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A Multifaceted Approach to Understanding the Botnet Phenomenon Authors : Moheeb Abu Rajab, Jay Zarfoss, Fabian Monrose, Andreas Terzis Computer Science.

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Presentation on theme: "A Multifaceted Approach to Understanding the Botnet Phenomenon Authors : Moheeb Abu Rajab, Jay Zarfoss, Fabian Monrose, Andreas Terzis Computer Science."— Presentation transcript:

1 A Multifaceted Approach to Understanding the Botnet Phenomenon Authors : Moheeb Abu Rajab, Jay Zarfoss, Fabian Monrose, Andreas Terzis Computer Science Department Johns Hopkins University Presented at : Internet Measurement Conference, IMC'06, Brazil, October 2006 Presented By : Ramanarayanan Ramani

2 Outline Working of Botnets Measuring Botnets Inference from Measurement Strengths Weaknesses Suggestions

3 Botnets A botnet is a network of infected end-hosts (bots) under the command of a botmaster. 3 Different Protocols Used:  IRC  HTTP  P2P

4 Botnets (contd.) 3 Steps of Authentication Bot to IRC Server IRC Server to Bot Botmaster to Bot (*) : Optional Step

5 Measuring Botnets Three Distinct Phases  Malware Collection Collect as many bot binaries as possible  Binary analysis via gray-box testing Extract the features of suspicious binaries  Longitudinal tracking Track how bots spread and its reach

6 Measuring Botnets Darknet : Denotes an allocated but unused portion of the IP address space.

7 Malware Collection Nepenthes is a low interaction honeypot Nepenthes mimics the replies generated by vulnerable services in order to collect the first stage exploit Modules in nepenthes  Resolve DNS asynchronous  Emulate vulnerabilities  Download files – Done here by the Download Station  Submit the downloaded files  Trigger events  Shellcode handler

8 Malware Collection Honeynets also used along with nepenthes Catches exploits missed by nepenthes Unpatched Windows XP are run which is base copy Infected honeypot compared with base to identify Botnet binary

9 Gateway Routing to different components Firewall : Prevent outbound attacks & self infection by honeypots Detect & Analyze outgoing traffic for infections in honeypot Only 1 infection in a honeypot Several other functions

10 Binary Analysis Two logically distinct phases  Derive a network fingerprint of the binary  Derive IRC-specific features of the binary IRC Server learns Botnet “dialect” - Template Learn how to correctly mimic bot’s behavior - Subject bot to a barrage of commands

11 IRC Tracker Use template to mimic bot Connect to real IRC server Communicate with botmaster using bot “dialect” Drones modified and used to act as IRC Client by the tracker to Cover lot of IP addresss

12 DNS Tracker Bots issue DNS queries to resolve the IP addresses of their IRC servers Tracker uses DNS requests Has 800,000 entries after reduction Maintain hits to a server

13 Measuring Botnets Darknet : Denotes an allocated but unused portion of the IP address space.

14 Botnet Traffic Share

15

16 DNS Tracker Results

17 Bot Scan Method 2 Types  Immediately start scanning the IP space looking for new victims after infection : 34 / 192  Scan when issued some command by botmaster

18 Botnet Growth - DNS

19 Botnet Growth – IRC Tracker

20 Botnet Online Population

21

22 Botnet Software Taxonomy Services Launched in Victim Machine OS of Exploited Host

23 Botmaster Analysis

24 Strengths All aspects of a botnet analyzed No prior analysis of bots Ability to model various types of bots

25 Weakness Only Microsoft Windows systems analyzed Focus on IRC-based bots as they are predominant

26 Suggestions Use the analysis to model new bots Use the analysis to model protection methods

27 Questions


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