Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Data security budgets are under more scrutiny than ever. When a CISO brings a new tool to the table, finance and the board want to know: What does this buy us, and how do we measure it? Data security posture management (DSPM) is one of the harder investments to quantify on paper, largely because its primary value is risk reduction rather than revenue generation. But that framing undersells it.

Your SOC gets an alert from the CNAPP: an outbound connection from a pod in the ai-prod namespace to . The destination is in the allowlist. The payload size is 28 kilobytes — well under the DLP threshold. The agent’s service account has permission to invoke the email tool. By every check your stack runs, the traffic is normal. Forty minutes later, a customer support lead notices that an email went out containing a summary of 2,400 customer records that the agent had no business querying.

You cannot turn a corner without entering the world of AI. I was in a big box home improvement store the other day and there was a manufacturer touting the AI built into their refrigerator! Children’s toys, personal electronics, and even cat litter boxes are now selling AI-assisted products. I am a technology early adopter, and where I’ve seen good uses of AI, we are in the phase of “throw AI into everything” mode, as we do not know what will stick.

Controlled unclassified information (CUI) protection requires consistent identification, marking, safeguarding, and access governance across every system that touches federal data. With CMMC Phase 1 underway and the FAR CUI rule in effect, compliance is now a contract prerequisite. Controlled unclassified information (CUI) is sensitive but unclassified information that requires safeguarding or dissemination controls under federal law, regulation, or government-wide policy.

Most organizations believe they have a handle on where their sensitive data lives. A closer look usually reveals a different picture. Classified files on unmanaged endpoints, customer records replicated into SaaS tools no one approved, and AI-generated content containing proprietary context that was never meant to leave a controlled environment. The gap between perceived and actual data security posture is exactly where breaches happen.

Cyber risk in 2026 isn’t defined by a lack of security tools; it’s defined by how quickly weaknesses compound when organizations aren’t aligned. To understand how organizations are responding, we researched the priorities, concerns, and blind spots of three critical leadership roles: the CISO, CIO, and CTO.

Proofpoint DLP and Trellix DLP are two notable data loss prevention solutions. In this blog, we’ll analyze both platforms in depth and see how they compare. We’ll also introduce Teramind as a compelling alternative that combines the best aspects of Proofpoint and Trellix, while offering additional tools that could increase your workforce’s safety and productivity.

RAG systems connect AI models to your internal data, making them powerful but also creating serious security gaps in access control, data retrieval, and compliance. Knowing how to ensure data security in RAG systems means securing every layer of the pipeline from ingestion to retrieval to output.

DSPM solutions continuously discover and classify sensitive data, map who can access it, and surface misconfigurations across cloud and hybrid environments. Without them, security teams cannot reliably find shadow data, assess real exposure, or demonstrate that sensitive information is protected. Choosing the right platform means matching data coverage, risk prioritization, and remediation workflows to your actual estate.