Atlassian recently disclosed a new critical vulnerability in its Confluence Server and Data Center product line, the CVE has a CVSS score of 10, and allows an unauthenticated attacker to gain Remote Code Execution (RCE) access on the vulnerable server. There is no workaround, the only solution being to upgrade to the latest patched versions.

Today, Cato is furthering our goal of simplifying security operations with two important additions to Cato SASE Cloud. First, we’re leveraging generative AI to summarize all the indicators related to a security issue. Second, we tapped ML to accelerate the identification and ranking of threats by finding similar past threats across an individual customer’s account and all Cato accounts.

Security analysts continue to face an ever-evolving threat landscape, and their traditional approaches are proving to be quite limited. They continue to be overrun with security alerts, and their SIEMs often fail to properly correlate all relevant data, leaving them more exposed to cyber threats. These analysts require a more effective method to understand threats faster and reduce security risks in their environment.

History taught us that whistleblowers can expose the darkest secrets and wrongdoing of global enterprises, governments and public services; even prime ministers and presidents. Whistleblowers usually have a deep sense of justice and responsibility that drives them to favor the good of the many over their own. Often, their contribution is really appreciated only in hindsight.

Wherever you are in your SASE or SSE journey, it can be helpful knowing what other CISOs are doing once they’ve implemented these platforms. Getting started with enhanced security is a lot easier than you might think. With Cato’s security services being delivered from a scalable cloud-native architecture at multiple global points of presence, the value is immediate. In this blog post, we bring the top three things you, as a CISO, can do with Cato.

In the previous post, we’ve discussed how passive OS identification can be done based on different network protocols. We’ve also used the OSI model to categorize the different indicators and prioritize them based on reliability and granularity. In this post, we will focus on the network and transport layers and introduce a machine learning OS identification model based on TCP/IP header values.

Enterprises often find themselves tethered to complex and inflexible network architectures that impede their journey towards business agility and operational efficiency. Secure Access Service Edge, or SASE, a term coined by Gartner in 2019, defines a newer framework that converges enterprise networking and security point solutions into a single, secure, cloud-native, and globally distributed solution that secures all edges.

If you are used to managed MPLS services, transitioning to Internet last-mile access as part of SD-WAN or SASE might cause some concern. How can enterprises ensure they are getting a reliable network if they are not promised end-to-end SLAs? The answer: by dividing the enterprise backbone into the two last miles connected by a middle mile and then applying appropriate redundancy and failover systems and technologies in each section.

By Vadim Freger, Dolev Moshe Attiya On December 7th, 2023, the Apache Struts project disclosed a critical vulnerability (CVSS score 9.8) in its Struts 2 open-source web framework. The vulnerability resides in the flawed file upload logic and allows attackers to manipulate upload parameters, resulting in arbitrary file upload and code execution under certain conditions. There is no known workaround, and the only solution is to upgrade to the latest versions, the affected versions being.