Data anomaly detection in Log360

Detect unusual activity across users, systems, and applications in real time. Log360 combines machine learning (ML), behavioral analytics, and entity risk scoring to reveal deviations, reduce false positives, and help security teams respond quickly to emerging threats.

How Log360 detects anomalies

Log360's anomaly detection is powered by multiple approaches that work together to reveal meaningful deviations:

 

Cloud-delivered rules: Detection rules are maintained and continuously updated to identify well-documented anomalies. These rules cover suspicious process launches, privilege misuse, insider-driven activities, and more.

 

Behavioral baselines: Every user, device, and application is continuously monitored to establish what normal looks like. When activity diverges (for example, a user downloading far more data than usual), it is flagged as anomalous.

 

Entity risk scoring: Deviations are evaluated against the context of the entity. An unusual process execution on a domain controller carries a higher weight than the same event on a test machine.

 

Pattern-based analysis: Beyond single event outliers, Log360 models time-based and sequence-based deviations to spot multi-stage attacks that develop over days or weeks

  • Centralized anomaly visibility
  • Precision tuning to reduce false positives
  • Investigate and respond in real time

Centralized anomaly visibility

Anomalies from across the IT landscape converge on a unified dashboard. From here, analysts can:

  • View anomalies grouped by the entity, anomaly, or risk score.
  • Correlate new deviations with historical activity to see if the behavior is part of a broader pattern.
  • Map anomalies to MITRE ATT&CK® tactics and techniques to guide investigation.
  • Drill into raw log data behind each anomaly for forensic clarity.
Centralized anomaly visibility

Precision tuning to reduce false positives

False positives drain analysts' time. Log360 includes multiple tuning mechanisms to ensure anomaly alerts are meaningful:

  • Object-level filtering: Routine processes or scheduled tasks can be excluded from detection, preventing unnecessary alerts.
  • Adaptive thresholds: ML-driven thresholds adjust automatically as usage patterns change, so alerts remain accurate without constant manual input.
  • Peer group analysis: Entities are compared to their peers. A spike in logins from a global admin is treated differently than the same activity from a temporary contractor.
  • Rule optimization guidance: Log360 highlights rules that frequently trigger non-critical anomaly alerts, suggesting refinements.
Precision tuning to reduce false positives

Investigate and respond in real time

Detecting anomalies is only useful if teams can act on them quickly. Log360 streamlines the process from threat detection to response:

  • Context-rich alerts: Each anomaly alert includes risk scores, linked entities, past activity, and the raw log data for verification. Analysts don’t need to jump between tools to piece together the story.
  • Anomaly timelines: Log360 builds chronological views of related events, making it easy to see whether an anomaly is isolated or part of a broader attack chain.
  • Automated response actions: Predefined workflows enable teams to immediately disable suspicious accounts, terminate malicious processes, or block IP addresses when anomalies reach a certain risk level.
  • Escalations and integrations: Anomaly alerts can be pushed to ITSM tools like ServiceNow and Jira or escalated to SOC workflows for deeper incident handling.
  • Investigation assistance: AI-driven recommendations and mapped MITRE ATT&CK tactics and techniques guide analysts on the next steps to take, reducing manual guesswork and speeding up resolution.
Investigate and respond in real time

Key anomaly detection use cases

By establishing baselines for normal login patterns such as the time, location, and device, Log360 spots unusual access behavior like off-hours activity, impossible travel, or repeated failed logins. Peer group comparisons and risk scoring help teams separate legitimate travel from brute-force attempts. Log360 flags suspicious password changes across Windows, workstations, and Microsoft SQL Server, including resets on sensitive accounts like the Directory Services Restore Mode admin. It also highlights excessive login failures, account lockouts, and long gaps without a password reset in Microsoft 365.

Unusual privilege escalation or the abnormal use of elevated accounts is flagged immediately. If a user suddenly gains admin rights or accesses systems outside their role, Log360 highlights the deviation and prioritizes it with entity risk scoring. This includes unauthorized group or GPO deletions, off-hours GPO changes, and suspicious registry access in Windows. It also covers conditional access policy changes in Microsoft 365 and unapproved rule changes across firewalls and SaaS platforms from providers such as Sophos, Fortinet, and SonicWall.

