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CERT ® Coordination Center Software Engineering Institute Carnegie Mellon University Pittsburgh, PA 15213-3890 The CERT Coordination Center is part of.

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Presentation on theme: "CERT ® Coordination Center Software Engineering Institute Carnegie Mellon University Pittsburgh, PA 15213-3890 The CERT Coordination Center is part of."— Presentation transcript:

1 CERT ® Coordination Center Software Engineering Institute Carnegie Mellon University Pittsburgh, PA The CERT Coordination Center is part of the Software Engineering Institute. The Software Engineering Institute is sponsored by the U.S. Department of Defense. © 2001 by Carnegie Mellon University some images copyright 1 Trends in Denial of Service Attack Technology Kevin J. Houle NANOG23 – October 2001

2 © 2001 by Carnegie Mellon University 2 Background: Pre-1999 DoS Tools: -Single-source, single target tools -IP source address spoofing -Packet amplification (e.g., smurf) Deployment: -Widespread scanning and exploitation via scripted tools -Hand-installed tools and toolkits on compromised hosts (unix) Use: -Hand executed on source host

3 © 2001 by Carnegie Mellon University 3 Background: 1999 DoS Tools: -Multiple-source, single target tools -Distributed attack networks (handler/agent) -DDoS attacks Deployment: -Hand-selected, hard-coded handlers -Scripted agent installation (unix) Use: -Custom, obfuscated control channels ›intruder  handlers ›handlers  agents

4 © 2001 by Carnegie Mellon University 4 Background: : Infamous DDoS attacks : DNS amplification attacks, mstream DDoS tool : VBS/Loveletter, t0rnkit : Hybris : Trinity IRC-based DDoS tool (unix) :Multiple IRC-based DDoS tools (Windows)

5 © 2001 by Carnegie Mellon University 5 Background: :Ramen worm :VBS/OnTheFly (Anna Kournikova), erkms worm, 1i0n worm :Adore/Red worm, carko DDoS tool :cheese worm, w0rmkit worm, sadmind/IIS worm :Maniac worm, Code Red worm :W32/Sircam, Leaves, Code Red II, various telnetd worms, various IRC-based DDoS tools (knight, kaiten) : Nimda worm

6 © 2001 by Carnegie Mellon University 6 Trends – Deployment Greater degree of automation Self-propagating worms -Central source propagation -Back channel propagation -Autonomous propagation

7 © 2001 by Carnegie Mellon University 7 Central Source Propagation central-source attackervictims next-victims 1 - exploit 2 – copy code 3 - repeat Example: 1i0n worm

8 © 2001 by Carnegie Mellon University 8 Back Channel Propagation attackervictims next-victims 1 - exploit 2 – copy code 3 - repeat Example: Ramen worm

9 © 2001 by Carnegie Mellon University 9 Autonomous Propagation attackervictims next-victims 1 – exploit & copy code2 - repeat Examples: Code Red, Code Red II

10 © 2001 by Carnegie Mellon University 10 Trends – Deployment (cont.) Degree of Blind Targeting Selective Targeting AutomationVery highLow  high Vulnerability- specificity Very highLow  high Other criteriaLowVery high Targeting Systems: Blind vs. Selective Targeting

11 © 2001 by Carnegie Mellon University 11 Blind Targeting Social Engineering -W32/Sircam Specific vulnerabilities -sadmind/IIS worm unix/Microsoft IIS -Code Red, Code Red II Microsoft IIS -Nimda Windows/IIS -Various telnetd worms unix Activity tends to follow vulnerability lifecycles

12 © 2001 by Carnegie Mellon University 12 Selective Targeting Windows end-users increasingly targeted -less technically sophisticated -less protected -difficult to contact en mass -slow response to security alerts/events -well-known netblocks -widespread broadband connectivity -increase in home networking -exploit technology base is maturing CERT® Tech Tip - Home Network Security

13 © 2001 by Carnegie Mellon University 13 Selective Targeting (3) Routers increasingly targeted -source for recon/scanning -proxy to IRC networks -source for packet flooding attacks -Compromise via weak/default passwords -Routers sometimes reconfigured ›public guides are available -Increased threat of routing protocol attacks ›discussions at DefCon and Black Hat Briefings

14 © 2001 by Carnegie Mellon University 14 Trends: Use Control Infrastructure – The classic DDoS model intruder handler agent victim

15 © 2001 by Carnegie Mellon University 15 Control Infrastructure Increased use of IRC networks and protocols -IRC server replaces the handler ›common, ‘legit’ service ports (e.g., 6667/tcp) ›commands are buried in ‘legit’ traffic ›no agent listeners; outbound connections only -More ‘survivable’ infrastructure ›reduction in address lists maintained ›disposable, easy to obtain agents ›makes use of public IRC networks ›private servers are also used

16 © 2001 by Carnegie Mellon University 16 Control Infrastructure (2) Increased use of IRC networks and protocols (cont.) -Agent redirection / update is easier ›everyone change to a new channel ›everyone change to a new IRC server ›everyone download this updated module -“floating” domains used to direct agents ›bogus WHOIS data, stolen credit cards ›‘A’ record modification redirects hard-wired agents

17 © 2001 by Carnegie Mellon University 17 Trends: Use Less emphasis on forged packet characteristics -size and distribution of DDoS makes response difficult ›overwhelming number of sources in DDoS attack ›sources often cross multiple AS boundaries ›high bandwidth consumption is easy; no need for fancy packets -increase in attacks using legitimate traffic ›mixes with other traffic ›harder to filter/limit

18 © 2001 by Carnegie Mellon University 18 Trends: Impact Increase in collateral damage (e.g., blast radius) -backup systems impacted by sharp increases in log volumes -financial impact at sites with measured usage circuits -multiple sites impacted in shared data centers -arp storms impacting locally infected networks Highly automated deployments are themselves causing denial of service conditions

19 © 2001 by Carnegie Mellon University 19 What We Are Not Seeing Changes in fundamental conditions that enable denial of service attacks Consumption of limited resources -Processing cycles -Memory resources -Network bandwidth Interdependency of security on the Internet -The exposure to DoS attack of SiteA depends on the security of SiteB -There are huge numbers of SiteB’s

20 © 2001 by Carnegie Mellon University 20 What We Are Not Seeing (2) Advances in DoS attack payload Seeing the same common packet stream types Known attacks work, there is little incentive to improve -TCP (SYN|ACK|FIN|RST) flood -UDP flood -ICMP echo request/reply flood -Amplification attacks -Source IP address spoofing

21 © 2001 by Carnegie Mellon University 21 What We Are Not Seeing (3) Reductions in launch-point availability Vendors are still producing insecure products Administrators/users are still deploying and operating systems insecurely Vulnerability life cycle is still lengthy (2-3 years)

22 © 2001 by Carnegie Mellon University 22 Credits Paper:Trends in Denial of Service Attack Technology Authors: Kevin Houle Neil Long Rob Thomas George Weaver

23 © 2001 by Carnegie Mellon University 23 CERT Coordination Center Software Engineering Institute Carnegie Mellon University 4500 Fifth Avenue Pittsburgh PA USA Hotline: CERT personnel answer 8:00 a.m. — 8:00 p.m. EST(GMT-5) / EDT(GMT-4), and are on call for emergencies during other hours. Fax: Web:http://www.cert.org/ CERT ® Contact Information


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