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Threat Detection with "Zero-cost

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Tran Trung Hieu - Threat detection with 0 cost

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THREAT DETECTION WITH “ZERO-COST” @Lep @Neo @HieuTTMMO EagleEye Team
INDEX Threat Detection with Zero-cost 01 Abstract 03 Detection Strategy 02Detection Architecture 04Demo 05 Q&A
NUMBERS TELL STORIES: GLOBAL DWELL TIME It takes so long to detect badguys inside your organization. FireEye Mandiant M-Trends 2019 Special Report
1. Too many tools, too many solutions 2. Implement everything without a roadmap 3. Collect everything and forgetting about analysis 4. Forgetting about people 5. Forgetting about security fundamentals SECURITY COMMON PITFALLS
Threat Detection with “Zero-cost” Will be powerful Will enable hunters Will help to spot badguys ASAP
Threat Detection with “Zero-cost” Will not be easy Will not be a silver bullet Will not be really Zero-cost
THREAT DETECTION ARCHITECTURE
A system has capabilities to: 1. Centralize logging 2. Establish context 3. Real-time analysis 4. Historical analysis 5. Case management
THREAT DETECTION SYSTEM ARCHITECTURE
Key Takeaways
Data-gathering strategies Input-Driven Strategy Output-Driven Strategy DEFINITION • Collecting everything allows for analysis PROs • You have everything CONs • Hard for searching, hunting…etc • Slow and expensive DEFINITION • Collecting only what you need makes deployment and analysis easier PROs • Least expensive approach • Easier rollout and improved search performance CONs • Likely to miss something you did not know you needed Different types of event sources seem limitless and growing. We need to know what to collect and what to analyze.
Data Enrichment Proper log enrichment saves analysts time and adds detection capabilities. • We need data come with context • Applying log enrichment help to maximize log value: 1. GeoIP lookups 2. DNS lookups 3. Top 1 million websites tagging 4. Threat intelligence feeds 6. Base64 decoding Ordinary Extraordinary query: fireoscaptiveportal.com query: fireoscaptiveportal.com length: 23 reputation: Good top1m_rank: 5994 domain_freq: 9.0176 country: United States creation_date: 2017-06-16 destination_ASN: Amazon.com, Inc. (14618)
Data Broker Act as a buffer to handle bursts in log traffic or outages on another backend systems. BEFORE BROKER This design will FALL 1. Too much EPS 2. Heavy parsing or enrichment crashes the Processor 3. Storage overload cause dropping of inbound log
Data Broker Go broke or go home… AFTER BROKER This design will WIN 1. The Collector can handle tons of logs 2. The Processor will only fetch logs from the broker when it is ready. 3. Whenever the Storage starts to get overloaded, Processor will hold off all the log until Storage is back to normal state.
LOG STORAGE Storage must be designed to handle: • Handle large amounts of logs • Log retention • Fast search response times. Ideally is lower then 30 seconds • Proper classification of log data
SEE EVERYTHING MISS NOTHING Put in the reference threat detection architecture some Zero-cost solutions
Sysmon Free download tools from Windows Sysinternals kit Run as Windows system service Having capabilities to monitors so many things: • Processes • Registry • Network connections • Driver & DLL loading • Modifications of file • DNS Query https://docs.microsoft.com/en-us/sysinternals/downloads/sysmon
Elastalert Framework for alerting on anomalies, spikes, or other patterns of interest from data in Elasticsearch. Reliable, highly modular, and easy to set up and configure Several rule types with common monitoring paradigms: Built-in support for the following alert types: 1. Email 2. JIRA 3. OpsGenie 4. Commands 5. HipChat 6. MS Teams 7. AWS SNS 8. VictorOps 9. PagerDuty 10. PagerTree 11. Exotel 12. Twilio 14. Zabbix 15. Slack 16. Telegram 17. GoogleChat 18. Gitter 19. Line Notify https://github.com/Yelp/elastalert
Threat Detection Strategy
https://redcanary.com/resources/webinars/threat-hunting-with-attck-3-part-webinar-series/
Demo
T1100: Web Shell
T1086: Powershell T1102: Web Service
T1003 Credential Dumping
Thanks for your attention

