Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The largest CCPA settlement in California history isn’t a story about a company that ignored privacy. It’s a story about what happens when doing the right things isn’t the same as making sure the right things have been done right.

Modern software development has a fundamental problem: we are writing code faster than we can secure it. This creates security debt, a quantifiable backlog of unaddressed vulnerabilities that lingers for over a year. Much like financial debt, it compounds interest over time, but the currency is risk. Despite increased investment in security tools, this backlog is growing, not shrinking. With security debt reaching a critical mass in 2026, organizations must shift their strategy.

Too many organizations today still rely on "legacy" retainer models. These traditional contracts are often rigid, opaque, and reactive, and designed for a world that no longer exists. That’s why LevelBlue is proud to announce the Resilience Retainer. This is a modern, flexible approach built on our experience of handling more than 9,000 cyber incidents worldwide. This up-to-date approach is a necessity, given the long-lasting impact an incident can have.

Organizations adopt multi-cloud architectures for many reasons, including compliance requirements, business strategy, and resiliency. Regardless of the cloud provider, the security challenges remain the same: Identify the most critical risks, prioritize them with business context, and remediate them before they are exploited by a bad actor.

Every cloud security vendor now has an AI-SPM dashboard. Strip away the branding, though, and most of these dashboards are doing the same thing: checking IAM configurations, scanning for misconfigured network access, inventorying AI models across cloud accounts, and flagging compliance gaps. It’s cloud security posture management with an AI label applied. That’s a problem, because AI workloads don’t behave like other cloud workloads.

Your security stack was built for workloads that follow predictable code paths. AI agents don’t. They interpret prompts, generate code on the fly, invoke tools dynamically, and escalate privileges in ways no developer anticipated — all as part of normal operation. The signals that indicate a compromise in a traditional container are indistinguishable from an AI agent doing its job. And most detection tools can’t tell the difference. This isn’t a theoretical gap.

Your CISO just got word that engineering is deploying AI agents into production Kubernetes clusters next quarter. Not chatbots—autonomous agents that generate and execute code, call external APIs through MCP tool runtimes, access internal databases, and make decisions without human review. The question lands on your security team: “How are we securing these?”

We work directly with your leadership team to design, implement, and sustain a CMMC-aligned security program that goes beyond checklists and stands up to real-world scrutiny.

A Russia-linked threat actor widely tracked as APT28 leveraged a zero-day vulnerability in Microsoft’s MSHTML engine, tracked as CVE-2026-21513, in targeted operations before a security patch was made available. The vulnerability enabled remote code execution through crafted content rendered by the Windows MSHTML component, which remains embedded across supported Windows systems. The exploitation occurred in targeted spear-phishing campaigns aimed at diplomatic and defense-aligned organizations.