Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Security operations have never been more complex. Analysts face more alerts, more tools, and more pressure to make the right decision at the right moment. The work feels less like running a security program and more like trying to keep an orchestra in sync while each musician plays from a different sheet of music. This is the challenge Sam was created to solve. Sam, the Securonix AI SOC Analyst, acts like a skilled conductor guiding a symphony.

Security operations teams are facing a structural problem that tools alone cannot solve. Alert volumes continue to rise. Telemetry is fragmented across cloud, SaaS, identity, and endpoint environments. Experienced analysts are stretched thin, and hiring additional talent has become increasingly difficult. At the Same time, boards are demanding faster response, stronger governance, and clear proof that security investments are delivering measurable value. AI is often presented as the answer.

Insider threats pose a growing risk to organizations. Whether insiders take malicious actions, exhibit negligent behavior, or make accidental errors, they have the potential to cause significant harm to an organization’s assets, sensitive data, and reputation. Insiders can pose a variety of risks, from stealing confidential data and intellectual property to disrupting systems.

Let's take a closer look at the fragmented NHI inventory from a site reliability engineer's perspective.

Threat actors target the insurance industry for a simple reason: insurers sit on concentrated volumes of sensitive personal data, financial records, and in many cases health information, all of which are highly valuable for resale on dark markets. Claims systems, customer portals, broker platforms, and third-party service providers also present a complex attack surface that offers threat actors multiple paths into the business.

This blog shows how aggregating vulnerabilities by machine and package turns fragmented, multi-tool findings into a single, normalized issue, enriched with AI-driven context to support clearer prioritization and faster remediation.

A practical guide to VM-aware data protection for VMware-to-OpenShift migrations VMware exits rarely fail because engineers cannot move bits. They fail because the organization discovers, mid-flight, that it cannot reliably recover those bits once they land somewhere new.

Cybersecurity requirements for companies in the defense supply chain have entered a decisive enforcement phase. The Department of Defense has moved beyond self-attestation and toward verifiable, contract-bound cybersecurity standards. The Cybersecurity Maturity Model Certification (CMMC), now plays a central role in determining which organizations are eligible to work with the DoD. CMMC establishes three compliance levels, each tied directly to the sensitivity of the data an organization handles.

As organizations move deeper into cloud ecosystems, automation, AI integrations, and global supply chains, one truth becomes increasingly clear: In 2026, third-party risk is not just an IT concern. It is a business continuity concern, a regulatory concern, and in many industries, a board-level concern. From software vendors and cloud providers to managed services, payment processors, contractors, and niche business tools, every external connection introduces potential exposure.

In the cybersecurity arena, script executors are among the most divisive tools. On the face of it, they appear harmless enough; in fact, these tools are generic script-execution utilities that can be used for automation but are also widely abused outside legitimate development environments. They become powerful tools against cybercrime, malware deployment, and privacy invasions when corrupted.