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SplunkLive! Boston
Jason Pufahl, Chief Information
Security Officer
About Jason
•  Chief Information Security Officer at the University of
Connecticut
Current Date:
Original Issues
•  Not enough people had access to the data
o  Making sense of the data for non-technical types and visualizations
o  Today: 130 people with access to Splunk, widely viewed as a resource
•  Decentralized IT structure doesn’t allow for a full scope
across departments
•  Incident response times and capacity planning
•  Helping law enforcement
o  Track down missing students
o  Find stolen IT assets
Current Date:
Decreasing Incident Response Times
•  Heavily centralized the authentication system + Splunk allows
us to correlate locations and incidents
•  Response times have decreased from hours to minutes
•  Example: servicing law enforcement request dropped from
3 day turnaround to 20 minutes
Current Date:
Data Sources and Splunk Apps
•  Data: Firewalls, IPS, DHCP, Antivirus, NAC, web servers,
Active Directory, Exchange, VMware, SCCM, switches,
custom applications, many others
•  Apps: Splunk for Exchange, Splunk for AD, Splunk on
Splunk, Google Maps, DNS, DB Connect, Deployment
monitor, many custom apps and commands
•  Volume: 90 to 180 GB/day (rare spikes during data intake of
new departments)
Current Date:
Encouraging Departments to
Understand their Data
•  Encourages standardizing of operating systems
•  SecureU initiative
o  If you run an IT device of some sort, your log data has to be collected
o  Each school/division gets 2 gigs each thus increased adoption
•  Allows for central IT to see trends across entire University
•  Reports sent to Deans, Directors at each department
o  Encourages healthy competition for security compliance
•  The “Security Score”
o  Getting university departments to understand importance of security and value
Current Date:
Encouraging Departments to
Understand their Data (example)
Operating System demographics
Current Date:
Encouraging Departments to
Understand their Data (example)
Operating
Systems
by population
Current Date:
Encouraging Departments to
Understand their Data (example)
Departmental Antivirus demographics
Current Date:
Demographics by Campus (example)
Campus Antivirus demographics
Current Date:
•  Alerts set for stolen IT assets when they get back on the
network
o  MACs of lost devices flagged => triggers Splunk alert
•  Missing person’s alerts? Well they aren’t missing, they just
aren’t calling Mom back – they’ve been on the network
•  Resolving a bomb threat
o  Able to identify culprit due to accessory data collected by
Splunk
o  "Fringe" data can be security data too
Helping Law Enforcement
Current Date:
GeoIP Analysis
Goal:
Flag user logins occurring further from campus than the user norm
(e.g. Phishing attack immediately followed by login from China,
Russia)
Search foundation:
sourcetype="vpn" "Login succeeded" | table src_ip, netid | geoip
src_ip | haversine origin="41.808333,-72.249444"
inputFieldLat=src_ip_latitude inputFieldLon=src_ip_longitude
units=mi | stats max(mi) by netid, geo_info
Current Date:
GeoIP Analysis
VPN logins
over 24h
Current Date:
Capacity Planning
•  Splunk allows us to see and anticipate which wired and
wireless points on campus are being used at which times of
day to allocate accordingly
•  Two examples :
o  Single sign on authentication via CAS: rate of usage over
time
o  Wireless networks: utilization high water marks over time
Current Date:
Capacity Planning (example)
Capacity planning
as influenced by
rate of growth
(Single sign on)
Current Date:
Capacity Planning (example)
Capacity planning
as influenced by
rate of growth
(Wireless network)
Current Date:
Protecting Against Breaches and Fines for
Personal Identifiable Information
•  Used Splunk to identify PII across systems
o  DLP tool finds the PII and Splunk used for reporting
o  Removed to avoid breaches and fines
•  Identified PII used in security score
o  Avoided millions in fines
o  Increased program participation
Current Date:
Future Goals and Plans
•  Doing more correlation across systems and become more
proactive
o  e.g., across auth systems, AV, NAC, IPS, and PII to provide granular and
actionable threat prioritization
•  UCONN as a service provider for other educational facilities
across the state of Connecticut
Current Date:
Results/ROI
•  Response times have decreased from hours to minutes
•  Standardized operating systems
•  Changed each department’s behavior to encourage upgrading
anti-virus software and security measures
•  Huge risk reduction
•  Saved millions in potential fines from PII and breaches
Current Date:

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SplunkLive! Boston June 2013 - UCONN

