Hunting for the Undefined Threat: Advanced Analytics & Visualization

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Transcription:

SESSION ID: ANF-W04 Hunting for the Undefined Threat: Advanced Analytics & Visualization Joshua Stevens Enterprise Security Architect Hewlett-Packard Cyber Security Technology Office

Defining the Hunt Team

Cyber Defense Evolution Point Solutions Ad-hoc monitoring per device console SIEM/SOC Real-time monitoring of known threats Hunt Teams Find unknown threats, understand new adversary TTPs 1995 2000 2003 2006 2013 Log Mgmt Centralized ad-hoc monitoring Threat Intel Track known adversary IOCs, TTPs, intent

Hunt er Skillsets Cyber Security Intrusion Analysis Malware Analysis Threat Intelligence Data Science Data Management Data Visualization Statistics Programming Mindset Desire to learn Creative Analytical Red team Hunter

Hunt Processes Unstructured Hunt Exploratory data analysis Pattern discovery Structured Hunt Identify and search for indicators of compromise Real-time Monitoring Create or modify detection methods

The Need for Data and Security Analytics

Hiding in Plain Sight Known Threat Unknown Threat Matches a signature New behavior Goes to a bad place Goes to an approved place Works in the clear Works encrypted Unauthorized use Authorized use Outside of baseline Inside of baseline Within monitored infrastructure Outside monitored infrastructure Bad guys know how to stay inside the bell curve!

Security Analytics Comes in Different Flavors

A 13-billion Event Prototype

Security Analytics Prototype Anomaly Detection Distributed R (models) Causal Analysis Cluster Analysis Security Analytics What-If Analysis Raw Events Vertica Data Store Hadoop Connectors Normalized events SIEM Correlation Kafka/Storm Prototype Ingested events SIEM Logging

5 Hunt Team Use Cases

Case 1: Cluster Analysis for Hunt Team Managers

View: Proportional Relationships Less VPN traffic and more IPS traffic reveals blind spots

Apply Categorization SIEM categorization and destination port surfaces hostile events.

Case 2: Track Anomalies for Security Analysts

View: Events by High Severity Rating and Volume

Change View to Destination Type Display trend of unique destinations visited

Apply Anomaly Chart Graph filtered from billions of events Anomalous Event Uncover unique event, alerting next level of investigation.

Case 3: Analyze the Haystack for the Hunt Team

View: IPS Events for 45 days

Model IPS Events by Technique

Filter on the Return Traffic Display IPS evasion, recurring pattern and gaps in visibility.

Case 4: Behavioral Analysis for the Hunt Team

View: Non-Security Events in the Environment

A Typical View of VPN Logging by Source

Overlay VPN Source with Recon Events Correlate two sources of information to identify atypical behavior

Case 5: Advanced Analysis for the Hunt Team

Source Drilldown Reveals Subtle Patterns Horizontal line denotes large scale brute force attempts Time

In Closing Defining the Hunt Team Leveraging Data and Security Analytics An internal analytics prototype Use cases for the hunt team

Apply What You Have Learned Today 1 Week Give Analysts 4 hours/week for unstructured hunting 3 Months Build data science skills into your hunt team 6 Months Feedback lessons learned into other operational teams 1 Month Identify relevant data to begin hunting 4 Months Implement a Hunt practice Incorporate use cases

Questions?