Insider Threats

Abused credentials from a trusted insider, a compromised account, or an AI agent look like legitimate activity. Signatures and rules can’t spot the threat. This means security teams have no visibility into attacks from within.

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INSIDER THREAT DETECTION

Understanding Normal Behavior to Find the Abnormal

Credential abuse plays a critical role in breaches, giving attackers a fast path to lateral movement and privilege escalation. Behavioral analytics is the most effective way to stop it. By using AI to baseline normal activity for every user and device, Exabeam detects anomalies, scores risk in real time, and helps analysts prioritize and respond to credible threats.

Insider Threat Behaviors

While indicators of compromise (IoCs) change with every attack, attacker behaviors (TTPs) remain consistent. Relying on rules, statistics, and signatures alone isn’t enough.

Organizations need a reliable method to detect, investigate, and respond to insider threats. Exabeam uses AI to baseline normal behavior across all users and entities. This enables security teams to detect lateral movement, privilege escalation, tampering, account manipulation, data destruction, data exfiltration, and more.

Abnormal Authentication and Access

Exabeam detects abnormal authentication and access patterns from users and monitors the activity of automated agents to provide full context for investigations.

Lateral Movement

Detect attacker techniques like Pass-the-Hash and Pass-the-Ticket. Exabeam applies behavioral analytics to contextualize anomalous activity—such as first-time access to a critical server—and distinguishes attacker TTPs from normal user and entity activity.

Privilege Escalation

Attackers escalate privileges to gain access to critical assets. Exabeam detects techniques like credential enumeration and BloodHound execution by identifying abnormal behavior from users and providing visibility into the actions of automated processes.

Privileged Account Monitoring

Attackers target privileged accounts to bypass security controls and exfiltrate data. Exabeam detects this activity by applying behavioral analytics to human identities and providing deep monitoring of non-human accounts to detect suspicious activity.

Account Manipulation

Exabeam detects unauthorized changes in Active Directory, including account creation, deletion, or modification. It also surfaces attempts to conceal actions using misused service and agent identities.

Data Exfiltration

A standalone data loss prevention (DLP) alert lacks context. Exabeam adds behavioral context to DLP alerts to identify compromised and malicious insiders. By monitoring activity from multiple sources, Exabeam helps detect suspicious data exfiltration through DNS, email, or web uploads, or from AI agent data transfers.

Attack Evasion

Exabeam detects evasion techniques such as audit log tampering and file destruction. Behavioral analytics reveal malicious intent from users, while centralized logging provides the visibility needed to investigate when autonomous AI agents attempt to conceal their activity.

Data Leakage

Data leakage often resembles normal behavior, making it difficult to detect. Exabeam combines DLP alerts with authentication, access, and contextual data into a complete timeline. This helps analysts determine if a user, entity, or agent is acting maliciously.

Data Access Abuse

Malicious insiders may abuse privileges to access sensitive data. Exabeam identifies this abuse by baselining normal user activity to detect meaningful deviations and by providing detailed monitoring of agent activity to help analysts spot potential misuse.

Audit Tampering

Attackers often tamper with or clear logs to cover their tracks. Exabeam adds business and identity context to user anomalies and all non-human activity, helping analysts accurately identify tampering regardless of the identity used.

Data Destruction

A malicious insider may destroy critical data to disrupt operations. Exabeam baselines file and data activity to flag abnormal deletion patterns across all users.

Physical Security

Exabeam detects suspicious physical access, such as an employee badge being used in two locations in an impossible timeframe. This can indicate a shared or stolen badge being used for unauthorized access.

At-Risk Employees

Exabeam identifies at-risk users by correlating HR data with activity patterns, such as communication with competitors or unusual data access, that may indicate an employee is preparing to leave the organization.

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Exabeam provides prebuilt content and automated workflows that map to your most critical security use cases.

USE CASE

Compliance

Manual processes and disparate tools make it difficult to meet regulatory requirements like GDPR, PCI DSS, and SOX. Exabeam automates compliance monitoring and reporting to reduce risk and simplify audits.

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USE CASE

External Threats

External attackers use phishing, malware, and other techniques to breach your organization for financial gain, espionage, or sabotage. Exabeam detects and responds to the entire attack chain, from initial compromise to final exfiltration.

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