Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

A browser sensor reports that somebody pasted 18,000 characters into an AI tool. A network sensor reports a 24 kilobyte upload to the same destination. Joining those two records on size looks reasonable and is the wrong instinct. ‍ The two numbers describe different objects with several transformations between them, and the transformations do not all run in the same direction. The error cannot even be signed, which rules out a tolerance as well as an equality. ‍

Since joining BlueVoyant in May, I’ve spent my first 100 days listening. I've had conversations with nearly 50 customers and partners across industries and geographies, as well as the broader security industry, engaging with leaders at Black Hat last month. What I heard reinforced something I believe strongly: the security challenges organizations face today are changing faster than the traditional enterprise security model was designed to handle.

CrowdStrike Counter Adversary Operations identified a financially motivated threat actor who works as a bug bounty hunter and who developed and distributed the JavaScript (JS)-based information stealer PhantomRaven via npm, a platform on which developers can access open-source packages to build applications and software.

Tines co-founder and COO Thomas Kinsella recently joined Peter High on the Technovation podcast to talk about the evolution of Tines, the rise of "wild code," and why agents aren’t always the right tools for the job. The conversation covered a lot of ground — from the original problem that inspired Tines, to how teams should think about combining AI agents, deterministic automation, and humans in a single workflow. Here, we’ll share some of the highlights.

For the past year, I've described this as an AI fog: competing claims, uncertain risks, and leaders struggling to see what mattered. The winds are up now. AI is accelerating software creation, exposing years of accumulated vulnerabilities, and handing both attackers and defenders capabilities that operate at machine speed.

Anthropic CEO Dario Amodei published an essay this month called “We Must Pace the Frontier.” His argument is straightforward, calling out the reality that AI capabilities are advancing faster than the industry’s ability to align and safeguard them, and frontier labs need to slow the rate of capability growth long enough for safety work, alignment, and interpretability to catch up. He points to two developments behind his concern.

Every security team knows the feeling. The quarterly vulnerability scan completes. The report lands, with thousands of findings, color-coded by CVSS severity, neatly timestamped. And the moment it’s printed, it’s already out of date. That is the fundamental flaw at the heart of traditional exposure management: it is built around a point in time.