Performance Attacks on Intrusion Detection Systems

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    Performance Attacks on Intrusion Detection Systems - Presentation Transcript

    1. Performance Attacks on Intrusion Detection Systems Davide Eynard eynard@elet.polimi.it Dipartimento di Elettronica e Informazione Politecnico di Milano 2007/12/06 Performance Attacks on Intrusion Detection Systems
    2. Intro  Intrusion Detection Systems  Open problems and vulnerabilities  The queueing model  Algorithmic complexity attacks  Tests and evaluations  Conclusions p. 2 2007/12/06 Performance Attacks on IDS
    3. Intrusion Detection Systems  As the Internet grows, the number of • vulnerabilities • attacks • attackers!  increases: what kind of protections can we use for our systems?  IDS are used to detect unauthorized access attempts to computers or local networks  They work as alarms in apartments • they do not prevent attackers to break in the system... • but they allow administrators to know when an attack is taking place p. 3 2007/12/06 Performance Attacks on IDS
    4. Intrusion Detection Systems p. 4 2007/12/06 Performance Attacks on IDS
    5. IDS Performance  Measures: • coverage • probability of false alarms • probability of detection • resistance to attacks directed at the IDS • ability to handle high bandwidth traffic • ability to correlate events • ability to detect new attacks • ability to identify an attack • ...  Traffic generation: • background • attacks p. 5 2007/12/06 Performance Attacks on IDS
    6. IDS Vulnerabilities  Insertion • an IDS accepts packets that an end system rejects  Evasion • an IDS rejects packets accepted by the end system  Denial of Service • compromises the availability of the IDS, either consuming its resources or targeting at bugs in software • fail-closed vs fail-open systems p. 6 2007/12/06 Performance Attacks on IDS
    7. Model K=L+1 L λ λa X ... λr S = 1/μ Queue size: K Service time: S Incoming packet rate: λ pkt/sec Throughput: X λa accepted λr rejected p. 7 2007/12/06 Performance Attacks on IDS
    8. Model Markov Chain: p. 8 2007/12/06 Performance Attacks on IDS
    9. Model behavior Drop probability as a function of λ/μ, plotted with four different queue sizes p. 9 2007/12/06 Performance Attacks on IDS
    10. Model behavior P(K) Packet frequency Service time p. 10 2007/12/06 Performance Attacks on IDS
    11. Model behavior Drop probability as a function of S, seen for different values of λ p. 11 2007/12/06 Performance Attacks on IDS
    12. What if I have a 56Kbps?  Gigabit Ethernet: ~ 1.6Mpps (frame size: 78B)  100MB Ethernet: ~ 148Kpps (frame size: 84B)  10MB Ethernet: ~ 14.8Kpps  2MB ADSL: ~ 3Kpps  56Kbps modem: ~ 80 pps p. 12 2007/12/06 Performance Attacks on IDS
    13. Algorithmic complexity attacks  S. Crosby, D. Wallach: “Denial of Service via Algorithmic Complexity Attacks”, 2003  They exploit algorithmic deficiencies in many common applications' data structures • ie. both hash tables and binary trees can degenerate to linked list with carefully chosen input  One particular case: backtracking algorithmic complexity attacks p. 13 2007/12/06 Performance Attacks on IDS
    14. Backtracking attacks  A vulnerable rule: p. 14 2007/12/06 Performance Attacks on IDS
    15. Backtracking attacks  every triple (x, y, z) contains: • x: the match name • y: where the parsing started • z: where the next parsing will start p. 15 2007/12/06 Performance Attacks on IDS
    16. Backtracking attacks  IDS behavior (left: normal, right: under attack) p. 16 2007/12/06 Performance Attacks on IDS
