Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Low and slow attacks look normal because they are intentionally distributed into small, permissible actions that avoid detection thresholds. Each step appears legitimate on its own, which prevents detection systems from recognizing the overall progression. The issue is not that security teams lack telemetry. The issue is that traditional detection often evaluates activity in fragments. When each action stays below a rule or threshold, the broader pattern can remain invisible.

The LogRhythm SIEM July 2026 release adds new investigation workflow features, expands automation for administration and archiving, and broadens telemetry coverage across cloud, identity, collaboration, endpoint, and email environments. Organizations running on-premises and hybrid environments often need tight control over data to meet sovereignty and operational requirements.

Exabeam expands Behavior Intelligence to address risks introduced by agentic AI. This release introduces open-source projects for agent verification and telemetry, expanded AI observability with Anthropic Claude support, more than 50 new Agent Behavior Analytics (ABA) detections (bringing total to 90), Exabeam Nova Content Creator, and OWASP Agentic Top 10 coverage scoring in Outcomes Navigator, enabling teams to continuously verify, observe, analyze, and improve AI agent security.

Short correlation windows miss insider risk because misuse develops gradually, often over longer periods than detection models track. Short correlation windows miss insider risk because misuse often spans longer periods than detection models track. When context resets at fixed intervals, small behavioral changes fail to accumulate into visible risk. When context resets at fixed intervals, behavior is evaluated in disconnected segments.

Insider threats often don’t trigger alerts because the activity relies on valid credentials, approved tools, and authorized workflows. When viewed as individual events, this behavior looks normal and stays below traditional rule thresholds. Risk accumulates across otherwise valid actions without producing a signal that meets alert thresholds.

Every CISO has prepared for a budget conversation by building the strongest possible business case. The right data, the right framing, the right numbers. But the security leaders who consistently earn CFO support are not necessarily the ones with the most polished decks. They are the ones who built the relationship that made the ask credible before it ever landed on the table. That distinction came through clearly in a recent conversation between Exabeam CISO Kevin Kirkwood and Exabeam CFO Mike Byron.

By mid-2026, the question is no longer whether AI belongs in the enterprise. It’s already embedded in daily work, supporting research, development, customer engagement, and operations. AI agents now act on behalf of employees, automate decisions, and interact directly with enterprise data and systems. This shift creates a new security challenge.

Most security platform comparisons begin and end with the wrong number. Two vendors submit proposals. One comes in lower. Finance notes the delta, flags the savings, and the conversation shifts. What rarely makes it into that comparison is everything that determines what the platform actually costs once deployed, staffed, scaled, and operating effectively in production. That gap between sticker price and real cost is where security investment decisions quietly go wrong.

There is a huge amount of excitement right now about AI and security operations. Across the industry, we are seeing rapid innovation in areas such as behavioural analytics, AI-assisted investigation, and increasingly agent-based capabilities designed to help security teams process large volumes of activity more effectively. Security teams need that help. The scale of alerts, identities, and telemetry they must manage today has grown far beyond what humans alone can realistically handle.