data from leaving. The premise was simple – identify where sensitive data was stored, define what could or couldn’t happen to it, and enforce those rules through network and endpoint controls. These early DLP tools relied heavily on static content inspection and then blocking or alerting based on pre-configured rules.

Machine identities have quietly become the backbone of digital infrastructure, outnumbering human users in most enterprise environments. While they don’t forget passwords or call tech support, they do introduce a unique set of security and operational risks. Unlike human users, machine identities (like service accounts, API keys, bots, and microservices) often operate with highly permissive access rights and weak or nonexistent authorization policies.

Running an online apparel business is exciting, but as your store grows, so does the complexity behind the scenes. More suppliers. More products. More variants.

The healthcare sector continues to be a prime target for cyber adversaries, with threat actors constantly evolving their tactics to exploit vulnerabilities. Over the past year, CrowdStrike Services responded to a growing number of financially motivated attacks aimed at encrypting data and extorting victims across the healthcare ecosystem.

Organizations waste enormous amounts of time chasing down security alerts that turn out to be nothing. Recent research from May 2025 shows that 70% of a security team's time is spent investigating alerts that are false positives, wasting massive amounts of time in the investigation rather than working on proactive security measures to improve organizational security posture.