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Detecting ICMP Rate-Limiting

Detecting ICMP Rate-Limiting. Les Cottrell Warren Matthews Mit Shah. Motivation 1. Smurf Attacks : IP spoofing and ICMP packets to an IP Broadcast group. Traffic to target multiplied by responses from each member

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Detecting ICMP Rate-Limiting

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  1. Detecting ICMP Rate-Limiting Les Cottrell Warren Matthews Mit Shah

  2. Motivation 1 • Smurf Attacks : IP spoofing and ICMP packets to an IP Broadcast group. Traffic to target multiplied by responses from each member • Example : Attacker on 768Kbps stream and a 100 member Broadcast group generate 77Mbps of traffic and swamp target! • Routers set to : “no ip directed-broadcast”

  3. Motivation 2 • Cisco introduces CAR (Committed Access Rate) in 7200 and 7500 series routers. Later includes support in IOS 12.0 • access-list 102 permit icmp any any echo • interface Serial3/0/0 rate-limit input access-group 102 256000 8000 8000 conform-action transmit exceed-option drop

  4. ICMP Blocking - No Response! • www.vincy.bg.ac.yu blocked 884 rounds of 10 ICMP packets each, out of 903 • islamabad-server2.comsats.net.pk blocked 554 out of 903 rounds • leonis.nus.edu.sg blocked all packets it was sent (All examples from data for Dec 1999) • Yet in reality, none of these servers was down!

  5. SYNACK developed in-house Establishes TCP connections and measures time taken by target to respond Cleans up connections Highly visible to system admins STING developed by Stefan Savage TCP can’t ack out-of-order packets Data-seeding and Hole-filling (reliable) Need to change one line of kernel code New tools to the rescue

  6. Results from Sting & Synack • Both tools based on TCP/IP, hence appear to router to be “normal” traffic • Results : • The Singapore node responds ONLY to 56+8 byte packets • Both the other nodes were alive-and-kicking with low loss rates!

  7. Utility of Sting as an aid • These are 5 sites that were responding to pings very infrequently, and neglecting entire sets of 10 pings more than 50% of the time • Sting showed that they were alive on port 80!

  8. Tail-Drop Behavior • Rate-limiting kicks in after the first few packets and hence later packets are more likely to be dropped • This node no longer displays tail-drop behavior!

  9. Frequency Analysis • Calculate the packet drops as a function of packet-numbers • Calculate the slope and identify extremes • Implemented by Warren as a metric • Some encouraging early results!

  10. Some Candidates :

  11. CAR (Committed Access Rate) • Tokens removed in proportion to size of packet • Maximum number of tokens in bucket = Normal Burst Size • Extended Burst mechanism to make drops more RED-like

  12. RED (Random Early Detection) • Tail-drop causes packet-loss across all TCP streams when traffic is too heavy • Causes all TCP-streams to sense congestion and start recovery • Small, bursty TCP streams also have to restart • Solution : drop packets randomly BEFORE congestion strikes!

  13. Extended Burst Mechanism in CAR • Stream allowed to borrow more tokens if extended-burst value > normal-burst • “ Compounded debt” computed as sum of a(j) where j denotes the jth packet that tries to borrow tokens since last packet drop and a(j) denotes actual debt value • Packet dropped if CD > extended-burst and CD set to 0

  14. Detecting CAR : the good news • A stream at constant rate R, above the configured-rate C, will exhaust tokens in bucket after B/(R-C) sec, at most • From this point on, borrowed packets at jth packet = j*(R-C) and beyond j=E/(R-C), actual debt > extended-burst and all packets will be dropped • Pattern is non-random!

  15. Detecting CAR : A trial • Analyzed the first-order differences in packet-numbers of dropped packets to see if there was a pattern hoping that site-specific CAR might have set packet-size > normal_burst_size + extended_burst_size • Not surprisingly, no results • False alarm : 10th packet being dropped but data was TOO clean!

  16. Detecting CAR : the bad news • It appears that most sites will impose a traffic-limit on TOTAL icmp traffic • Predicting when a packet drop occurs akin to predicting the rest of the traffic on that router at that moment - a known “hard” problem! • Solution : Aggressive pinging, your traffic-stream dominates! High signal-to-noise!!!

  17. Further study • Pinging with variable-sized packets (less than MTU) and detect whether packet-loss varies linearly with size • trivial to determine MTU? • How important are other effects like being more likely to be dropped from queue? • Set up a router that implements CAR, simulate icmp traffic, and study patterns

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