Detect the enemies within, and secure data from misuse and abuse.
Malicious insiders can be current employees, former employees, or third parties, like partners, contractors, or temporary workers with access to the organization’s physical or digital assets. Because of their access and knowledge of the organization’s most valuable assets, attacks involving malicious insiders are harder to identify and remediate than those that originate from outside the enterprise.
To minimize harm to an organization, insider threat teams need a reliable method to monitor, detect, investigate, respond, and report on threats from malicious insiders.
Data must move in and out of an enterprise in order to support the business operations. However, malicious data leaks can closely resemble normal activity, making it challenging to detect. Broadly alerting on data exfiltration can also result in a high volume of false positives from data loss prevention solutions.
Exabeam automatically stitches together DLP alerts with authentication, access, and contextual data sources into a timeline of all a user’s activity. With a complete picture of a user’s activity, analysts can determine if the insider is acting with malicious intent and spend their time investigating actual attacks, not false positives.
Employees often need access to sensitive data and applications as part of their job. However, a malicious insider may abuse their privilege to access customer information, medical records, or other sensitive corporate data. Exabeam baselines normal user activity and detects deviations from this normal behavior. Flagging anomalous activity helps insider threat teams detect a malicious insider at the stage of data access abuse, preventing the malicious insider from causing greater harm to their organization through exfiltration.
Systems access, as well as knowledge of organizational policies, processes, and procedures, gives malicious insiders an advantage over external actors seeking to circumvent detection. A malicious insider with knowledge of auditing and event logging can tamper or clear logs to circumvent their detection. Exabeam enriches flagged abnormal activity with user and business context data, so analysts can determine if an insider is tampering with audit logs and acting with malicious intent.
A malicious insider may intentionally destroy critical business information in order to disrupt operations or cause financial harm. A disgruntled employee, for example, may look for ways to delete data and files on critical systems, bringing the entire organization to a halt. Exabeam baselines user activity and flags abnormalities in the number of files deleted to help detect malicious insiders motivated to wreak havoc on an organization.
Privileged accounts, highly desirable for abuse or account takeover, are often the first targets of malicious insiders. With greater access than standard user accounts, privileged accounts provide a malicious insider with access to sensitive and confidential business information. Exabeam helps organizations detect and respond to unusual behavior by privileged accounts as well as privileged activity by non-privileged users. To do so, privileged accounts are defined during on-boarding or from contextual data ingested from directory services. Once privileged accounts are identified, Exabeam can detect suspicious behavior and misuse, such as: using a privileged account to elevate privileges to the user’s own account, abnormal access to classified or sensitive documents, or abusing the privileged access of service and executive accounts.
Failing to monitor and secure physical access can leave an organizations' personnel, information, equipment, IT infrastructure vulnerable to abuse or sabotage. Specifically, access to an organization's secure areas, equipment, or materials containing sensitive information makes it easier for a malicious insider to carry out cyber attacks.
Exabeam detects changes in user behavior, like when a user badges into a building for the first time or when a user travels the distance between two geographical locations at an impossible speed. These incidents could identify an employee who has shared their badge credentials, giving physical access to another employee, contractor, or partner, or it could be indicative of a malicious insider attempting to access, manipulate, or destroy critical physical assets. By analyzing both physical and virtual activity, Exabeam can help detect and respond to a user accessing physical spaces outside of typical usage patterns.
Shorter tenures at work and high employee turnover means many employees no longer feel the sense of loyalty they did in previous times. Unfortunately, this also means that when an employee decides to leave an organization, they are at a higher risk of becoming a malicious insider.
Exabeam helps identify and monitor users who are exhibiting signs of leaving an organization or communicating with a competitor to prevent malicious insiders from causing monetary, reputation, or operational harm to the organization before exiting: exfiltrating data, printing customer info, or stealing intellectual property to share with a competitor. Analysts can quickly determine if an employee is exhibiting signs of leaving based on rich-contextual information and specific activity patterns such as browsing job sites, uploading data to job search sites, or sending sensitive data to their personal email address. Customized response plans enable an analyst to take actions in response to a malicious insider who is exhibiting signs of leaving an organization or communicating with a competitor.
An employee performing authentication or access activities outside of their typical behavior patterns could indicate a malicious insider performing reconnaissance after hours. Analysts are often bombarded with authentication alerts, so a malicious attack can be easily overlooked.
Exabeam helps organizations detect and respond to malicious insiders performing abnormal authentication, and interactions outside of their typical usage or behavior patterns. To do so, Exabeam models the large volume of events to identify unusual behavioral patterns—such as activity at an unusual time, repeated failed logins to assets that have never been accessed, atypical account management activity—or a user whose behavior deviates from their peers. Data Insight Models provide security analysts with the reasoning and analysis behind behavioral models and rules. This takes the guesswork out of behavior-based investigation and provides security analysts with the evidence to feel confident about making a decision to investigate or dismiss an anomalous event.
The Gartner 2020 Market Guide for insider risk management
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