Insider threats, both intentional and through negligence, can lead to huge losses. Organizational infrastructures and cybersecurity environments have become so complex that detecting insider threats is very time consuming.
OpenText™ Core Behavioral Signals is a behavioral analytics solution that uses unsupervised machine learning and UEBA cybersecurity to identify hidden threats within your organization. It automatically adapts to your environment, detects anomalous behavior, and helps threat hunters and security analysts act faster by surfacing the most relevant leads—no rule writing required.
OpenText Core Behavioral Signals uses AI to detect behavioral anomalies in real time, helping security teams uncover advanced threats, reduce alert noise, and cut investigation time.
[OpenText Core Behavioral Signals] highlighted interesting behaviors in some of our applications that provided valuable intelligence. Having a deep insight into how our staff use the environment gives us the opportunity to spot anomalous behaviors and stop a malicious actor faster.
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From insider risks to compromised credentials, OpenText Core Behavioral Signals provides threat hunting tools that reveal hard-to-detect threats through behavioral insights.
Identify employees or contractors behaving out of character—before data exfiltration or sabotage occurs. Behavioral baselines adapt in near real time to flag risky deviations.
Spot threats that don’t match known IOCs or signatures. Behavior-based detection uncovers novel attack techniques before they escalate.
Filter out the noise and get high-priority leads. OpenText Core Behavioral Signals surfaces real threats with rich context, reducing analyst workload.
Detect stolen credentials through behavior anomalies like unusual login times, privilege changes, or lateral movement—without creating rules.
Uncover low-and-slow threats by spotting changes in behavior of previously quiet accounts. This tactic is essential for detecting long-dwell intrusions.
Catch suspicious access to sensitive data and IP—before it’s leaked or shared. Behavioral context helps stop accidental or malicious misuse quickly.
Surface real risks faster using behavioral analytics, UEBA, and unsupervised machine learning—no tuning or rule-writing required.
Continuously monitors user and entity behavior to uncover suspicious activity, even when threats evolve or mimic normal behavior.
Learns normal behavior patterns from your data automatically—no need for labeled data or manual rule creation.
Transforms raw logs into prioritized threat leads by identifying behavior that deviates significantly from the norm.
Helps threat hunters move quickly by surfacing enriched leads that reduce investigation time and cognitive overload.
OpenText Core Behavioral Signals
Organizational risk at a glance |
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Dynamic anomaly and risk timelines |
Fully transparent alerts |
Analyst collaboration |
MITRE ATT&CK mapping |
Raw events viewer |
APIs for SOAR and trouble ticketing system |
CrowdStrike Falcon data support |
Public cloud |
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Explore the complex issue of insider threats. From 3rd party risks to phishing and ransomware.
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