compromise indicator magic
DESCRIPTION
TRANSCRIPT
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Compromise Indicator Magic: Living with Compromise
Vladimir Kropotov, Vitaly Chetvertakov, Fyodor YarochkinPhDays 2014
Affilations: Academia Sinica, o0o.nu, chroot.org
May 22, 2014, Moscow
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
OutlineIntroduction
IOC Standards
V:IOCs
mining IOCs
Applying IOCs
Case studies
Categirizing Incidents
Practical tasks
Analysing Network traffic
Analyzing HTTP logs
Analyzing AV logs
Creating 0wn IOCs
EOF
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Everyone is p0wn3d :)
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Challenges
Main Assumption: All networks are compromisedThe difference between a good security team and a bad security team is thatwith a bad security team you will never know that you’ve been compromised.
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Statistic speaks
I about 40,000,000 internet users in RussiaI for every 10,000 server hosts 500 hosts trigger redirects to malicious
content per weekI about 20-50 user machines (full AV installed, NAT, FW) get ..affected
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Campaigns
r*.ru News ~ 790 000ne*.com news ~ 590 000ga*.ru news ~ 490 000a*f.ru news ~ 330 000m*.ru news ~ 315 000v*.ru news ~ 170 000li*.ru news ~ 170 000top*s.ru news ~ 140 000
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Introduction:terminology
Indicators of CompromiseIndicator of compromise (IOC) in computer forensics is an artifact observed onnetwork or in operating system that with high confidence indicates a computerintrusion.http://en.wikipedia.org/wiki/Indicator_of_compromise
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Why Indicators of compromise
Indicators of Compromise help us to answer questions like:
I is this document/file/hash malicious?I is there any past history for this IP/domain?I what are the other similar/related domains/hashes/..?I who is the actor?I am I an APT target?!!;-)
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Workshop: hands-on part
If you’d like to try as we go, these are tools we are about to cover:I http://github.com/fygrave/ndfI http://github.com/fygrave/hntpI fiddlerI elasticsearch && http://github.com/aol/moloch (vm)I yara (as moloch plugin)I hpfeedsI CIFI https://github.com/STIXProject/ - openioc-to-stix/
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
IOC representations
Multiple standards have been created to facilitate IOC exchanges.I Madiant: OpenIOCI Mitre: STIX (Structured Threat Information Expression), CyBOX
(CyberObservable Expression)I Mitre: CAPEC, TAXIII IODEF (Incident Object Description Format)
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Standards: OpenIOCOpenIOC - Mandiant-backed effort for unform representation of IOC (nowFireEye) http://www.openioc.org/
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
