1 / 44

New Directions in Network Intrusion Detection

New Directions in Network Intrusion Detection. Presented to CS694 October 16, 1998 Jeremy Elson. does security matter?. Would you care if someone could:. Crash your computer every 5 minutes? Subtly change your thesis? Change your bank statement? Sink a ship?

broderick
Download Presentation

New Directions in Network Intrusion Detection

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. New Directionsin NetworkIntrusionDetection Presented to CS694 October 16, 1998 Jeremy Elson

  2. does security matter? Would you care if someone could: • Crash your computer every 5 minutes? • Subtly change your thesis? • Change your bank statement? • Sink a ship? • (Think it’s unlikely? It happened; see NY Times, vol. CXLIII, page E7 - Oct. 24, 1993)

  3. when will it matter? Some systems and/or protocols are designed with security in mind from the beginning -- maybe even as their primary design goal. But for most? The story’s the same… • Protocol design? (Nah, that’s an application problem) • Application design? (We plan to add that in the future...) • Application deployment? (Let’s get it running first) • System administration? (I’m putting out fires every day!)

  4. Type of site # of hosts Total % % Yellow% Red scanned vulnerable banks 660 68.33 32.7335.61 credit unions 274 51.09 30.6620.44 US federal sites 47 61.70 23.4038.30 newspapers 312 69.55 30.7738.78 sex 451 66.08 40.5825.50 Totals 1734 64.94 33.8531.08 houston, we havea problem... Yellow = Probably Hackable; Red = Trivially Hackable Source: Independent Security Survey By Dan Farmer, Dec 1996 http://www.trouble.org/survey

  5. system vulnerabilities • Almost all vulnerabilities come from bugs in the implementation of, or misconfigurations of, the OS and/or apps • Rarely, a problem with a protocol itself • Vulnerabilities can lead to: • Unauthorized access: attacker gains control of the victim’s machine (attacker can log in, read files, and/or make changes to the system) • Denial of Service against host (attacker can crash the computer, disable services, etc.) • Denial of Service against network (attack can disrupt routing, flood the network, etc.)

  6. security incidents reported to CERT Source: CERT/CC -- http://www.cert.org/stats/cert_stats.html

  7. Mitnick Simpson who is the enemy? • The Troubled Genius • Has a deep understanding of systems • Capable of finding obscure vulnerabilities in OS’s, apps, and protocols, and exploiting them • Extremely skilled at evading countermeasures • Can dynamically adapt to new environments • The Idiot • Little or no true understanding of systems • Blindly downloads & runs code written by T.G. • Can usually be stopped by calling his mother Who do you think causes more damage?

  8. d’oh! • The idiots collectively cause more damage because there are a vast number of them • Every security incident I analyzed while I was at NIH was the work of an idiot • Every time smart hackers find a new security hole, they make it public -- they have a publish or perish “ethic” • Each time, hordes of idiots pounce on it and break into every system they can find

  9. publish or perishor, good help is not hard to find

  10. the never-ending game 1. New bugs are found; exploits are published 2. Hordes of idiots cause damage using those exploits 3. Vendors are pressured to come out with fixes 4. Users install the fixes (sometimes? rarely?) 5. Go to step 1. The big questions are: 1. How can we protect a large site? (The site is only as strong as its most poorly administered machine.) 2. How can we pro-actively protect against attacks that we have never seen before, to avoid Step 2 damage?

  11. the rest of my talk • Bro, Vern Paxon’s network security monitor, attempts to get a handle on site-wide security monitoring in a way that firewalls can’t -- more on that soon • Computer Immune Systems, from Stephanie Forrest at UNM, attempts to solve Problem 2 -- but only on a host, not for an entire network. • My idea: how to combine the best of both

  12. securing your systemthe quick & easy way “ It’s easy to run a secure computer system. You just have to disconnect all dial-up connections and permit only direct-wired terminals, put the machine and its terminals in a shielded room, and post a guard at the door. ” F.T. Grampp and R.H. Morris (Great! Let’s go to the router room with some bolt cutters.)

  13. firewalls(not as good as bolt cutters, but…) • Routers: easy to say “allow everything but…” • Firewalls: easy to say “allow nothing but…” • This helps because we turn off access to everything, then evaluate which services are mission-critical and have well-understood risks • Note: in my opinion the only difference between a router and a firewall is the design philosophy; do we prioritize security, or connectivity/performance? (configurability, logging)

  14. typical firewall setup evil Internet DMZ internal network Diagram courtesy of CheckPoint Software Tech, www.checkpoint.com

  15. the firewall setup • Firewall ensures that the internal network and the Internet can both talk to the DMZ, but usually not to each other • The DMZ relays services at the application level, e.g. mail forwarding, web proxying • The DMZ machines and firewall are centrally administered by people focused on security full-time (installing patches, etc.); it’s easier to secure 20 machines than 20,000 • Now the internal network is “safe” (but not from internal attacks, modems, etc.)

