Artificial Intelligence (AI) is changing how individuals and organizations conduct many activities, including how cybercriminals carry out phishing attacks and iterate on malware. Now, cybercriminals are using AI to generate personalized phishing emails, deepfakes and malware that evade traditional detection by impersonating normal user activity and bypassing legacy security models. As a result,

Security teams have spent years building identity and access controls for human users and service accounts. But a new category of actor has quietly entered most enterprise environments, and it operates entirely outside those controls. Claude Code, Anthropic's AI coding agent, is now running across engineering organizations at scale. It reads files, executes shell commands, calls external APIs,

When a Magecart payload hides inside the EXIF data of a dynamically loaded third-party favicon, no repository scanner will catch it – because the malicious code never actually touches your repo. As teams adopt Claude Code Security for static analysis, this is the exact technical boundary where AI code scanning stops and client-side runtime execution begins. A detailed analysis of where Claude

Security teams today are not short on tools or data. They are overwhelmed by both.  Yet within the terabytes of alerts, exposures, and misconfigurations – security teams still struggle to understand context:  Q: Which exposures, misconfigurations, and vulnerabilities chain together to create viable attack paths to crown jewels? Even the most mature security teams can’t answer that

A majority of security leaders are struggling to defend AI systems with tools and skills that are not fit for the challenge, according to the AI and Adversarial Testing Benchmark Report 2026 from Pentera. The report, based on a survey of 300 US CISOs and senior security leaders, examines how organizations are securing AI infrastructure and highlights critical gaps tied to skills shortages and

If you run security at any reasonably complex organization, your validation stack probably looks something like this: a BAS tool in one corner. A pentest engagement, or maybe an automated pentesting product, in another. A vulnerability scanner feeding an attack surface management platform somewhere else. Each tool gives you a slice of the picture. None of them talks to each other in any

Disclaimer: This report has been prepared by the Threat Research Center to enhance cybersecurity awareness and support the strengthening of defense capabilities. It is based on independent research and observations of the current threat landscape available at the time of publication. The content is intended for informational and preparedness purposes only. Read more blogs around threat

Phishing has quietly turned into one of the hardest enterprise threats to expose early. Instead of crude lures and obvious payloads, modern campaigns rely on trusted infrastructure, legitimate-looking authentication flows, and encrypted traffic that conceals malicious behavior from traditional detection layers. For CISOs, the priority is now clear: scale phishing detection in a way that helps

The most dangerous phishing campaigns aren’t just designed to fool employees. Many are designed to exhaust the analysts investigating them. When a phishing investigation takes 12 hours instead of five minutes, the outcome can shift from a contained incident to a breach. For years, the cybersecurity industry has focused on the front door of phishing defense: employee training, email gateways that

“You knew, and you could have acted. Why didn’t you?”  This is the question you do not want to be asked. And increasingly, it’s the question leaders are forced to answer after an incident. For years, many executive teams and boards have treated a large vulnerability backlog as an uncomfortable but tolerable fact of life: “we’ve accepted the risk.” If you’ve ever seen a report showing

Artificial Intelligence (AI) is no longer just a tool we talk to; it is a tool that does things for us. These are called AI Agents. They can send emails, move data, and even manage software on their own. But there is a problem. While these agents make work faster, they also open a new "back door" for hackers. The Problem: "The Invisible Employee" Think of an AI Agent like a new employee who has

You can't control when the next critical vulnerability drops. You can control how much of your environment is exposed when it does. The problem is that most teams have more internet-facing exposure than they realise. Intruder's Head of Security digs into why this happens and how teams can manage it deliberately. Time-to-exploit is shrinking The larger and less controlled your attack surface is,

Mid-market organizations are constantly striving to achieve security levels on a par with their enterprise peers. With heightened awareness of supply chain attacks, your customers and business partners are defining the security level you must meet. What if you could be the enabler for your organization to remain competitive — and help win business — by easily demonstrating that you meet these

Scaling cybersecurity services as an MSP or MSSP requires technical expertise and a business model that delivers measurable value at scale. Risk-based cybersecurity is the foundation of that model. When done right, it builds client trust, increases upsell opportunities, and drives recurring revenue. But to deliver this consistently and efficiently, you need the right technology and processes.

Most organizations assume encrypted data is safe. But many attackers are already preparing for a future where today’s encryption can be broken. Instead of trying to decrypt information now, they are collecting encrypted data and storing it so it can be decrypted later using quantum computers. This tactic—known as “harvest now, decrypt later”—means sensitive data transmitted today could become

Organizations typically roll out multi-factor authentication (MFA) and assume stolen passwords are no longer enough to access systems. In Windows environments, that assumption is often wrong. Attackers still compromise networks every day using valid credentials. The issue is not MFA itself, but coverage.  Enforced through an identity provider (IdP) such as Microsoft Entra ID, Okta, or

As AI becomes the central engine for enterprise productivity, security leaders are finally getting the green light — and the budget — to secure it. But there’s a quiet crisis unfolding in the boardroom: many organizations know they need "AI Governance," but they have no idea what they are actually looking for. The CISO’s Dilemma: You Have the AI Budget, but Do You Have the Requirements? As AI

Every CISO knows the uncomfortable truth about their Security Operations Center: the people most responsible for catching threats in real time are the people with the least experience. Tier 1 analysts sit at the front line of detection, and yet they are also the most vulnerable to the cognitive and organizational pressures that quietly erode SOC performance over time. The Paradox at the Gate:

The Rise of MCPs in the Enterprise The Model Context Protocol (MCP) is quickly becoming a practical way to push LLMs from “chat” into real work. By providing structured access to applications, APIs, and data, MCP enables prompt-driven AI agents that can retrieve information, take action, and automate end-to-end business workflows across the enterprise. This is already showing up in production

Most SaaS teams remember the day their user traffic started growing fast. Few notice the day bots started targeting them. On paper, everything looks great: more sign-ups, more sessions, more API calls. But in reality, something feels off: Sign-ups increase, but users aren’t activating. Server costs rise faster than revenue. Logs are filled with repeated requests from strange user agents. If