OpenIOCsD i g i t a l Append ices /Appendix G ( D i g i t a l ) − IOCs$ l s0 c7c902c−67f8−479c−9f44−4d985106365a . i o c 6bd24113−2922−4d25−b490−f 727 f47ba948 . i o cad521068−6f18−4ab1−899c−11007 a18ec73 . i o c12 a40bf7−4834−49b0−a419−6abb5fe2b291 . i o c 70 b5be0c−8a94−44b4−97a4−1e95b09498a8 . i o ca f 5 f 6 5 f c−e1ca−45db−88b1−6ccb7191ee6a . i o c2106 f0d2−a260−4277−90ab−edd3455e31fa . i o c 7c739d52−c669−4d51−ac15−8ae66305e232 . i o cAppendix G IOCs README. pdf26213db6−9d3b−4a39−abeb−73656 acb913e . i o c 7 d2eaadf−a5 f f −4199−996e−af6258874dad . i o cc32b8af3−28d0−47d3−801 f−a2c2b0129650 . i o c2 b f f 2 23 f −9e46−47a7−ac35−d35f8138a4c7 . i o c 7 f9a6986−f00a−4071−99d3−484c9158beba . i o cc71b3305−85e5−4d51−b07c−f f 2 27181 fb5a . i o c2 fc55747 −6822−41d2−bcc1−387 fc1b2e67b . i o c 806 be f f 3 −7395−492e−be63−99a6b4a550b8 . i o cc7fa2ea5 −36d5−4a52−a6cf−ddc2257cb6f9 . i o c32b168e6−dbd6−4d56−ba2f −734553239 e f e . i o c 84 f04d f2 −25cd−4f59−a920−448d8843b6fc . i o cd14d5f09−9050−4769−b00d−30 fce9e6eb85 . i o c3433dad8−879e−40d9−98b3−92ddc75f0dcd . i o c 8695bb5e−29cd−41b9−b8b1−a0d20a6b960d . i o cd1c65316−cddd−4d9c−8e fe−c539aa5965c0 . i o c3e01b786−fe3a −4228−95 fa−c3986e2353d6 . i o c 86 e9b8ec−7413−453b−a932−b5fb95a8dba6 . i o cd4f103f8−c372−49d1−b9f4−e127d61d0639 . i o c4 a2c5f60−f4c0−4844−ba1f−a14dac9 fa36c . i o c 86 f988b7−fa02−46df−8e19−e50c e37 f 0 f ed . i o cd5e49501−c30d−41ae−b381−c3c473040c39 . i o c4 d1ced5f−fe47−4ba4−be0e−81d547f3aa8a . i o c 8900 aa6b−883d−48d3−a07d−d49b0429dd2b . i o cd8240090−a f f d −466e−a39c−64add5b98813 . i o c5477b392−e565−45c5−9cb4−f561d6daeddc . i o c 8dd23e0a−a659−45b4−a168−67e4b00944fb . i o ce928aac0−9f71−4adf −9978−4177345 ec610 . i o c547 e4128−9d f f −45d9−b90f−081ce3966dee . i o c 9 c9368cd−3a1f−4200−b093−adb97d5f1 f5d . i o ceb91abad−afe0−4bd6−80f2−850d14a99308 . i o c56468547−6 cf5−4c66−af56 −2543d4271482 . i o c a1f02cbe−7d37−4f f 8−bad7−c5 f 9 f 7 ea63a3 . i o cece1846e−98d3−4ddc−a520−0dcda4866989 . i o c6091 c4ce−6d73−4202−a7a8−b52406fa4d77 . i o c a461f381−8612−4ce1−a0dc−68bcaca028d0 . i o cfabdf553−b3ed−4bc9−9ac6−13d6bd174dad . i o c61695156−298c−4d77−ad7f−48 f eb562 fb75 . i o c a486d837−9f05−4360−908e−b4244c24723d . i o cfd fb2c22−d0c4−4bf0−8ea4−27d8d51f98ea . i o c
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Standards: Mitre
Mitre CybOX: http://cybox.mitre.org/https://github.com/CybOXProject/Toolshttps://github.com/CybOXProject/openioc-to-cybox Mitre CAPEC:http://capec.mitre.org/ Mitre STIX: http://stix.mitre.org/ MitreTAXII http://taxii.mitre.org/
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Mature: stix
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Indicators of Compromise
I Complex IOCs covering all steps of attackI Dynamic creation of IOCs on the flyI Auto-reload of IOCs, TTLsI Dealing with different standards/import export
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Exploit pack trace
url ip mime type refhttp://cuba.eanuncios.net/1/zf3z9lr6ac8di6r4kw2r0hu3ee8ad.html 93.189.46.222 text/html http://www.smeysyatut.ru/ 118162 413 200