  16. Dear Professor _____________ , Our firewall has detected your attempt to use the network protocol ________. This protocol is not supported under the USC Security Policy. Please cease these activities at once. Any further infractions will result in your disconnection from our network. Cordially, UCS ESTRIN PIM firewall politics • In a corporate environment, firewalls are great. The network user is an employee of the network service provider; it’s in the provider’s power to say “Thou Shalt Not Use Any Internet Services Except For These...” • How well do you think that would work here?

  17. big brother is watching • “Bro” passively monitors the network at some key location (say, the border router) • Reconstructs flows and searches for known “attack signatures” -- a manually created database, based on known network attacks • Provides real-time notification of security personnel when it sees something suspicious • Future versions may actively terminate connections by sending forged TCP RST ftp://ftp.ee.lbl.gov/papers/bro-usenix98-revised.ps.Z

  18. thoughts on bro • It provides a nice site-wide view of security • It’s not disruptive to users • It’s centrally administered • Unlike a firewall, which stops badness before it starts, bro’s alarm may come too late • It can’t flag attacks that are not in its database of known attack signatures • It can not reliably determine what an end-station is seeing, for a variety of reasons

  19. subverting bro(we’ll start with the easy ones) • Let’s say we’re trying to scan for the string “su root”. • What if I type “su me^H^Hroot”? • What if I type “su<telnet option> root”? • What if I type “alias blammo su”, then type “blammo root”?

  20. TCP: HDR USER HDR root HDR HDR US HDR ER HDR HDR ro IP: HDR ot reconstructing flows • Let’s say you want to search for the text “USER root”. Is it enough to just search the data portion of TCP segments you see? USER root (Uh oh… we have to reassemble frags and resequence segs)

  21. HDR HDR US HDR ER HDR HDR ro HDR ot fun with fragments Imagine an attacker sends: 1. 2. 3. 1,000,000 unrelated fragments 4. 5. Think of the entire campus as being a massively parallel computer. That supercomputer is solving the flow-reconstruction problem. Now we’re asking a single host to try to solve that same problem.

  22. HDR HDR US HDR ER HDR HDR HDR HDR ro fo HDR ot more fragment fun Imagine an attacker sends: Seq. # 1. Time 2. 3a. 3b. 4. Should we consider 3a part of the data stream “USER root”? Or is 3b part of the data stream? “USER foot”! -- If the OS makes a different decision than the monitor: Bad. -- Even worse: Different OS’s have different protocol interpretations, so it’s impossible for Bro to agree with all of them

  23. trickery • Non-standard parts of standards • IP fragment overlap behavior • TCP sequence number overlap behavior • Invalid combinations of TCP options • Other ways to force a disparity between the monitor and the end-station • TTL • Checksum • Overflowing monitor buffers See http://www.secnet.com/papers/ids-html/ for detailed examples

  24. is bro useless? • Of course not. • Remember, most of the problems are caused by idiots; they don’t know how to subvert bro and the techniques can’t be pre-packaged easily. • It doesn’t cost us anything. • Just because the monitor can be subverted doesn’t mean we can’t use it. Using it doesn’t mean we are making a tradeoff, so why not? • There is no silver bullet. • Don’t expect anysystem to single-handedly “solve” the security problem. Take what you can get.

  25. the reverse approach • Systems like Bro define “bad” -- anything they don’t recognize, therefore, is assumed to be good. • Problem: Your “bad” list is always out of date • Other systems attempt to define “good” -- anything they don’t recognize is “bad” • Now, new badness is automatically caught! • Problem: How do you define “good”?

  26. the immune system • Stephanie Forrest et al were inspired by biological immune systems. • A biological immune system doesn’t have a catalog of all viruses that exist in the world • They have a strong sense of “self”, allowing them to identify and attack non-self entities • Is the same thing possible on the computer? • Motivation: UNIX processes; there is a well-known and easy technique for getting almost any buggy program to execute arbitrary code by just sending it carefully! http://www.cs.unm.edu/~steveah/research.html

  27. getting to know yourself 1. Find a metric that characterizes the system. 2. Build up a database of normal values for that metric when the system is working as it should. 3. Continually monitor the metric; set off an alarm if it deviates from the database. 4. Test the metric for false positives/negatives.

