Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Reducing Time-to-Protect with Cato's Self-Evolving Vulnerability Protection Agent

TL;DR: In the age of frontier AI models, vulnerability discovery and exploit development are scaling faster than human defenders can manually respond. Security teams already face growing CVE volumes, shorter exploitation windows, and manual workflows for researching vulnerabilities, creating protections, validating them, and preparing them for deployment. As attackers weaponize vulnerabilities faster than organizations can patch them, time-to-protect is becoming a critical security metric.

Private App Access, Zero Network Change

As organizations advance toward Security Service Edge (SSE), secure access to private applications has become a practical priority. Executives rightly expect these programs to improve security while increasing agility. Yet many initiatives slow down at the same point: extending access to private applications. The work often depends on firewall exceptions, routing changes, and cross-team coordination, followed by tightly controlled maintenance windows.

What Consistent Leadership Across SSE, SD-WAN, and SASE Signals

GigaOm’s latest analysis highlights a clear shift in the market. As they note, “The standalone Secure Service Edge (SSE) market has largely disappeared, with leading vendors now offering complete SASE solutions that converge software-defined wide-area network (SD-WAN) and SSE into single-vendor platforms. Organizations increasingly favor this consolidated approach to reduce operational complexity and improve visibility.”

Access the App, Not the Network - with Cato Private Access

See how Cato Private Access helps organizations access the app, not the network. In this demo, we show how IT teams can deliver secure access to private applications without routing or firewall changes, while maintaining application-level access control, centralized policy enforcement, and visibility through the Cato Management Application. We also highlight how Cato manages private application access through the Cato SASE platform, enabling a more unified, operationally efficient approach than traditional connector-based architectures.

Cato CTRL Threat Brief: AI, Zero-Days, and the US-China Cyber Arms Race

Underlying the US–China AI race, there’s arguably a more sinister arms race—the race to identify zero-day threats. Frontier AI algorithms, such as Anthropic Mythos (here) and China’s Qihoo 360 (here), are compressing the zero-day discovery cycle. But how those discoveries are gathered and shared among cooperating entities is giving China significant defensive and offensive advantages.

Defending Against the Next Generation of Agentic Attacks

The attack lifecycle is compressing. Frontier AI models like Anthropic’s Mythos and OpenAI’s GPT-5.5-Cyber can help bad actors research vulnerabilities, test approaches, adapt code, and change delivery methods at machine speed and scale. That reduces the time, skill, and coordination needed to move from vulnerability discovery to active attack. When attacks behave this way, security needs to operate in real time with full visibility and context across the attack path.

Cato Private Access: Zero Trust Access Without the Operational Overhead

Most organizations understand the need for Zero Trust access to private applications. The challenge is delivering it without creating operational bottlenecks, increasing network risk, or slowing projects with weeks of coordination. In this video, Chris Rudolph explains how Cato Private Access enables secure, application-level access to private applications without requiring routing updates, inbound firewall changes, or complex network redesigns.

Stop Treating AI Like Another SaaS App

Employees are leveraging AI to boost productivity and adopt skills that would take years to learn. This ranges from drafting content, writing code, and building automated workflows. Some of this use is approved. Much of it is not. For many security teams, the first instinct is to treat this risk like they would any other SaaS risk: discover the app, allow or block access, apply DLP rules, and report on usage. That model works for traditional SaaS, but AI is different.

Making Security Data-Aware with New Integration from Cato Networks and Cyera

Today, Cato Networks announced an integration of Cato XOps with the Cyera AI-native Data Security Platform Management (DSPM). The integration brings Cyera’s data security telemetry directly into Cato XOps, giving security teams visibility into the sensitivity and exposure of data involved in security events. In today’s distributed environments, data lives across the cloud, SaaS, endpoint, and network.

Frontier AI and the Demise of Hardware Security

The cybersecurity industry has long relied on a simple idea: find vulnerabilities, patch them, and measure success by how fast you close the gap. “Time-to-patch” became a badge of honor. That model no longer holds. The rise of Mythos-class Frontier AI Models introduces a different kind of threat. AI-driven, agentic attacks operate continuously, discover weaknesses automatically, and execute at a scale no human team can match.