Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

When I read Eyal’s blog, Why FWaaS is the Only Way Out of Endless Appliance Patching, I imagined a time in the immediate now (oxymoron intended); a time where the word “patching” is as quaint as rotary phones. In my mind, I was Marty McFly, jumping out of the DeLorean, shocked to discover that in the year 2025, we’re still patching appliance boxes. But here’s the kicker: everything has changed. Except the way we think about patching.

If there’s one truth in payments, it’s this: the network always wins. Think of what Visa and Mastercard created: not just payment rails, but global ecosystems of merchants, issuers, acquirers, and processors. Their networks didn’t just move money—they connected entire economies. As digital assets move into the mainstream, the same principle applies. But the networks of tomorrow won’t be built on closed systems and settlement delays.

The rapid adoption of generative AI (GenAI) in the enterprise is introducing a new category of unmanaged risk known as shadow AI. Organizations frequently lack insight into which employees are using GenAI tools and how they are being accessed, resulting in visibility limitations, policy enforcement challenges, and increased risk of data exposure. Security teams face potential data leaks and compliance violations, while IT teams struggle to integrate GenAI usage into existing governance models.

Swissport International AG is the world’s largest ground-handling company, ensuring seamless operations across 276 airports in 45 countries handling approximately 247 million airline passengers per year, as of the end of 2024. That kind of scale brings complexity. For Swissport’s new IT leadership, that complexity had grown into an unsustainable mix of legacy security controls, fragmented remote access solutions, and painfully slow troubleshooting. Then came the shift.

Generative AI (GenAI) is advancing rapidly, offering significant potential for business transformation. However, it also introduces new security risks. The Model Context Protocol (MCP), an open standard introduced by Anthropic in November 2024, enables seamless integration between GenAI applications and external data sources and tools. MCP is commonly referred to as a USB-C port for GenAI applications.

Today during SASEfy 2025, Cato Networks announced its latest AI innovation. Cato CASB (Cloud Access Security Broker), a native feature in the Cato SASE Cloud Platform, is now enhanced with new capabilities for generative (GenAI) applications including a shadow AI dashboard and policy engine. With the shadow AI dashboard, enterprises can detect, analyze, and gain insights into the use of GenAI. With the policy engine, enterprises can take control of user activities in GenAI applications.

Signature-based detections provide fast, effective defense against known attacks. But the threat landscape is rapidly changing: Attackers are utilizing novel, sophisticated techniques that can bypass traditional, signature-based detection methods and also weaponizing legitimate tools and processes to avoid established detection tools, including endpoint detection. In this dynamic environment, organizations must in turn deploy new detection techniques to keep pace.