Revealing botnet membership using DNSBL counter-intelligence

  • Authors:
  • Anirudh Ramachandran;Nick Feamster;David Dagon

  • Affiliations:
  • College of Computing, Georgia Institute of Technology;College of Computing, Georgia Institute of Technology;College of Computing, Georgia Institute of Technology

  • Venue:
  • SRUTI'06 Proceedings of the 2nd conference on Steps to Reducing Unwanted Traffic on the Internet - Volume 2
  • Year:
  • 2006

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Abstract

Botnets--networks of (typically compromised) machines--are often used for nefarious activities (e.g., spam, click fraud, denial-of-service attacks, etc.). Identifying members of botnets could help stem these attacks, but passively detecting botnet membership (i.e., without disrupting the operation of the botnet) proves to be difficult. This paper studies the effectiveness of monitoring lookups to a DNS-based blackhole list (DNSBL) to expose botnet membership. We perform counter-intelligence based on the insight that botmasters themselves perform DNSBL lookups to determine whether their spamming bots are blacklisted. Using heuristics to identify which DNSBL lookups are perpetrated by a botmaster performing such reconnaissance, we are able to compile a list of likely bots. This paper studies the prevalence of DNSBL reconnaissance observed at a mirror of a well-known blacklist for a 45- day period, identifies the means by which botmasters are performing reconnaissance, and suggests the possibility of using counter-intelligence to discover likely bots. We find that bots are performing reconnaissance on behalf of other bots. Based on this finding, we suggest counterintelligence techniques that may be useful for early bot detection.