Transcript Motivation behind botnets

BOTNETS
Pius Ndebele
Yermek Sakiyev
How big is the problem?
•
•
•
“The Storm worm botnet has grown so massive and far-reaching that it easily
overpowers the world's top supercomputers…If you add up all 500 of the top
supercomputers, it blows them all away with just 2 million of its machines. It's very
frightening that criminals have access to that much computing power, but there's
not much we can do about it."
“An industrial control security researcher in Germany who has analyzed the
Stuxnet computer worm is speculating that it may have been created to sabotage
a nuclear plant in Iran.”
“Shockingly, botnets produce 95% of the world's spam and have infected around
100 million systems. It makes defending against botnets tough.”
What is a botnet?
Life cycle
•
•
•
•
Exploitation
Securing the botnet
Waiting for orders and getting the payload
Reporting the results
Types of botnets
• IRC
• HTTP
• P2P
Fast flux networks
• Innovative technique built in DNS
• Use for load balancing
• Abused by criminals in a way that they can
register thousands of IP addresses assigned to
one hostname and change TTL to very short
time
• This way it will be very hard to detect the real
IP addresses of C&C
What can a botnet do?
•
•
•
•
Recruit others
DDoS
Spam
Phishing and identity theft
Motivation behind botnets
First Generation
Distribution/Platform: IRC / Chat rooms and warez
DDoS: fun, demonstration elite skill [l33t sk1llz, p0wnag3], political activism.
Examples:
AOHell [1]




Punter (IM-bomber), which would send an Instant Message containing HTML code to another user that would sign them off.
Mail bomb - script which would rapidly send e-mails to a user's inbox until it was full.
Flooding script that would flood a chat room with ASCII art of an offensive nature.
An 'artificial intelligence bot', which did not really contain artificial intelligence, but had the ability to automatically respond
to a message in a chatroom upon identification of keywords. (For example, a 'profane language' autoresponse was built-in to
the program.)
------------------------------------[1] http://en.wikipedia.org/wiki/AOHell
Motivation behind botnets
Second Generation
Distribution/Platform: Worm/trojan with malicious payloads
Motive: Money
 highly organized criminal organization
 botnet avoiding Ukraine.[6] Why? Avoiding local law enforcement
 Conficker used latest encryption algorithm MD6 [submitted to NIST/FIPS]. Flaw discovered and fixed in 16 days [2]
Examples:
Storm
 harvesting Personal Identifiable Information, racking a suspected profit $2m in 1 year [3]
 DDoS researchers investigating it [4]
Koobface [5]
 targeting social networks. Which one?
--------------------------------------[2] http://www.confickerworkinggroup.org/wiki/pmwiki.php/ANY/Timeline
[3] http://news.bbc.co.uk/2/hi/technology/7719281.stm
[4] http://boingboing.net/2007/10/24/stormworm-botnet-las.html
[5] http://www.infowar-monitor.net/reports/iwm-koobface.pdf
[6] http://en.wikipedia.org/wiki/Conficker
Motivation behind botnets
Third Generation
Distribution/Platform: Industrial systems
Hardware and firmware based botnets
Potential political/economic ‘cyberwar’ or espionage
 Counterfeit networking gear (Cisco) sold to DoE, US AirForce, Federal Aviation Administration and several
universities [6]
 To counteract NSA has its own chip fabrication plant [7] and a hardware/software certification program [8]
Example:
Stuxnet [9]
 Targeting Programmable Logic Circuits (PLC) in control system sold to vendors in Finland and Iran.
 Specifically targeted were nuclear high-speed centrifugal motors.
--------------------------------------------------------[6] http://www.popularmechanics.com/technology/gadgets/news/4253628
[7] http://en.wikipedia.org/wiki/National_Security_Agency
[8] http://www.nsa.gov/business/programs/tapo.shtml
[9] http://www.symantec.com/connect/blogs/stuxnet-breakthrough
Detection & Prevention Techniques
Detection techniques
Reactive
 (N)(H) IDS
 external notifications (eg spamming friends, spam-blacklist)
Proactive
 honeypots/honeynets (understanding internal workings; Torpig, Conficker)
 Note: Honeypot used to lure researcher to a fake C&C to study their techniques and provide fake statistics (exploitation rates
for IE, PDF, Java vulnerabilities) [10]
Prevention techniques
Depth-in-defense [Protection in layers]
Anti-Malware [anti-virus, rootkit detectors]
 (N)(H) IPS
 proxies; network and application [layer 3-7]
 firewalls (egress filtering)
 policies (security, patching policy, computer use – ex. use of usb media)
 local legislature and international laws: used as severe punitive deterrents
New research points to using new approaches like economics (incentives), psychology (
---------------------------------[10] http://blog.tllod.com/2010/11/03/statistics-dont-lie-or-do-they/