  28. applying the method • First target application: sendmail (infamous for many security holes) • First metric: system call traces • Normal database to be built up by recording sendmail’s behavior in a wide variety of everyday tasks (many types of messages)

  29. call call+1 call+2 call+3 open read, mmap mmap system call traces Sample call sequence: open, read, mmap, mmap, open, getrlimit, mmap, close read mmap mmap open mmap mmap, open, getrlimit, open, getrlimit mmap close getrlimit mmap close close

  30. database in training

  31. the normal database • Using a window size of 6, running sendmail through its paces produced a database of only 1500 entries and was stable! • This is only 5x10-5% of all possible entries • The small size of the database is critical: • Big database = variability in “normal” = difficulty in detecting anomalies • Big database = no realtime monitoring

  32. results Anomaly % Num sunsendmailcp 4.1 95 syslog: remote 1 4.2 470 remote 2 1.5 137 local 1 4.2 398 local 2 3.4 309 decode 0.3 24 lprcp 1.4 12 sm565a 0.4 36 sm5x 1.7 157 forward loop 1.8 58 (sm565a and sm5x were unsuccessful attacks; forward loop was nonmalicious anomalous behavior; others were successful breakins.)

  33. discussion • Programs seem to exhibit remarkable amounts of find-grained consistency when operating normally; this can be used to detect anomalies. • Since we now know what’s “good”, we can report badness that we have never seen before • Will not help to do things like determine that a user has stolen another user’s password • A solution for one host, not an entire site • Current system runs off-line (on-line planned)

  34. related work • Various expert systems for analyzing logs • Systems remain vigilant even given megs of log data every day, where humans throw away data • NIDES (ftp://ftp.csl.sri.com/nides) • Defines a set of events (e.g. directory modification, password file access, etc.) • Complex statistical algos for reporting anomalies while still adaptively learning new user behavior • Keystroke Dynamics - knows how users type

  35. bringing it all together • Bro is powerful in that it can monitor an entire site, but weak in that it can’t predict what future attack profiles will look like • Forrest’s work, and other systems mentioned, all suggest you can do well by adaptively learning “normal” and reporting deviations • Forrest’s work shows that surprisingly high-level characteristics of a system can become evident by looking at events on an extremely low level, fine grain, and small time scale

  36. my idea • Based on motivations mentioned in the previous slide, I propose a new type of network intrusion detector: • Monitors network traffic at the packet level • Creates per-flow packet traces similar to system call traces (e.g. SYN -> SYNACK -> ACK; ACK -> DATA -> ACK) • Uses various other metrics (e.g. % of total traffic that is SYN, ACK, RST; ratio of ACKs to data; packet size distribution; distribution of source and destination port numbers) • Adaptively learns what is “normal” for both traces and other metrics; reports abnormalities

  37. more on my idea • I think it would capture a wide variety of hard-to-see protocol-bug-based attacks • SYN Flood, Land, Teardrop, Smurf, plus (most importantly) whatever hasn’t been invented yet • Would probably see attacks on services (e.g. port scanning on a host, service scanning across many hosts -- DNS bug!) • Would even see deviations from normal behavior on regularly used services (e.g., catching a PHF bug or keystrokes to httpd)

  38. problems with my idea • Still not a useful way for finding things like stolen passwords • The variations in protocol implementations on the Net may mean that normal behavior will not exhibit self-similarity • Might miss things that could be more reliably detected by a pattern-matcher -- but why not run Bro and SIS at the same time (contrived acronym: Segment Initiated Security) • Probably a significant effort to build and characterize the system and I don’t have the time to do it :-)

  39. that’s all, folks! Thank You!

  40. backup slidesforanswering questions

  41. it hasn’t leveled off • I think the growth has remained exponential, although CERT’s reports flattened in 1995 • People nowadays don’t know what CERT is • People don’t report incidents • It’s time-consuming • It gets you in trouble with your boss • It’s embarrassing • It’s proprietary information

  42. the smurf attack victim Typically: evil has slow link (modem) victim has fast link (T1) big has very fast link (T3+) evil big ICMP_ECHO_RPL Source: big Dest: victim ICMP_ECHO_REQ Source: victim Dest: big (broadcast addr)

  43. func 2’s address func 1’s address buf c, d a, b func_3() { char buf[100]; read_user_input(buf); } func_2() { int c, d; func_3(); } func_1() { int a, b; func_2(); } buffer overflowson the stack

  44. func 2’s address buf’s address func 1’s address buf c, d a, b evil_assembly_code() func_3() { char buf[100]; read_user_input(buf); } func_2() { int c, d; func_3(); } func_1() { int a, b; func_2(); } buffer overflowson the stack Attacker is supplying input to buf… so buf gets a very carefully constructed string containing assembly code, and overwriting func 2’s address with buf’s address. When func3 returns, it will branch to buf instead of func2.

More Related