Sherlocked Security – Managed UEBA (User & Entity Behavior Analytics)

Proactive threat detection powered by behavior analytics to identify anomalies in user and entity activities, helping organizations detect insider threats, compromised accounts, and other sophisticated security risks.

1. Statement of Work (SOW)

Service Name: Managed UEBA
Client Type: Organizations seeking advanced detection of insider threats, compromised accounts, and anomalous behaviors across users and entities
Service Model: Managed service that utilizes User and Entity Behavior Analytics (UEBA) to monitor, detect, and respond to suspicious activity
Compliance Alignment: ISO 27001, SOC 2, HIPAA, PCI-DSS, GDPR, NIST CSF

Scope Includes:

Deployment and configuration of UEBA platforms (e.g., Sumo Logic, Exabeam, Varonis, Microsoft Sentinel)
Continuous monitoring of user and entity activities for behavioral anomalies
Advanced analytics to detect patterns indicative of malicious or unauthorized activity
Integration of user and entity data sources to establish baseline behavior
Real-time alerts for suspicious activities and behavior deviations
Incident response workflows triggered by detected anomalies
Reporting and ongoing tuning of detection models to reduce false positives

2. Our Approach

[Behavioral Analytics] → [Data Collection & Integration] → [Anomaly Detection] → [Incident Response] → [Reporting & Tuning]

Behavioral Analytics: Leverage machine learning and statistical analysis to profile typical behavior and detect deviations indicating potential threats.
Data Collection & Integration: Collect data from various sources, including user logins, file access, network traffic, and endpoint activities.
Anomaly Detection: Identify and classify abnormal user and entity behaviors (e.g., data exfiltration, privilege escalation, unusual access patterns).
Incident Response: When suspicious behavior is detected, automated workflows trigger actions such as user isolation, alerting the SOC, and further investigation.
Reporting & Tuning: Provide regular reports on detected incidents and continuously improve detection models based on feedback and incident analysis.

3. Methodology

Data Collection: We integrate and collect data from your organization’s user and entity systems (e.g., Active Directory, cloud applications, servers, and endpoints).
Behavior Baseline: Establish a baseline of normal user and entity behavior using historical data and machine learning algorithms.
Anomaly Detection: Use statistical models and AI to detect deviations from established baselines that may indicate potential threats.
Threat Intelligence Integration: Enhance anomaly detection with threat intelligence feeds to contextualize suspicious behavior.
Incident Response Playbooks: When an anomaly is detected, predefined playbooks are triggered to contain the incident, alert relevant stakeholders, and initiate further analysis.
Reporting: We provide detailed reports on security incidents, including the nature of the detected anomaly, the response actions taken, and recommendations for prevention.
Continuous Optimization: We continuously tune the UEBA platform to reduce false positives, enhance detection accuracy, and improve response efficiency.

4. Deliverables

UEBA Integration: Integrated UEBA platform with your infrastructure to monitor user and entity behaviors in real-time.
Behavioral Baseline Models: Tailored baseline models for user and entity behavior based on historical and ongoing data.
Anomaly Detection: Real-time alerts for anomalies in user and entity behaviors, including privileged actions, data access patterns, and more.
Incident Response: Automated or manual response to suspicious activities, with clear playbooks for containment and investigation.
Reporting: Regular reports detailing detected incidents, analysis of anomalies, and suggestions for reducing future risks.
Optimization: Ongoing tuning of the UEBA platform and anomaly detection models to improve accuracy and reduce false positives.

5. Client Requirements

Access to User & Entity Data: Data sources such as logs from Active Directory, Office 365, cloud applications, firewalls, endpoints, and network traffic.
Security Policies: Defined incident response and security policies to guide rule and playbook creation for anomaly detection.
Collaboration with SOC: Collaboration between the client’s internal security team and the managed security provider for incident escalation and resolution.
Historical Behavior Data: Access to past user and entity behavior data to help establish baseline behavior profiles and patterns.

