On December 4, 2025, a 17-year-old was arrested in Osaka under Japan’s Unauthorized Access Prohibition Act. The young man had run malicious code to extract the personal data of over 7 million users of Kaikatsu Club, Japan's largest internet cafe chain. When asked, the young man shared his motivation for the hack: he wanted to buy Pokémon cards. In a sense, this is a fairly conventional story.

The managed security services market is projected to grow from $38.31 billion in 2025 to $69.16 billion by 2030[1], with cybersecurity being the fastest-growing sector[2]. Despite this opportunity, many MSPs leave revenue on the table because their go-to-market strategy fails to connect technical expertise with business needs. This execution gap is where most deals stall. MSPs often focus on

Intro A sophisticated, high-resilience malicious campaign was identified by Atos Threat Research Center (TRC) in March 2026. This operation specifically targets the high-privilege professional accounts of enterprise administrators, DevOps engineers, and security analysts by impersonating administrative utilities they rely on for daily operations. By integrating Search Engine Order (SEO)

In February 2026, researchers uncovered a shift that completely changed the game: threat actors are now using custom AI setups to automate attacks directly into the kill chain. We aren't just talking about AI writing better phishing emails anymore. We’re talking about autonomous agents mapping Active Directory and seizing Domain Admin credentials in minutes. The problem? Most defensive workflows

Every security program is betting on the same assumption: once a system is connected, the problem is solved. Open a ticket, stand up a gateway, push the data through. Done. That assumption is wrong. It is also a major reason Zero Trust programs stall. New research my team just published puts numbers on it. The Cyber360: Defending the Digital Battlespace report, based on a survey of 500 security

When patching isn’t fast enough, NDR helps contain the next era of threats. If you’ve been tracking advancements in AI, you know the exploit window, the short buffer that organizations relied on to patch and protect after a vulnerability disclosure, is closing fast. Anthropic’s new model, Claude Mythos, and its Project Glasswing, showed that finding exploitable vulnerabilities and subtle cracks

Anthropic’s Claude Mythos Preview has dominated security discussions since its April 7 announcement. Early reporting describes a powerful cybersecurity-focused AI system capable of identifying vulnerabilities at scale and raising serious questions about how quickly organizations can validate, prioritize, and remediate what it finds. The debate that followed has mostly focused on the right

The AI Agent Authority Gap - From Ungoverned to Delegation As discussed in our previous article, AI agents are exposing a structural gap in enterprise security, but the problem is often framed too narrowly. The issue is not simply that agents are new actors. It is that agents are delegated actors. They do not emerge with independent authority. They are triggered, invoked, provisioned, or

Imagine a world where hackers don't sleep, don't take breaks, and find weak spots in your systems instantly. Well, that world is already here. Thanks to AI, attackers are now launching automated, large-scale exploits faster than ever before. The time you have to fix a vulnerability before it gets attacked is shrinking to zero. We call this the Collapsing Exploit Window, and it means your

Last week, Anthropic announced Project Glasswing, an AI model so effective at discovering software vulnerabilities that they took the extraordinary step of postponing its public release. Instead, the company has given access to Apple, Microsoft, Google, Amazon, and a coalition of others to find and patch bugs before adversaries can. Mythos Preview, the model that led to Project Glasswing, found

On January 31, 2026, researchers disclosed that Moltbook, a social network built for AI agents, had left its database wide open, exposing 35,000 email addresses and 1.5 million agent API tokens across 770,000 active agents. The more worrying part sat inside the private messages. Some of those conversations held plaintext third-party credentials, including OpenAI API keys shared between agents,

Security teams often present MTTR as an internal KPI. Leadership sees it differently: every hour a threat dwells inside the environment is an hour of potential data exfiltration, service disruption, regulatory exposure, and brand damage.  The root cause of slow MTTR is almost never "not enough analysts." It is almost always the same structural problem: threat intelligence that exists

The cybersecurity industry has spent the last several years chasing sophisticated threats like zero-days, supply chain compromises, and AI-generated exploits. However, the most reliable entry point for attackers still hasn't changed: stolen credentials. Identity-based attacks remain a dominant initial access vector in breaches today. Attackers obtain valid credentials through credential stuffing

The fastest way to fall in love with an AI tool is to watch the demo. Everything moves quickly. Prompts land cleanly. The system produces impressive outputs in seconds. It feels like the beginning of a new era for your team. But most AI initiatives don't fail because of bad technology. They stall because what worked in the demo doesn't survive contact with real operations. The gap between a

In 2024, compromised service accounts and forgotten API keys were behind 68% of cloud breaches. Not phishing. Not weak passwords. Unmanaged non-human identities that nobody was watching. For every employee in your org, there are 40 to 50 automated credentials: service accounts, API tokens, AI agent connections, and OAuth grants. When projects end or employees leave, most

A bank approved a Taboola pixel. That pixel quietly redirected logged-in users to a Temu tracking endpoint. This occurred without the bank’s knowledge, without user consent, and without a single security control registering a violation. Read the full technical breakdown in the Security Intelligence Brief. Download now → The "First-Hop Bias" Blind Spot Most&

Few technologies have moved from experimentation to boardroom mandate as quickly as AI. Across industries, leadership teams have embraced its broader potential, and boards, investors, and executives are already pushing organizations to adopt it across operational and security functions. Pentera’s AI Security and Exposure Report 2026 reflects that momentum: every CISO surveyed

OX Security recently analyzed 216 million security findings across 250 organizations over a 90-day period. The primary takeaway: while raw alert volume grew by 52% year-over-year, prioritized critical risk grew by nearly 400%. The surge in AI-assisted development is creating a "velocity gap" where the density of high-impact vulnerabilities is scaling faster than

Anthropic restricted its Mythos Preview model last week after it autonomously found and exploited zero-day vulnerabilities in every major operating system and browser. Palo Alto Networks' Wendi Whitmore warned that similar capabilities are weeks or months from proliferation. CrowdStrike's 2026 Global Threat Report puts average eCrime breakout time at 29 minutes. Mandiant's M-Trends

While much of the discussion on AI security centers around protecting ‘shadow’ AI and GenAI consumption, there's a wide-open window nobody's guarding: AI browser extensions.  A new report from LayerX exposes just how deep this blind spot goes, and why AI extensions may be the most dangerous AI threat surface in your network that isn't on anyone's