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Somewhere right now, malware running on a compromised machine is checking in with an AI model, asking it for a new version of itself. Google's Threat Intelligence Group caught this happening in late 2025. The malware, nicknamed PROMPTFLUX, does this every hour it runs, and each version comes back looking different from the last. By the time a security tool learns to recognize it, it has already changed shape again. This isn't a rare glitch or a lab experiment. It's a preview of how a growing share of attacks work today and why legacy SIEM platforms built to detect known patterns are starting to fall behind. Legacy security tools were built to detect, not to adapt A SIEM is a system that collects logs from every part of a company's network and looks for signs of an attack. For years, it worked like a security guard with a very long memory. The guard learns what a break-in looks like - a certain kind of file, a pattern of behavior, a code signature, and watches fo...

We had an enterprise customer tell us their entire AI footprint was Copilot. That was the whole answer. One tool, one line item, done. We ran the first scan. Copilot wasn't even close to number one. Claude was. OpenAI came in second. Copilot was third. Nobody on the security team knew because Claude doesn't show up the way a SaaS app used to show up. There's no single login screen, no single admin console, no one place to look. That's the part most security teams miss. Claude isn't one surface. It's six. The six places Claude actually runs Claude Enterprise and Connected Apps. This is the surface everyone pictures: employees typing into Claude, OAuth'd into Google Drive, GitHub, Slack, and Jira, asking Claude to act on what's inside. The audit log shows that a connection happened. It does not show what got pulled into the prompt or what came back out. A finance analyst can drop a quarter of board materials into a conversation in ten second...

When I work on an incident, the first question I ask is almost never "what malware ran." It's "whose credentials did it use, and what was that account allowed to touch." Nine times out of ten, the interesting part of the story isn't the exploit. It's the access. The exploit gets you in the door. The privilege is what lets you walk through the building. For thirty years, that question had a human-shaped answer. A person clicked something, a person got phished, a person reused a password, an admin left a service account sitting on a domain controller with a password from 2014. The identity at the center of the incident belonged to somebody with a badge and a manager. That assumption is quietly dying, and most enterprises have not adjusted their controls to match. The actor on your network is increasingly not a person at all. It is a workload, a script, a bot, an API (application programming interface) client, and now an AI agent that can reason, plan...

Why Authentication Context Matters Most people think logging in is a small act. Type your password, type your code, tap a screen, scan a face, and move on. But to the systems on the other side, the method behind that moment can matter just as much as the fact that it happened at all. That is where two strangely named but surprisingly important identity concepts enter the story: OIDC's AMR and SAML 2.0's AuthnContext. They sound like the kind of acronyms that only standards committees could love, yet both were created to answer a deeply human question in digital form: How sure a system has to be before it trusts someone? The backstory starts with the internet growing up. Early online services often treated authentication as a light switch: either the user was in, or the user was out. But as online systems began handling payroll, health records, taxes, academic data, contracts, and financial approvals, that simple model started to crack. A login backed by a reused password is not ...

Cybersecurity is entering a new phase. It's one where the gap between awareness and operational execution is becoming the industry's biggest challenge. That's what stood out to me most after reviewing the results of the 2026 Bitdefender Cybersecurity Assessment , which found that organizations have never had greater insight into the risks they face, yet turning that understanding into meaningful action remains a persistent challenge. Nowhere is that gap more visible, in my view, than in how organizations handle breach transparency. We surveyed 1,200 IT and cybersecurity professionals across six countries: France, Germany, Italy, Singapore, the United Kingdom, and the United States. Respondents ranged from frontline employees to IT managers to CISOs, all working within organizations with 500 or more employees. A Governance Problem, Not an Attacker Problem One of the most troubling findings in our report is not about attacker behavior. It's about internal respons...

We recently worked with an organization that had invested heavily in advanced security tooling, including AI-driven detection and monitoring capabilities. From a technical perspective, the environment appeared mature: alerts were firing, dashboards were populated, and risks were clearly identified.  Yet progress had stalled.  The security team and IT disagreed on ownership. Business leadership perceived cyber risk as "under control," while the security team felt increasingly exposed and unheard. AI surfaced the signals, but no one could agree on what to do with them.  The turning point did not come from additional tooling or deeper analysis. It came from reframing the conversation.  By aligning stakeholders around clear business impact, contextualizing the findings against industry peers, and translating technical gaps into credible, board-level risk narratives that reinforced the internal security team's concerns rather than questioning their judgment, decisions were finally ma...

For decades, the firewall was the most trusted enforcement point in enterprise security. Every packet crossed it. Every policy lived on it. If you wanted to secure the network, you started there. Then work moved somewhere the firewall couldn't follow. Today, the average enterprise employee spends most of their day inside a browser — navigating SaaS applications, collaborating in cloud platforms, running queries through AI tools, and sharing files through web interfaces. All of it travels over HTTPS. All of it looks identical at the network layer: port 443, encrypted, and opaque. The firewall sees a connection. It doesn't see a ChatGPT prompt containing customer PII. It doesn't see a browser extension silently harvesting credentials. It doesn't see the SaaS file-sharing that just moved sensitive data outside the organization's control. This is the visibility gap that defines enterprise security in 2026. SSE Was the Right Answer — Deployed the Wrong Way Securi...

In the digital world, the secure exchange of cryptographic keys is the foundation upon which all private communication is built. It's the initial, critical handshake that allows two parties, like a user's browser and a web server, to establish a shared secret and communicate securely over the untrusted expanse of the internet. As the quantum computing era approaches, the very mathematics underpinning our traditional key exchange mechanisms are facing an existential threat. This spurred the development of new, quantum-resistant algorithms. This blog post provides a deep dive into how modern key exchange works, from the trusted classical methods to the emerging post-quantum standards, and explores how Zscaler leverages hybrid key exchange to bridge the gap. The Key Components of Modern Key Exchange At a high level, a secure key exchange protocol must achieve the following: Confidentiality: The established key must be a secret shared only between the two communicating parties. An ea...

The market is flooded with chatbots that summarize requirements, GenAI that drafts policies, and AI assistants that extract provisions from contracts. And these tools undoubtedly make existing workflows better. But when it comes to transformational technology, different is better than better.  These AI for GRC capabilities are the direct result of practitioners and vendors alike asking, "How can AI make our current workflows better?" What they should be asking is "Does AI make a completely new way of operating possible?" Agentic GRC doesn't improve GRC workflows; it replaces them with agents. For something to earn the title agentic, it needs to take an entire workflow, including the decision-making between each step, and execute it from start to finish. Whether teams are ready for the future or not (and they should be), they need to start thinking about their workflows in an entirely new way. Here's a framework for them to do so. Why the Distinction Between AI f...

Enterprise adoption of AI is no longer a future trend; it's a present-day reality. As organizations race to leverage AI for innovations, security teams are grappling with a new, complex, and dynamic attack surface. AI is breaking the operational silos that currently segregate Cloud, SaaS and Endpoint Security; AI is everywhere and it is consuming enterprise data and assets across these channels. Traditional security tools, designed for cloud infrastructure and SaaS applications, are fundamentally ill-equipped to handle the unique risks posed by AI.  AI security posture management (AI-SPM) solutions can provide relief by protecting critical AI assets, but it's important to note that not all AI-SPM solutions are created equal. Many solutions offer only basic posture checks and are focused predominantly on infrastructure and vulnerability management. In addition, most focus solely on Cloud or SaaS, leaving many blind spots when trying to get the full picture of your AI landscape. ...