Insider Threats

Detect and respond to anomalous behavior from humans and entities and monitor suspicious activity from AI agents before insider risk escalates.

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DETECT HIDDEN THREATS

Find Insider Threats Other Tools Miss

Insider threats, whether intentional or accidental, are one of the most dangerous risks to an organization. Exabeam uses AI to baseline normal behavior for every human and device. It also monitors the activity of non-human entities, including AI agents. Our patented Session Data Model stitches together related activities into a complete timeline, detecting user anomalies that span weeks or months. This allows security teams to find slow-moving insider threats that SIEM or XDR tools with short correlation windows can’t see.

Detect undetectable insider behavior with AI

MONITOR EVERY IDENTITY

See Every Action from Human Users and AI Agents

AI agents act autonomously, access sensitive data, and can execute insider-like behavior. Exabeam applies behavioral analytics to human users to flag abnormal behavior and provides deep monitoring of machine and agent identities to give you visibility into their access, data transfers, and actions. This provides a more complete view of potential threats, regardless of whether they originate from a person or a process.

SECURE AI AGENTS

Extend Proven Insider Threat Detection to AI Agents

AI agents introduce a new vector for insider risk. With Agent Behavior Analytics (ABA), Exabeam applies its decade of leadership in user and entity behavior analytics (UEBA) to monitor AI agent behavior. This allows your security team to detect misuse or compromise, surface high-fidelity threats early, and enable secure AI adoption across the organization.

UNCOVER AUDIT TAMPERING

Expose Attempts to Hide Malicious Activity

Insiders with system knowledge may tamper with or clear logs to hide their actions. Exabeam enriches user anomalies with business context to reveal intent. The Session Data Model ensures that log manipulations remain visible over weeks or months, even when human or AI insiders attempt to erase traces of suspicious behavior.

PREVENT DATA DESTRUCTION

Detect Abnormal Deletion of Critical Data

A malicious insider may destroy critical information to disrupt operations. Exabeam baselines file activity for every user and entity, automatically flagging abnormal deletion patterns that indicate a potential threat.

DETECT MALICIOUS INSIDERS

Uncover Credential Misuse

Malicious insiders exploit their access to critical systems. Organizations need a way to monitor their activity and instantly measure incident scope. Exabeam provides this visibility by correlating behavioral analytics from human users with activity logs from AI agents to clearly communicate risk and impact.

Spotting credential misuse for personal gain

DISCOVER DATA LEAKAGE

Connect Events to Reveal Data Leaks

Data leakage often resembles normal behavior, making it difficult to detect. Exabeam puts DLP alerts in context by correlating them with authentication, access, and other data, automatically building a complete timeline of events. By baselining activity for all users and monitoring the activity of agents, Exabeam reveals malicious intent that other systems can’t see.

Understand user intent quickly and accurately

MONITOR PRIVILEGED ACCOUNTS

Identify Unauthorized Access to Prevent Breaches

Attackers exploit privileged accounts to evade security controls, disrupt operations, or exfiltrate data. Exabeam helps prevent unauthorized privileged activity by analyzing user context, identifying abnormal behavior patterns for human and entity identities, and monitoring the activity of agent identities.

DETECT PRIVILEGE ESCALATION

Stop Privilege Escalation Attempts

Attempts at privilege escalation place critical assets at risk. Exabeam detects these techniques by monitoring credential activity and highlighting anomalies in threat timelines. This exposes escalation behavior, even when it unfolds slowly or occurs through automated processes.

PREVENT DATA ACCESS ABUSE

Identify High-risk Access to Sensitive Data

Malicious insiders may abuse their privileges to access sensitive data. Exabeam baselines the normal activity of users to flag anomalies and detect intent. It provides deep monitoring of AI agents to help security teams identify potential data access abuse. By maintaining long-term correlation windows, Exabeam identifies risk patterns that develop over time, giving analysts a complete picture.

PHYSICAL ACCESS SECURITY

Detect Suspicious Physical Access

Exabeam monitors for physical access anomalies, such as badge misuse or impossible travel between geolocations. These incidents can signal credential sharing or other insider activity. By correlating identity, geolocation, and access logs, Exabeam reveals subtle insider threats that other solutions miss.

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Frequently Asked Questions

Why are AI agents considered insider threats?

AI agents operate with legitimate credentials, access sensitive data, and take autonomous actions. When misused, compromised, or poorly governed, they behave like insiders and introduce a new category of risk.

How does Exabeam cover insider threats?

Exabeam provides insider threat coverage for human users and non-human entities like AI agents. Our patented Session Data Model maintains open-ended correlation windows to detect low-and-slow threats that span weeks or months. This extended visibility, combined with behavioral analytics for users and monitoring for agents, allows Exabeam to reveal risks that most SIEM and EDR tools miss.

Does Exabeam monitor AI agents as insiders?

Yes. Exabeam monitors AI agents as potential insiders because they act with credentials and access sensitive data. It provides deep visibility into their activity by collecting and correlating their logs, allowing security teams to investigate suspicious behavior and hunt for threats from machine entities.

Does Exabeam map Lateral Movement to the MITRE ATT&CK^® framework?

Yes. Exabeam maps its detection capabilities to the ATT&CK framework. For the Lateral Movement tactic, this includes detecting specific techniques and sub-techniques such as Remote Desktop Protocol (RDP), SMB/Windows Admin Shares, Distributed Component Object Model (DCOM), Secure Shell (SSH), Virtual Network Computing (VNC), and Windows Remote Management (WinRM). The New-Scale Security Operations Platform uses UEBA to detect these threats, builds cases with correlation rules, automates response through Automation Management, and offers prebuilt dashboards sorted by ATT&CK TTPs.

Can I keep my current SIEM and add Exabeam to address insider threats?

Yes. Many customers integrate data feeds from SIEMs like Splunk, Microsoft Sentinel, IBM QRadar, and others. Exabeam offers fast integration and upgrades your existing insider threat coverage without requiring extensive team retraining.

What makes Exabeam different from SIEM or EDR tools for insider threat detection?

Most SIEM and EDR tools rely on narrow, short-term correlation windows, making them ineffective at detecting insider threats that unfold slowly. The Exabeam Session Data Model is unique in maintaining stateful, long-term timelines. This design surfaces subtle anomalies and insider activity that competitors often overlook.

“In 90% of real attacks, we see compromised credentials used, which can be very hard to detect and defend. We chose Exabeam because their tools can successfully detect these kinds of attacks as they use many sources, not just security alerts. Their technology effectively analyzes and baselines normal usage to quickly alert on a compromised user or credentials.”