The dangerous part of a stolen identity isn't always the initial login. It's what an attacker can do with that access next. With AI accelerating reconnaissance, exploitation of vulnerabilities, and privilege escalation, attackers can move through systems faster than security teams can investigate. A compromised account that looks legitimate at first could become the starting point for a much

A user opens a browser tab, pastes data into a chat assistant, and nothing is installed. A developer adds a coding assistant as an editor extension, and nothing shows up in the installed programs list. Someone downloads a local model runtime, a program that runs models directly on the machine instead of sending data to an external service, because they were told not to send company data

The personal AI agents rollout is going about as smoothly as expected: Amazon now blocks Meta's Muse because it doesn't identify itself as a bot while browsing; Instinct keeps raising privacy concerns; and the horror stories from pretty much every personal AI agent keep piling up. Regardless, the tech world is mesmerized by the capabilities and potential of these services. Less than a year

In environments studied for the 2026 State of Agent Security Report, roughly 1,280 third-party products now embed AI. About 282 of them sit behind single sign-on. The other thousand are invisible to identity infrastructure by default, not because anyone hid them, but because an identity stack can only govern what authenticates through it, and most agents never do. That gap is the clearest

As enterprises race to deploy autonomous AI agents to accelerate business, a new report reveals they are tethered to security architectures built for a different era. The "Horizons of Identity Security" report from SailPoint highlights a critical “velocity paradox,” in which organizations invest in AI-speed business operations while continuing to rely on human-speed security controls, creating a

Phishing kits are no longer limited to copying a familiar login page and waiting for a victim to enter credentials. Attackers are increasingly building filtering, session management, and traffic controls into the infrastructure that delivers the phishing page itself. ANY.RUN has identified Wazza, a new phishkit targeting banking, manufacturing, and government organizations across the US, Europe

The 2026 findings are not just a year-over-year shift. They mark the latest point in a five-year arc where resilience, AI governance, human risk, and board scrutiny are converging inside the systems where work actually happens. For years, the enterprise cybersecurity story has been told as a straight line of escalation: more attacks, more data loss, more pressure, and more urgency. That

If you’re evaluating an agentic pentesting solution right now, you’ve probably heard the same pitch more than once: point it at a target, and it discovers, validates, and exploits attack paths autonomously, the way a real attacker would. That promise is worth taking seriously. It’s also worth pressure testing, and three questions do the heavy lifting.  What can the assessment actually

In 2024, MCP (Model Context Protocol) set out to become the USB-C of AI: one standard for connecting models, agents, and IDEs to tools and data. The protocol delivered. Thousands of developers built servers, and enterprises plugged them into agent workflows. The ecosystem around it fell short. Earlier this year, our team at OX Security,  traced critical vulnerabilities in Anthropic's MCP

Every modern enterprise depends on credentials. This is how humans, systems, and now AI, all connect to data, services, and each other securely. GitGuardian helps secure that credential layer through three connected capabilities: Detect, Remediate, and Prevent. The journey starts with detection, because organizations first need to understand what credentials exist, where they live, and what they

Featuring: Cybersecurity is being reshaped by the expansion of cloud infrastructure, AI, distributed systems, and increasingly complex digital environments. As organizations manage more identities, devices, data, and internet-facing infrastructure, security is shifting toward continuous visibility, control, and the ability to respond to risk at scale. This report examines how core areas of

The quarterly board meeting is two weeks out. The security team is pulling exports from the identity provider, the cloud posture tool, the vulnerability scanner, the SIEM and the EDR console. Someone is building a spreadsheet to reconcile them. Someone else is turning that spreadsheet into slides. Then a board member asks three questions: How secure is the organization, overall? What is

Every security leader at a bank, insurer, or asset manager has had a version of this conversation: Security wants to eliminate a class of vulnerabilities. Engineering explains what it would take to upgrade the platform where they live. Somebody prices out the regression testing. Somebody else raises the change-freeze calendar. The finding gets an exception, a compensating control, and a date

Given that the browser is where business apps are accessed and used, it makes sense that attacks are happening there too. Most breaches today begin in a browser session. Often, they never leave it, with the entire attack chain from initial access to exfiltration playing out in the browser. Here are the six most dangerous techniques that should be on every security team's radar in 2026. 1.

ANY.RUN researchers traced a US-focused CSuite phishing campaign across 351 sandbox analyses, with 51% of submissions coming from the United States. Technology, manufacturing, government, and consulting organizations showed the highest exposure. By combining Microsoft 365 session theft with remote-access tool deployment, CSuite can turn a phishing incident into broader account compromise, fraud

What is IAM for AI agents? AI agents authenticate, invoke tools, and act across enterprise systems with delegated authority. IAM for AI Agents is the identity-control architecture that governs those actors. This guide covers the limits of conventional provisioning, the components that matter, how to evaluate framework choices, and what runtime evidence proves an agent behaved as intended.

AI agents are moving into production faster than security teams can govern them. They are connecting to apps, handling data, calling APIs, and acting across business systems—often without the same controls applied to human users. According to Okta’s Global CISO Insights 2026 report, only 47% of CISOs are confident they can identify every AI agent in their environment. Even among those who feel

The way we talk about AI agents is shifting, and the way we implement them requires an even more fundamental shift. While earlier discourse focused on how quickly organizations could stand up agents and how much productivity they could promise, a string of recent incidents, including a widely discussed intrusion at Hugging Face during an evaluation of OpenAI agents, has spurred organizations to

Security leaders keep debating whether AI will produce an entirely new class of cyberattack. The nearer change is quieter and already visible: AI has made a failed attack cheap to retry. The routine version looks like this. An attacker lands on a low-privilege cloud account, and the first try at privilege escalation goes nowhere. That dead end used to cost hours of documentation reading,

AI coding agents are changing how quickly developers can build and ship software as well as how quickly credentials can become exposed. According to GitGuardian’s 2026 State of Secrets Sprawl Report, commits identified as AI-assisted are leaking secrets at approximately twice the rate of human-written ones. Most of the fastest-growing categories of leaked credentials are now connected to AI