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Threat Detection with "Zero-cost

  • 2. INDEX Threat Detection with Zero-cost 01 Abstract 03 Detection Strategy 02Detection Architecture 04Demo 05 Q&A
  • 3. NUMBERS TELL STORIES: GLOBAL DWELL TIME It takes so long to detect badguys inside your organization. FireEye Mandiant M-Trends 2019 Special Report
  • 4. 1. Too many tools, too many solutions 2. Implement everything without a roadmap 3. Collect everything and forgetting about analysis 4. Forgetting about people 5. Forgetting about security fundamentals SECURITY COMMON PITFALLS
  • 5. Threat Detection with “Zero-cost” Will be powerful Will enable hunters Will help to spot badguys ASAP
  • 6. Threat Detection with “Zero-cost” Will not be easy Will not be a silver bullet Will not be really Zero-cost
  • 8. A system has capabilities to: 1. Centralize logging 2. Establish context 3. Real-time analysis 4. Historical analysis 5. Case management
  • 9. THREAT DETECTION SYSTEM ARCHITECTURE
  • 11. Data-gathering strategies Input-Driven Strategy Output-Driven Strategy DEFINITION • Collecting everything allows for analysis PROs • You have everything CONs • Hard for searching, hunting…etc • Slow and expensive DEFINITION • Collecting only what you need makes deployment and analysis easier PROs • Least expensive approach • Easier rollout and improved search performance CONs • Likely to miss something you did not know you needed Different types of event sources seem limitless and growing. We need to know what to collect and what to analyze.
  • 12. Data Enrichment Proper log enrichment saves analysts time and adds detection capabilities. • We need data come with context • Applying log enrichment help to maximize log value: 1. GeoIP lookups 2. DNS lookups 3. Top 1 million websites tagging 4. Threat intelligence feeds 6. Base64 decoding Ordinary Extraordinary query: fireoscaptiveportal.com query: fireoscaptiveportal.com length: 23 reputation: Good top1m_rank: 5994 domain_freq: 9.0176 country: United States creation_date: 2017-06-16 destination_ASN: Amazon.com, Inc. (14618)
  • 13. Data Broker Act as a buffer to handle bursts in log traffic or outages on another backend systems. BEFORE BROKER This design will FALL 1. Too much EPS 2. Heavy parsing or enrichment crashes the Processor 3. Storage overload cause dropping of inbound log
  • 14. Data Broker Go broke or go home… AFTER BROKER This design will WIN 1. The Collector can handle tons of logs 2. The Processor will only fetch logs from the broker when it is ready. 3. Whenever the Storage starts to get overloaded, Processor will hold off all the log until Storage is back to normal state.
  • 15. LOG STORAGE Storage must be designed to handle: • Handle large amounts of logs • Log retention • Fast search response times. Ideally is lower then 30 seconds • Proper classification of log data
  • 16. SEE EVERYTHING MISS NOTHING Put in the reference threat detection architecture some Zero-cost solutions
  • 17. Sysmon Free download tools from Windows Sysinternals kit Run as Windows system service Having capabilities to monitors so many things: • Processes • Registry • Network connections • Driver & DLL loading • Modifications of file • DNS Query https://docs.microsoft.com/en-us/sysinternals/downloads/sysmon
  • 18. Elastalert Framework for alerting on anomalies, spikes, or other patterns of interest from data in Elasticsearch. Reliable, highly modular, and easy to set up and configure Several rule types with common monitoring paradigms: Built-in support for the following alert types: 1. Email 2. JIRA 3. OpsGenie 4. Commands 5. HipChat 6. MS Teams 7. AWS SNS 8. VictorOps 9. PagerDuty 10. PagerTree 11. Exotel 12. Twilio 14. Zabbix 15. Slack 16. Telegram 17. GoogleChat 18. Gitter 19. Line Notify https://github.com/Yelp/elastalert
  • 20.
  • 21.
  • 23. Demo
  • 27.
  • 28. Thanks for your attention