Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The Future Is Cyber Risk Intelligence

Risk is expanding faster than most organizations can measure it, communicate it, and act on it. The convergence of AI, an ever-expanding attack surface, and deep, often hidden supply chain risks—extending into third-, fourth-, and fifth-party connections—all pose strategic and material risks to companies. Security leaders are ultimately looking for better ways to identify risk, prioritize action, and support stronger risk decisions across the entire business ecosystem.

The NVD Funding Crisis Was Bigger Than Mythos

Everyone is calling Claude Mythos a watershed moment. I’d like to offer a slightly different take. Not because the capability isn’t real, it is. But if Mythos is the moment that finally convinced your organization that rapid vulnerability discovery is an existential threat, you’ve been watching the wrong thing. We saw this coming. Vulnerability Management has been moving in this direction for years, and we built Nucleus with this trajectory in mind. What surprises me is the surprise.

New Data Shows Why Security Teams Can't Keep Up With AI-Driven Attacks

AI is changing how attacks happen, and how fast they happen. Seemplicity’s 2026 State of Exposure Management report shows why most security teams aren’t struggling to find risk, but to fix it quickly enough. Based on insights from 300 security leaders, it highlights where remediation breaks down, how AI is being used today, and why execution is becoming the real bottleneck.

Sybil Attacks Explained: How They Work and Why They Matter

Sybil attacks are well documented in academic research. In practice, most organizations discover them too late, after the fake identities have already accumulated enough network influence to do real damage. The attack does not announce itself. It looks like growth. You see more nodes. More accounts. More participation. All of it is controlled by one attacker running a coordinated identity flood.

From Plaintext, to BLESS, to Identity: The Evolution of Secure Remote Access

My first introduction to UNIX remote access was via telnet and rsh protocols in college, which was the standard method at the time. But I soon started reading articles about how easy it was for someone to sniff the network and capture passwords since they were being transmitted in plaintext. On the shared network segments common to university campuses and early enterprise environments, the tools to intercept traffic were freely available, well-documented, and required very little skill to use.

Evil Token: AI-Enabled Device Code Phishing Campaign

On April 6, 2026, Microsoft Defender Security Research published an advisory detailing a large-scale phishing campaign that leverages the OAuth Device Code Authentication flow to compromise Microsoft 365 accounts across organizations globally. This campaign represents a significant evolution from manual social engineering to fully automated, AI-driven attack infrastructure.

Complete Guide to Patch-in-Place SCA Remediation

A definitive guide to how automated and human-reviewed patch-in-place remediation solves both direct and transitive open source vulnerabilities - without forcing risky upgrades. Learn why traditional tools miss transitive risk, and how to evaluate modern platforms based on SLA, provenance, and CI/CD fit.

What makes One Identity an Overall Leader in SAP access control

SAP environments, especially in the age of cloud work and hybrid infrastructures, are ripe with security complications. But SAP support and security is nothing to scoff at. Access controls alone in SAP environments require compliance capabilities for ultimate security, regardless of the security solution or deployment scenario.

AI Governance and Risk: Expert Insights for Enterprise Leaders

‍ As GenAI tools become embedded in core business operations, the governance programs meant to oversee them are still catching up. Closing that gap requires visibility into where AI operates and the ability to express exposure in financial terms that leadership can act on. The organizations best positioned to manage AI risk are those that have already started treating it as a measurable business variable rather than an abstract operational concern. ‍