Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

As AI continues to weave itself into the fabric of everyday business operations, it’s bringing real ethical questions to the forefront—especially around how data is used and protected. With innovation moving fast, tech leaders can’t afford to treat privacy and ethics as afterthoughts. It’s on us to build systems that respect people’s rights from the ground up and to make sure our use of AI reflects the values society expects us to uphold.

In our modern digital world, sensitive data protection is an essential challenge for organizations of any scale. Data breaches can translate into huge financial losses, loss of customer confidence, and heavy legal fines. Data Loss Prevention (DLP) technology plays a crucial role in protecting information, but not all DLP technologies are capable of addressing the evolving threats. Legacy DLP infrastructure, which was the norm, is no longer good enough, exposing organizations to risks.

Trapping attackers and catching them red-handed before they even enter your network is the ultimate defense strategy. There is no doubt that traditional security systems are efficient in handling threats—but known threats! What if the attacker finds a new and unimaginable way to intrude into your network? This is where we need deception technology! Let’s go through both methods and find the differences in detail.

In 2025, hybrid cloud environments have emerged as a cornerstone for businesses striving to modernize their IT infrastructure. From leveraging AI-driven tools to enhancing performance, sustainability, and security, hybrid cloud is paving the way for a new era of efficiency and growth.

Effectively responding to cloud security incidents can be daunting for organizations expanding rapidly in the cloud. Whether you face a policy violation or an active threat, quick and reliable alerting and response are essential to keeping cloud services secure and available. For many organizations, Sysdig and PagerDuty each play a critical role in automating DevSecOps and helping modern IT operations and security teams respond effectively.

On March 14, 2025, the popular GitHub action tj-actions/changed-files was compromised, exposing secrets in CI logs. GitGuardian's analysis identified leaked secrets like GitHub tokens, AWS keys, and more.

Speed and innovation rule in software development, which makes it easy to overlook one crucial aspect: security. As a Staff Solutions Engineer at Snyk, I’ve seen firsthand how a single overlooked vulnerability can spiral into a crisis, affecting businesses, customers, and trust. Secure coding isn’t just about writing better code—it’s about protecting what matters, which includes the credibility and reputation of individuals, teams, and the business.

Developers are trapped in a loop: constantly chasing dependency upgrades to mitigate security risks or chasing down security reports of vulnerable code or findings in the CI pipeline. Developers often refer to this as “vulnerability fatigue,” a term commonly referenced in npm package install logs that list the newly introduced security vulnerabilities for third-party dependencies.

If you are a mature organization, you might manage an external IP block of 65,000 IP addresses (equivalent to a /16 network). In contrast, very large organizations like Apple may handle an astonishing 16.7 million IP addresses or more (about a /8 network). However, this isn’t the case for many of us. IP addresses are fixed assets and can be costly, so most modern organizations do not have a large number of directly assigned IP addresses for every service they expose to the internet.

Today, Cato Networks published the 2025 Cato CTRL Threat Report. It is the inaugural annual threat report from Cato CTRL, the Cato Networks threat intelligence team. The key theme for this year’s report is artificial intelligence (AI), which reflects the current cybersecurity landscape where AI usage is skyrocketing among vendors—and threat actors. Within the report, we examine the security risks associated with LLMs and the increased adoption of AI applications within organizations in 2024.