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How to Own the Internet in Your Spare Time. Giannis Kapantaidakis University of Crete CS558. (Stuart Staniford Vern Paxson Nicholas Weaver ). What could you do if you 0wn’d a million hosts?. Distributed DOS attacks Access sensitive information Confuse-Corrupt the information
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How to Own the Internet in Your Spare Time Giannis Kapantaidakis University of Crete CS558 (Stuart Staniford Vern Paxson Nicholas Weaver )
What could you do if you 0wn’d a million hosts? • Distributed DOS attacks • Access sensitive information • Confuse-Corrupt the information Makes it valuable tool in Cyber warfare
How to 0wn a million hosts? Worms • Programs that self-propagate across the Internet exploiting security flaws in widely-used services (As opposed to viruses, which require user action to spread.)
Code Red I • Initial version released July 13, 2001. • Exploited known bug in Microsoft IIS Web servers. • But: failure to seed random number generator.All worms attempted to compromise the same sequence of hosts. • Linear spread, didn’t get very far
Code Red I v2 • Released July 19, 2001. • Same codebase but: • random number generator correctly seeded. • DDoS payload targeting IP address of www.whitehouse.gov • That night, Code Red dies (except for hosts with inaccurate clocks!) • It just takes one of these to restart the worm come the first of the next month!
Random Constant Spread Model • N: Total number of Vulnerable servers in Internet • K: Initial Compromise Rate: Rate at which a infected host is able to infect new hosts at the start of the incident • a: Proportion of machines already compromised • T: Time at which the incident happens • Equation: Nda = (Na)K(1-a)dt • Solution: a = e (K(t-T)) / 1 + e (K(t-T)) • Good enough model (Works for Code Red I)
K=1.8 T=11.9 • Max probe rate:510.000 scans per hour • Came close to saturation before turning off
Reawake on Aug 1st , K=0.7 • Number of vulnerable systems was less than 40% as many as the first time • Code Red more or less followed the model.
Code Red II • Released August 4, 2001. • Comment in code: “Code Red II.”But in fact completely different code base. • Payload: a root backdoor allowing unrestricted remote access • Bug: crashes NT, only works right on Windows 2000. • Used localized scanning strategy
Localized Scanning • Attempt to infect addresses close to it • With probability 3/8 it chooses a random IP from with the class B address space of the infected machine • With probability ½ from class A • And with probability 1/8 from the whole internet • Localized spreading works - hosts around it are often similar,topologically faster,spreads fast in internal network once it gets through the firewall
Nimda • Released September 18, 2001. • Multi- mode spreading: • attack IIS servers via infected clients. • email itself to address book as a virus • copy itself across open network shares • modifying Web pages on infected servers in order to infect clients • scanning for Code Red II and sadmind backdoors (!)
Average - 100 connections per second • About 3X number of Code Red probes • Full functionality still not known!
Since Nimda spreads by multiple vectors,the counts shown for it may be an underestimate
Ways of reducing time • Hit List scanning • Permutation scanning • Topological Scanning • Internet scale hit-lists
Hit List scanning Idea: reduce slow startup phase. • The author of the worm collects the list of around 10,000 -50,000 potentially vulnerable machines ideally the ones with very good network connection, before releasing the worm • The worm when released initially attacks these machines .So the initial infection is higher.When it infects a machine it divides the hit-list in half
Ways to get Hit list • Distributed Scanning - use zombies • Stealthy Scan- spread it over several months • DNS searches - e. g., www. domain. com • Spiders - ask the search engines • Just Listening-P2P, or exploit existing worms
Permutation Scanning Idea: reduce redundant scanning. • Permutation allows a worm to detect when a host is already infected. • Worms share a common permutation of the IP address space. • An infected machine starts scanning just after their position in the permutation. When the worm sees an infected machine is chooses a new random start point.
Warhol Worm • Based on: • Hit List & • Permutation Scanning • Simulation Environment • Results of Simulation
So now we already have methods to attack most vulnerable targets in <15 minutes.
Topological Scanning • Alternative to hit-list scanning • Use addresses available on victim’s machines. • Use this as a start point before using Permutation Scanning. • Peer to peer systems are highly vulnerable to this kind of scanning
Flash Worms:The Real Danger • Idea: use an Internet- sized hit list. (entire address space scan roughly 2hr) • Initial copy of the worm has the entire hit list. • Each generation, infects nfrom the list, gives each 1/n. (Or, point them to a well- connected servers that serves upportions of the list.) • If n=10 requires 7 generations to infect 10^7 hosts (less than 30 seconds! )
Still need better worms • All those worms use singular communication patterns • This forms the basis for automatic detection • How can we remove that weakness from worms?
Contagion Worms • Suppose you have two exploits: • Es : exploit in web server • Ec: exploit in client • You infect a server (or client) with Es (Ec) • Then you…wait. (Perhaps you bait, e. g., host porn.) • When vulnerable client arrives, infect it. • You send over both Es and Ec • As client happens to visit other vulnerable servers infects • Clearly there are no unusual communication patterns to be observed (other than slightly larger- than- usual transfers)
Contagion Worms • They become Dangerous with P2P systems because: • Likely only need a single exploit, not a pair. • Often, peers running identical software. • Often used to transfer large files. • Often give access to user’s desktop rather than server. • and can be Very Large
Contagion Worms • KazaA: 9 million distinct IP connections with university hosts (5800) in a single month • If you 0wn’d a single university, then in November, 2001you could have 0wn’d 9 million additional hosts. • How fast? Faster than 1 month.
Updating and control • Distributed control • Each worm has a list of other copies • Ability to create encrypted communication channels to spread info • Commands cryptographically signed by author. • Each worm copy, confirms signature,spreads to other copies and then executes the command • Programmatic Updates • Operating systems allow dynamic code loading • New encrypted attack modules from Worm author
Centre for Disease Control • Roles it is expected to perform • Identifying outbreaks • Rapidly Analyzing pathogens • Fighting Infections • Anticipating new vectors • Resisting future threats
How open? • Have a open website (accessible to all)? • Drawbacks: • Attacker targets the site • How correct an information placed on site is • Attacker also gains understanding • Some sources may not be willing to make their information public • How International.