Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

It's 11:40 am. A security questionnaire just hit your inbox. You open the file and quickly realize you can't finish this alone. Legal needs to review the data processing language. Product has to complete the architecture section. Security is the only team that can sign off on incident response. So you split up the questionnaire, Slack each department their section to answer, and wait... and wait... and wait.

AI security is entering a more demanding phase. The market is moving beyond who can add AI to a product and toward who can make it useful in the real world — across existing security environments, partner ecosystems, and day-to-day operations. CRN’s 2026 Annual Report Card offers a useful snapshot of that shift. In the AI Security category, Exabeam earned the top overall score at 90.6, leading all four subcategories and every one of the 21 individual evaluation criteria.

Six new security issues for every one issue remediated. That's the ratio Snyk research has found, and it's why the AI Security Engineers Community gave an hour of livestream time to fixing rather than finding. Play Video: Remediation Agents Demystified: Your AI Teammate for Fixing Security Bugs Remediation Agents Demystified paired a fireside chat with a live demo.

Keeper Security, the leading zero-trust and zero-knowledge identity security platform, today announces the availability of a certified connector integrating Keeper Secrets Manager with Microsoft Azure Logic Apps. The connector, now published on the Microsoft Power Platform marketplace, enables enterprise teams to create and retrieve credentials at runtime directly within automated workflows without ever hardcoding sensitive values in flows.

AI-accelerated attacks are redefining the threat landscape, but many of them still rely on one of the oldest tactics in the book: exploiting known vulnerabilities. The difference today is speed. Vulnerabilities that once took skilled hackers months or weeks to exploit can now be weaponized in hours or minutes. This acceleration is forcing organizations to rethink how they identify and remediate risk.

Shadow AI is the use of generative AI tools by employees without the knowledge, approval or oversight of an organization's IT or security teams.

Browser-layer AI monitoring produces events, and the natural next step is forwarding them to the security operations center. Consider what they arrive into. Industry research for 2026 puts false positives at close to half of all alerts, with around forty-two percent going entirely uninvestigated. ‍ Browser AI events are behavioral anomaly alerts, and behavioral anomaly alerts are the category analysts already deprioritize, precisely because they are noisy by nature.

Healthcare carries the highest average breach cost of any industry and has for well over a decade, and it operates under a rule that has required risk analysis since 2003. Those two facts sit uncomfortably together, and federal regulators have started saying why. ‍ Enforcement has moved from asking whether an organization performed a risk analysis to asking what it did about the findings.

An AI governance framework tells a financial institution to inventory its systems, assess risk and document decisions. Consumer protection law tells it something different and considerably harder, which is that a model unable to produce specific reasons for a credit denial cannot lawfully be used to make one. ‍ That distinction is what separates AI governance in financial services from AI governance generally.

Black Hat USA 2026 wrapped in Las Vegas with a clear verdict: the industry has stopped debating whether AI changes the threat landscape and started building for the fact that it already has. Nearly a third of the conference's briefings dealt directly with AI security, agent exploitation, or LLM-assisted offensive research — and the conversations happening in partner meetings and dinners around the show floor tracked right alongside it.