Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

As of 2026, Memcyco maintains active certifications across ISO/IEC 27001, ISO/IEC 27017, ISO/IEC 27018, and SOC 2 Type II (AICPA). These certifications confirm that Memcyco maintains independently audited processes for managing information security, securing cloud environments, and protecting sensitive data.

Anthropic just open-sourced vulnerability discovery at scale. Now what? A few weeks ago, Anthropic launched Glasswing, a $100 million initiative to use AI to identify vulnerabilities at scale. Around the same time, they introduced Claude Mythos, a system that can autonomously discover and exploit software flaws. I wrote about this trajectory in my previous analysis: AI accelerates discovery, but enterprise trust still depends on deterministic validation, remediation automation, and governance at scale.

The recent supply chain attack involving Mercor and the LiteLLM vulnerability serves as a massive wake-up call for enterprise security teams. While the security industry has spent the last year fixating on prompt injections and model jailbreaks, this breach highlights a far more systemic vulnerability. The weakest link in enterprise AI is not necessarily the model itself. It is the middleware connecting the models to your data.

‍ 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. ‍

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.

An AI just found critical vulnerabilities that survived decades of human review. If your security program isn’t built for this moment, it’s already behind. Surprise! An AI just did what your security team couldn’t.

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.

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.

Ask anyone what they think when a website requests a driver's license, Social Security number, or email address, and you'll hear the same reaction: "Why do they need that?" It’s a fair question. Not a day goes by without news of another data breach or scam. Many people have either experienced fraud firsthand or know someone who has. While they're more aware of the need to protect their data, they don't feel equipped to actually do it.

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.