6. Tooling Stack

UEBA Platforms: Exabeam, Sumo Logic, Varonis, Microsoft Sentinel, LogRhythm
Endpoint Detection & Response (EDR): CrowdStrike, SentinelOne, Carbon Black
SIEM Platforms: Splunk, QRadar, LogRhythm
Security Orchestration, Automation, and Response (SOAR): Cortex XSOAR, D3 Security, Swimlane
Threat Intelligence Feeds: MISP, IBM X-Force, ThreatConnect

7. Engagement Lifecycle

Discovery & Planning: Understand your infrastructure, data sources, and threat landscape.
UEBA Platform Integration: Integrate and configure the UEBA platform with your data sources and security systems.
Behavioral Baseline Creation: Create baseline behavior profiles for users and entities.
Anomaly Detection and Fine-Tuning: Set up detection rules and fine-tune the platform to recognize deviations from established baselines.
Incident Response Playbook Design: Develop automated and manual incident response workflows for detected anomalies.
Testing & Validation: Test the system to ensure it accurately detects true anomalies and minimizes false positives.
Continuous Monitoring & Optimization: Provide 24×7 monitoring, ongoing tuning, and periodic reviews to improve the effectiveness of the UEBA system.
Reporting & Review: Provide reports on the effectiveness of the service and actionable recommendations for improvement.

8. Why Sherlocked Security?

Feature	Sherlocked Advantage
Advanced Anomaly Detection	Detect abnormal behavior using machine learning algorithms and statistical analysis
User & Entity Behavior Profiling	Establish comprehensive behavioral baselines for all users and entities in your network
Real-Time Monitoring	24×7 monitoring for deviations in user and entity behavior with rapid response capabilities
Threat Intelligence Integration	Enhance detection accuracy by incorporating global threat intelligence feeds
Automated Response	Automatically trigger incident response workflows to contain and resolve detected threats
Reduced False Positives	Continuous fine-tuning of detection models to ensure accuracy and minimize disruptions
Comprehensive Reporting	Detailed reporting on detected anomalies, investigations, and responses for continuous improvement
Scalable and Flexible	Scalable platform that adapts as your organization grows and evolves

9. Use Cases

Use Case 1: Insider Threat Detection

Alert: An employee accesses sensitive financial data at unusual hours.
Custom Rule: A UEBA rule flags this activity as anomalous based on the employee’s typical access patterns.
Playbook: An automated playbook is triggered to isolate the employee’s account and alert the SOC for further investigation.
Escalation: SOC team investigates and identifies the employee’s account was compromised by an external actor.
Resolution: The account is locked, and the threat actor is removed from the network.
Reporting: Incident report outlines the investigation, actions taken, and recommendations to prevent similar incidents.

Use Case 2: Compromised Account Detection

Alert: A user logs in from an unusual geographic location outside their normal work hours.
Custom Rule: UEBA flags the login attempt as anomalous based on historical login patterns and geographic location.
Playbook: Automated playbook triggers an account lock and sends an alert to the SOC for further review.
Escalation: SOC team confirms the account was compromised through phishing, and the attack vector is mitigated.
Resolution: The user’s account is secured with multi-factor authentication (MFA), and a full investigation is conducted.
Reporting: Incident report includes detailed findings, corrective actions, and recommendations for improving account security.

10. Managed UEBA Readiness & Ops Checklist

UEBA Integration

[ ] Ensure proper integration with user and entity data sources (e.g., Active Directory, cloud apps, endpoints).
[ ] Confirm that the UEBA system is fully integrated with SIEM and other security tools for optimal threat detection.
[ ] Verify that data feeds are correctly configured and monitored for integrity.

Behavioral Baseline Development

[ ] Establish baseline behavior profiles for users and entities based on historical data.
[ ] Identify and classify key user activities that should be monitored (e.g., file access, login times, privilege escalation).
[ ] Implement machine learning and statistical algorithms to adapt to behavior changes over time.

Anomaly Detection & Response

[ ] Develop detection rules to flag deviations from established behavior baselines (e.g., unusual access times, data exfiltration).
[ ] Set up automated response playbooks to isolate accounts or systems involved in suspicious activity.
[ ] Continuously fine-tune detection algorithms to minimize false positives and improve accuracy.

Incident Handling & Reporting

[ ] Ensure incidents are reported in a timely manner, with clear details on the detected anomaly, investigation, and response.
[ ] Provide regular reporting on incident trends, system performance, and areas for further tuning.
[ ] Ensure that incident response workflows are reviewed and updated based on lessons learned from previous cases.

Managed UEBA