    17. Tests and evaluations  Backtracking attacks seem a good way to create high service times  The plan: • install Snort on a test machine • generate background traffic on the network • attack Snort with backtracking attacks • see/measure its behavior  Test machine • 2.4GHz Athlon, 1GB RAM, Linux kernel 2.6.22.14 • Snort 2.4.3 and 2.8.0  Attacker machine • 1.86GHz Pentium M, 1GB RAM, Linux kernel 2.6.22.14 • blabla tool to replay the DARPA 1999 dataset • a perl script to generate attack packets p. 17 2007/12/06 Performance Attacks on IDS
    18. Test attack alert tcp $EXTERNAL_NET any ­> $SMTP_SERVERS 25 ( msg:\"SMTP spoofed MIME­Type auto­execution attempt\";  flow:to_server,established;  content:\"Content­Type|3A|\"; nocase;content:\"audio/\"; nocase;  pcre:\"/Content­Type\\x3A\\s+audio\\/(x­wav|mpeg|x­midi)/i\";  content:\"filename=\"; distance:0; nocase;  pcre:\"/filename=[\\x22\\x27]?.{1,221}\\.(vbs|exe|scr|pif|bat)/i\";  reference:bugtraq,2524; reference:cve,2001­0154;  classtype:attempted­admin; sid:3682; rev:2;) p. 18 2007/12/06 Performance Attacks on IDS
    19. Test attack alert tcp $EXTERNAL_NET any ­> $SMTP_SERVERS 25 ( msg:\"SMTP spoofed MIME­Type auto­execution attempt\";  flow:to_server,established;  content:\"Content­Type|3A|\"; nocase;content:\"audio/\"; nocase;  pcre:\"/Content­Type\\x3A\\s+audio\\/(x­wav|mpeg|x­midi)/i\";  content:\"filename=\"; distance:0; nocase;  pcre:\"/filename=[\\x22\\x27]?.{1,221}\\.(vbs|exe|scr|pif|bat)/i\";  reference:bugtraq,2524; reference:cve,2001­0154;  classtype:attempted­admin; sid:3682; rev:2;) Match example:  Content­Type: audio/x­wav;                filename=”virus.scr” p. 19 2007/12/06 Performance Attacks on IDS
    20. Test attack alert tcp $EXTERNAL_NET any ­> $SMTP_SERVERS 25 ( msg:\"SMTP spoofed MIME­Type auto­execution attempt\";  flow:to_server,established;  content:\"Content­Type|3A|\"; nocase;content:\"audio/\"; nocase;  pcre:\"/Content­Type\\x3A\\s+audio\\/(x­wav|mpeg|x­midi)/i\";  content:\"filename=\"; distance:0; nocase;  pcre:\"/filename=[\\x22\\x27]?.{1,221}\\.(vbs|exe|scr|pif|bat)/i\";  reference:bugtraq,2524; reference:cve,2001­0154;  classtype:attempted­admin; sid:3682; rev:2;) Match example:  Content­Type: audio/x­wav;                filename=”virus.scr” Attack example: ... Content­Type: audio/x­wav; filename=filename=filename=filename= Content­Type: audio/x­wav; filename=filename=filename=filename= ... p. 20 2007/12/06 Performance Attacks on IDS
    21. Results  Snort 2.8.0 is not affected by the attacks  Snort 2.4.3 experiences serious slowdowns • normal service time: ~100μsec • normal attack: 500~1000μsec • backtracking attack: 1500000μsec  With such service time, just few packets are able to make the queue fill up and the IDS drop packets => other attacks are undetected!  Results comparable with paper: real behavior seems worse than in the model p. 21 2007/12/06 Performance Attacks on IDS
    22. Conclusions  The incoming packet rate and the service time are interchangeable  The model is useful not just to plan attacks • it explains why backtracking attacks work • it allows to study an IDS as a black box  Limits • test suffers the classical problems of IDS evaluations • bursts not taken into account  Possible future work • take bursts into account • multiclass model p. 22 2007/12/06 Performance Attacks on IDS
    23. That's All, Folks Thank you! Questions are welcome p. 23 2007/12/06 Performance Attacks on IDS

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