Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

It's 4 p.m. and a client calls. It's an employee's last day, and you need to make sure they no longer have access to company environments, applications, systems, sensitive information—or even the corporate laptop. You remove VPN access. Then remote desktop access. Then access to applications and internal systems. Multiple locations, multiple consoles, and it only takes missing one of them to leave a door open. Now multiply that by the number of clients you manage.

In Part 1 of this series, we addressed 18 Kubernetes best practices spanning across container hardening, observability, availability, and fault tolerance. Those practices secure the containers that agents run in. But the CNCF AI Technical Community Group's cloud-native agentic standards go further, establishing that securing containers is only the beginning.

The deciding factor now is whether a solution can reduce risk, fit the environment, and make the team more effective.

At Corelight Labs, our mission is to help organizations stay a step ahead of evolving threats. When our researchers came across Censys' detailed write-up on ScoutC2, a rapidly growing open-source command-and-control (C2) framework favored by threat actors, we knew we needed to bolster community defenses quickly.

Credential abuse is the common vector in 13% of data breaches. Cybercriminals can gain access to sensitive organizational data through weak, stolen, or reused passwords belonging to employees or customers. Single sign-on (SSO) and Multi-Factor Authentication (MFA) are industry-standard solutions for addressing these issues, and they can help to mitigate security threats. But external Jira Service Management (JSM) customers often authenticate differently.

88% of organizations are running AI in at least one workflow, yet nearly two-thirds report more rework than savings. The model is rarely the bottleneck. Everyone has access to the same frontier models now. The difference is what sits underneath: content that's unstructured, ungoverned, and disconnected from the workflows that need it. Fixing the content problem usually means giving AI broad access to content, and that's where governance breaks down.

Every year, KnowBe4 analyzes millions of simulated phishing tests to measure one thing: how likely is your workforce to fall for a phishing attack? The results, published in the 2026 Phishing by Industry Benchmarking Report, paint a clear picture of where human risk concentrates — and what organizations can do about it. Here are the key findings security leaders need to know.

KeeperDB is a secure, multi-protocol database client built on Keeper’s zero-knowledge platform. Available as both a free standalone desktop application and a privileged session component of KeeperPAM, KeeperDB combines a database query engine, vault-managed credentials, real-time performance monitoring and an AI-powered database assistant in a unified interface. Continue reading to learn more about how KeeperDB works, its key features and the benefits of using it to help secure database access.

When we think about email security, our minds almost always jump to the inbound threats: the sophisticated phishing lures, the AI-generated business email compromise (BEC) attacks, and the malicious attachments knocking at the perimeter. But there is a silent, internal crisis happening on the way out of your organization. And chances are, you’re flying completely blind to it.

Fraudsters are adaptive actors who follow the path of least resistance. The goal of fraud-fighting teams is often to make the cost of fraud high enough that attackers go elsewhere. Leveraging Persona’s Mobile SDK raises fraudsters’ costs by requiring identity verification to happen in signal-rich mobile environments. For years, fraud fighters have layered verification checks and risk signals to detect various types of attacks.