Splunk Live in RTP - March-2014-Jeff-Bollinger-Cisco

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How Cisco Infosec uses Splunk to develop and execute their Incident Response playbook strategy.

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  • Trying to protect?
    infrastructure
    intellectual property
    customer and employee data
    brand reputation
    What are the threats?
    Malware gone wild
    Targeted attacks
    Rogue insiders
    Mismanagement
    How do I discover them?
    Security monitoring
    Logging and event retrieval
    Operational intelligence
    How do we respond?
    IR process
    Identification
    Isolation
    Remediation
  • Lots of sensors
    Defense in depth
    Log collection
    Log analysis
  • Old Way: (SIEM approach, and our early v1 approach with Splunk)
    Dependent upon vendors to write queries for you or to have a magic box or algorithm that will find it all
    Tuning can be an issue within a SIEM if you can’t do it from the event source itself (i.e. wheat from chaff problem)
    New Way: data-centric playbook approach using log data and Splunk (v2)
    Flexible & easily adaptable for updates, and tactical changes
    Totally custom upfront, but work savings after plays are operationalized
    Topical, relevant, and current research can be deployed quickly, even as a simple test for a larger operations
  • In terms of Incident Response a playbook is….
  • Cisco indexes between 150 and 300 Gb of WSA data per day
  • Splunk Live in RTP - March-2014-Jeff-Bollinger-Cisco

    1. 1. Copyright © 2014 Splunk Inc. Splunk the SIEM Jeff Bollinger 0x506682C5 Technical Leader and Infosec Investigator: CSIRT Cisco Systems, Inc. https://blogs.cisco.com/author/jeffbollinger/ https://twitter.com/jeffbollinger
    2. 2. About Me... – Cisco Computer Security Incident Response Team (CSIRT) – CSIRT = Security Monitoring and Incident Response – Architecture, Engineering, Research, and Investigations – Enterprise global threat and 24x7 incident response
    3. 3. The Numb3rs Cisco Systems Inc.: –100 countries –130,000 employees (with laptops and phones) –150,000 servers of all types –40,000 routers –1,500 labs –1 CSIRT analyst for every 7,000 employees
    4. 4. The Numb3rs Cisco indexes almost 1Tb of log data per day
    5. 5. Incident Response Basics •What am I trying to protect? •What are the threats? •> How do I detect them? •How do we respond?
    6. 6. How Do I Detect?
    7. 7. Out With The Old • You don’t know what you don’t know • Buy and trust a SIEM to run canned reports • Wait for updates from the vendor • Try to edit/create custom reports • Build your own collection infrastructure • Data-centric approach • Build your own reports • Research your own intelligence • Operationalize and optimize! The Old Way The New Way
    8. 8. playbook | plā bŏk|ˈ ˌ (noun) A prescriptive collection of repeatable queries (reports) against security event data sources that lead to incident detection and response. Analyze: SIEM
    9. 9. A Note on Strategy Hunting vs. Gathering
    10. 10. Hunting: Build a Query – Find Bad Stuff • Start with the obvious and simple: index=wsa earliest=-24h x_wbrs_score=ns English translation: Splunk, look at our web proxy logs over the past 24 hours, and give me all the web sites (objects) that had no known reputation score.
    11. 11. Hunting: Build a Query – Find Bad Stuff index=wsa earliest=-24h x_wbrs_score=ns Let me stop you right there…
    12. 12. Hunting: Build a Query – Find Bad Stuff • Filter based on unique attributes: index=wsa earliest=-24h x_wbrs_score=ns |where isnull(cs_referer) English translation: Splunk, look at our web proxy logs over the past 24 hours, and give me all the web sites (objects) that had no known reputation score, and there was no HTTP referrer.
    13. 13. Hunting: Build a Query – Find Bad Stuff index=wsa earliest=-24h x_wbrs_score=ns | where isnull(cs_referer) Ok getting better, sort of…
    14. 14. Hunting: Build a Query – Find Bad Stuff • Filter, refine, filter, refine: index=wsa earliest=-24h application/x-dosexec ns GET 200 x_wbrs_score=ns cs_method=GET sc_http_status=200 cs_mime_type=application/x-dosexec (java OR MSIE) NOT (mirror OR cdn) | where isnull(cs_referer) English translation: Splunk, query our web proxy logs over the past 24 hours, and give me all the web sites (objects) that had no known reputation score, and there was no HTTP referrer, where either Java or Internet Explorer successfully downloaded an executable file from a site that didn’t have ‘mirror’ or ‘CDN’ in the URL.
    15. 15. Hunting: Build a Query – Find Bad Stuff Here we go! index=wsa earliest=-24h application/x-dosexec ns GET 200 x_wbrs_score=ns cs_method=GET sc_http_status=200 cs_mime_type=application/x-dosexec (java OR MSIE) NOT (mirror OR cdn) | where isnull(cs_referer)
    16. 16. Gathering: Build a Query – Find Bad Stuff If you can find or create a re-usable pattern, you can save a search, make a report, and automate! 16
    17. 17. Gathering: Build a Query – Find Bad Stuff For example: this query will detect the Tracur clickfraud trojan: index=wsa earliest=-6h@h m cs_url="*/m/*” MSIE (NOT (cs_referer="*")) | regex cs_url="^http://(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?). (25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?).(25[0-5]|2[0-4][0-9]|[01]?[0- 9][0-9]?).(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)/m/[A-Za-z0-9/+] {50,1000}$" http://www.microsoft.com/security/portal/threat/encyclopedia/entry.aspx?Name=Trojan%3aWin32%2fTracur
    18. 18. Do It Yourself Once you have: • Solid, repeatable, saved searches • Research and intelligence gathering • Consistent handling procedures • Documentation and tuning You have your own SIEM, running in Splunk, and completely custom to your organization.
    19. 19. Thank you

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