Adversaries often abuse system tools. Log360’s rules detect rare or obfuscated command usage and suspicious child process activity, such as PowerShell spawning unusual processes or Regsvr32 running with uncommon flags. It also monitors privileged command execution on Unix, IIS FTP, Microsoft SQL Server, and Check Point devices, and failed attempts or scheduled tasks created outside of working hours are treated as signs of persistence or reconnaissance..

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Spikes in downloads, file transfers, or uploads to unapproved cloud apps are detected by comparing them against established baselines. Analysts get alerts with risk scoring to judge whether the behavior is routine or a potential breach. Other signals include excessive file changes or deletions on Windows, abnormal surges in Microsoft 365 file deletions, bulk data transfers in Salesforce, and unusual email activity such as large volumes of emails sent to a single recipient.

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Slow-moving threats are uncovered by linking anomalies across time, such as unusual login patterns combined with rare process execution and abnormal file access. This correlation reveals campaigns that would otherwise be missed. Examples include Salesforce user setting changes, app integrations after hours, unauthorized firewall or policy modifications, and unusual mailbox access in Microsoft 365—all of which point to insider misuse or persistent attack activity.

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Discover more with Log360

 

Threat investigation

Utilize Log360's Incident Workbench to delve into security alerts, correlate events, and trace attack paths. This analytical console offers a unified view of core entities like users, processes, and threat sources, enabling swift identification of the root cause of incidents.

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Compliance reporting

Generate audit-ready reports for standards such as ISO/IEC 27001, the GDPR, the PCI DSS, and HIPAA. Custom report templates make evidence collection faster and more reliable.

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SOAR and workflow automation

Automate repetitive response tasks like account suspension or IP blocking. Orchestrate actions across integrated tools to reduce the response time and analyst workload.

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AD auditing

Monitor user logins, group changes, GPO modifications, and privileged account activity in real time to safeguard critical identity infrastructure.

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  •  

    We wanted to make sure that one, we can check the box for different security features that our clients are looking for us to have, and two, we improve our security so that we can harden our security footprint.

    Carter Ledyard

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    The drill-down options and visual dashboards make threat investigation much faster and easier. It’s a truly user-friendly solution.

    Sundaram Business Services

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    Log360 helped detect insider threats, unusual login patterns, privilege escalations, and potential data exfiltration attempts in real time.

    CIO, Northtown Automotive Companies

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    Before Log360, we were missing a centralized view of our entire infrastructure. Now, we can quickly detect potential threats and respond before they escalate.Log360 has been invaluable for improving our incident response and ensuring compliance with audit standards. It’s a game-changer for our team.

    ECSO 911

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Frequently Asked Questions

It's the process of identifying unusual activity patterns such as logins, processes, or data movements that deviate from established baselines and may indicate malicious behavior.

Log360 uses multiple detection techniques to identify security threats accurately. Static, rule-based detection looks for predefined attack patterns such as multiple failed logins or privilege changes. Correlation-based detection connects events across systems to uncover multi-stage attacks that single alerts might miss. Anomaly detection goes a step further by learning the normal behavior for each user, device, and application, then flagging activity that deviates from these baselines. Together, these methods help teams detect both known and unknown threats in real time.

The solution ingests logs from servers, applications and network devices. This wide scope helps it correlate user activity with entity behavior for more accurate anomaly detection.

Yes. Insider threats are difficult to detect because they often involve legitimate user accounts performing harmful actions. Log360’s anomaly detection engine identifies subtle behavioral deviations, such as unusual data transfers, privilege escalations, or login activity outside normal work hours, that static alerts may overlook. By establishing baselines for each user and comparing real-time activity against them, Log360 helps teams detect misuse early and minimize damage.

See what normal looks like—and what it doesn’t look like

Establish baselines for user and system activity, detect anomalies instantly, and protect your environment.