Compromised Insiders

Exabeam helps security teams detect compromised credentials by applying machine learning and user behavior analysis to baseline normal behavior for every user, device, and peer group.

Exabeam then automatically detects anomalous behaviors that are indicative of a compromised account, regardless of the attackers’ techniques.

Using specific data Exabeam enables analysts to see risky access and attacker techniques, like pass the hash, pass the ticket, and more.

Exabeam behavioral models put anomalous activity, like first time or failed access to hosts and assets in the context of the historical behavior of that user, their peers, and their organization to clearly identify attacker behavior from normal activity.

Privilege escalation can enable access to high-value assets without restriction.

Exabeam mitigates attackers’ privilege escalation by detecting techniques like credential enumeration, bloodhound execution, and more.

Behavioral models detect anomalous activity, like first-time access to hosts and assets or permission changes, and put them in the context of the historical behavior of that user, their peers, and their organization to clearly distinguish an attacker from a normal user.

Attackers target privileged accounts to bypass security controls and monitoring, disrupt corporate operations, or exfiltrate large amounts of sensitive data.

Exabeam detects attackers performing privileged activity through the combination of user context and identification of abnormal behavior.

Exabeam detects account manipulation by identifying abnormal user behavior such as manipulating an organization’s active directory (AD), creating or deleting accounts, or modifying group membership and permissions.

Exabeam also detects unusual activity performed by attackers, like when they hide behind system accounts, or when there is an abnormal activity using a non-service account.

Exabeam puts DLP alerts in the context of a user’s normal behavior to better identify when they pertain to a compromised user. By combining user activity from a variety of data sources, including those from DLP tools, Exabeam can detect data exfiltration across a variety of channels, including domain name system (DNS), email, or web upload.

Exabeam detects anomalous activity associated with evasions, such as tampering with audit logs, file destruction or encryption, and the use of a tor proxy to hide web activity.