  • 1. SplunkLive! Boston Jason Pufahl, Chief Information Security Officer
  • 2. About Jason •  Chief Information Security Officer at the University of Connecticut Current Date:
  • 3. Original Issues •  Not enough people had access to the data o  Making sense of the data for non-technical types and visualizations o  Today: 130 people with access to Splunk, widely viewed as a resource •  Decentralized IT structure doesn’t allow for a full scope across departments •  Incident response times and capacity planning •  Helping law enforcement o  Track down missing students o  Find stolen IT assets Current Date:
  • 4. Decreasing Incident Response Times •  Heavily centralized the authentication system + Splunk allows us to correlate locations and incidents •  Response times have decreased from hours to minutes •  Example: servicing law enforcement request dropped from 3 day turnaround to 20 minutes Current Date:
  • 5. Data Sources and Splunk Apps •  Data: Firewalls, IPS, DHCP, Antivirus, NAC, web servers, Active Directory, Exchange, VMware, SCCM, switches, custom applications, many others •  Apps: Splunk for Exchange, Splunk for AD, Splunk on Splunk, Google Maps, DNS, DB Connect, Deployment monitor, many custom apps and commands •  Volume: 90 to 180 GB/day (rare spikes during data intake of new departments) Current Date:
  • 6. Encouraging Departments to Understand their Data •  Encourages standardizing of operating systems •  SecureU initiative o  If you run an IT device of some sort, your log data has to be collected o  Each school/division gets 2 gigs each thus increased adoption •  Allows for central IT to see trends across entire University •  Reports sent to Deans, Directors at each department o  Encourages healthy competition for security compliance •  The “Security Score” o  Getting university departments to understand importance of security and value Current Date:
  • 7. Encouraging Departments to Understand their Data (example) Operating System demographics Current Date:
  • 8. Encouraging Departments to Understand their Data (example) Operating Systems by population Current Date:
  • 9. Encouraging Departments to Understand their Data (example) Departmental Antivirus demographics Current Date:
  • 10. Demographics by Campus (example) Campus Antivirus demographics Current Date:
  • 11. •  Alerts set for stolen IT assets when they get back on the network o  MACs of lost devices flagged => triggers Splunk alert •  Missing person’s alerts? Well they aren’t missing, they just aren’t calling Mom back – they’ve been on the network •  Resolving a bomb threat o  Able to identify culprit due to accessory data collected by Splunk o  "Fringe" data can be security data too Helping Law Enforcement Current Date:
  • 12. GeoIP Analysis Goal: Flag user logins occurring further from campus than the user norm (e.g. Phishing attack immediately followed by login from China, Russia) Search foundation: sourcetype="vpn" "Login succeeded" | table src_ip, netid | geoip src_ip | haversine origin="41.808333,-72.249444" inputFieldLat=src_ip_latitude inputFieldLon=src_ip_longitude units=mi | stats max(mi) by netid, geo_info Current Date:
  • 13. GeoIP Analysis VPN logins over 24h Current Date:
  • 14. Capacity Planning •  Splunk allows us to see and anticipate which wired and wireless points on campus are being used at which times of day to allocate accordingly •  Two examples : o  Single sign on authentication via CAS: rate of usage over time o  Wireless networks: utilization high water marks over time Current Date:
  • 15. Capacity Planning (example) Capacity planning as influenced by rate of growth (Single sign on) Current Date:
  • 16. Capacity Planning (example) Capacity planning as influenced by rate of growth (Wireless network) Current Date:
  • 17. Protecting Against Breaches and Fines for Personal Identifiable Information •  Used Splunk to identify PII across systems o  DLP tool finds the PII and Splunk used for reporting o  Removed to avoid breaches and fines •  Identified PII used in security score o  Avoided millions in fines o  Increased program participation Current Date:
  • 18. Future Goals and Plans •  Doing more correlation across systems and become more proactive o  e.g., across auth systems, AV, NAC, IPS, and PII to provide granular and actionable threat prioritization •  UCONN as a service provider for other educational facilities across the state of Connecticut Current Date:
  • 19. Results/ROI •  Response times have decreased from hours to minutes •  Standardized operating systems •  Changed each department’s behavior to encourage upgrading anti-virus software and security measures •  Huge risk reduction •  Saved millions in potential fines from PII and breaches Current Date: