~/talk

Zero Days, Thousands of Nights: The Life & Times of Zero-Day Vulns and Their Exploits

Talkat Black Hat Europe 2017 · 2017-12-04..12-07· [security, data-engineering]
links:none on file
slides:none on file

RAND analyzes a private dataset of ~200 zero-days spanning 14 years from 64 vendors and finds over half still unknown, an average lifespan of ~7 years, and a median ~6% per year collision rate (drops to <1% over 90 days). Exploit development is fast—70% of exploits developed within a month, 31% within a week. Memory corruption dominates; mitigations shift attackers from stack to heap. Purchased bugs (4%) die quickly; hypervisor/AV bugs remain largely viable.

AI-written summary · about

  1. 0:00Intro
  2. 3:00The decision calculus is complicated
  3. 6:15We focus on characteristics of the vulnerabilities
  4. 8:43Various groups search for vulnerabilities
  5. 12:20BUSBY finds zero-day vulnerabilities, and develops exploits for them
  6. 14:10Data stats: three main types of vulnerabilities
  7. 14:37Vulnerability Sub-Type: Memory Corruption
  8. 14:58Vulnerability Sub-Type: Memory Mismanagement
  9. 15:14Vulnerability Sub-Type: Logic
  10. 15:30Data stats: number of vulnerabilities per source code type
  11. 15:44Data stats: number of vulnerabilities found and exploited, by vendor
  12. 16:29Some other observations about the data
  13. 19:15Exploit development time is relatively short
  14. 20:20Mitigations have affected exploitability (e.g., heap vs stack overflow)
  15. 21:35Exploit development career lengths vary
  16. 24:32There are some caveats to our research
  17. 25:49Life Status
  18. 26:37About 1 in 6 of the alive are immortal
  19. 27:01Patches killed most of the dead
  20. 27:35Code revisions created a bunch of code refactored "zombies"
  21. 28:13Longevity
  22. 30:43We plotted the survival probability of our data
  23. 31:34Average life expectancy is nearly 7 years
  24. 32:03Do certain characteristics indicate a long or short life?
  25. 34:34Does life expectancy or survival probability change over time?
  26. 35:19Collision Rate
  27. 37:18Clarity about time intervals is important
  28. 39:52Implications and recommendations of findings
  29. 41:48Our findings can help inform the retain vs. disclose discussions
  30. 43:03Zero-days affect many sectors, and raise policy questions
  31. 44:28Key findings
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