http://cuba.eanuncios.net/2909620968/1/1399422480.htm 93.189.46.222 text/html http://cuba.eanuncios.net/1/zf3z9lr6ac8di6r4kw2r0hu3ee8ad.html 37432 441 200
http://cuba.eanuncios.net/2909620968/1/1399422480.jar 93.189.46.222 application/java-archive - 18451 323 200http://cuba.eanuncios.net/2909620968/1/1399422480.jar 93.189.46.222 application/java-archive - 18451 280 200http://cuba.eanuncios.net/f/1/1399422480/2909620968/2 93.189.46.222 - - 115020 244 200http://cuba.eanuncios.net/f/1/1399422480/2909620968/2/2 93.189.46.222 - - 327 246 200
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Nuclearsploit pack{ ’ Nu c l e a r s p l o i t p a c k ’ : {’ s tep1 ’ : {’ f i l e s ’ : [ ’ wz3u6s i8e5 lh7k2tk5ox4ne6d8g . html ’ , ’ t 3 f 5 y9a2bb3d l 7 z8gc4o6 f . html ’ , ’ z f 3 z 9 l r 6 a c8d i 6 r 4 kw2 r 0hu3ee8ad . html ’ , ’ r x 3 v b 9 q g 6 l q 8 l l 6 i j 4 u 2 s a 0 x x 3 l n 8 l e . html ’ , ’ k2qx3dv0ey7 l o3 rp8q6ce4 lw0 fp0z . html ’ , ’ k z6 tp7k4cx3h4 j 8k r3za5a . html ’ , ’ wq6 ln7o4z j3d4 fu8zc3a5sw . html ’ , ’ z2c8mg6h0df2n2ss8kd2e6k7y . html ’ ] ,’ domains ’ : [ ’ f a t h e r . f e r r em o v i l . com ’ , ’ t h a i . a l o h a t r a n s l l c . com ’ , ’ cuba . e anunc i o s . net ’ , ’ duncan . d i s e n o c o r p o r a t i v o . com . ar ’ , ’ homany . c o l l e c t i v e i t . com . au ’ , ’ p r i v a c y . t e r a p i a . o rg . ar ’ ] ,
’ arguments ’ : [ ] ,’ d i r e c t o r i e s ’ : [ ’ 1 ’ ] ,
’ ip ’ : [ ’ 9 3 . 1 8 9 . 4 6 . 2 0 1 ’ , ’ 9 3 . 1 8 9 . 4 6 . 2 0 3 ’ , ’ 9 3 . 1 8 9 . 4 6 . 2 2 2 ’ , ’ 9 3 . 1 8 9 . 4 6 . 2 2 4 ’ , ’ 9 3 . 1 8 9 . 4 6 . 2 3 3 ’ ] } ,’ s tep2 ’ : {’ f i l e s ’ : [ ’ 1399422480 . htm ’ , ’1399704720 . htm ’ , ’1399513440 . htm ’ , ’1399514040 . htm ’ ,’1399773300 . htm ’ ] ,’ domains ’ : [ ’ cuba . e anunc i o s . net ’ , ’ duncan . d i s e n o c o r p o r a t i v o . com . ar ’ , ’ homany . c o l l e c t i v e i t . com . au ’ , ’ p r i v a c y . t e r a p i a . o rg . ar ’ ] ,’ arguments ’ : [ ] ,’ d i r e c t o r i e s ’ : [ ’ 2909620968 ’ , ’ 1 ’ , ’507640988 ’ , ’940276731 ’ , ’3957283574 ’ , ’ 952211704 ’ ] ,’ ip ’ : [ ’ 9 3 . 1 8 9 . 4 6 . 2 2 2 ’ , ’ 9 3 . 1 8 9 . 4 6 . 2 2 4 ’ , ’ 9 3 . 1 8 9 . 4 6 . 2 3 3 ’ ] } ,’ s tep3 ’ : {’ f i l e s ’ : [ ’ 1399422480 . j a r ’ , ’1399513440 . j a r ’ ] ,’ domains ’ : [ ’ cuba . e anunc i o s . net ’ , ’ homany . c o l l e c t i v e i t . com . au ’ ] ,’ arguments ’ : [ ] ,’ d i r e c t o r i e s ’ : [ ’ 2909620968 ’ , ’ 1 ’ , ’ 940276731 ’ ] ,’ ip ’ : [ ’ 9 3 . 1 8 9 . 4 6 . 2 2 2 ’ , ’ 9 3 . 1 8 9 . 4 6 . 2 2 4 ’ ] } ,’ s tep4 ’ : {’ f i l e s ’ : [ ’ 2 ’ ] ,’ domains ’ : [ ’ cuba . e anunc i o s . net ’ ] ,’ arguments ’ : [ ] ,’ d i r e c t o r i e s ’ : [ ’ f ’ , ’ 1 ’ , ’1399422480 ’ , ’2909620968 ’ , ’ 2 ’ ] ,’ ip ’ : [ ’ 9 3 . 1 8 9 . 4 6 . 2 2 2 ’ ] }}}
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Redirect (example)
http://mysimuran.ru/forum/kZsjOiDMFb/ 89.111.178.33 http://agency.accordinga.pw/remain/unknown.html?mods=8&id=26,text/htmlhttp://mysimuran.ru/forum/kZsjOiDMFb/js.js?4231 89.111.178.33 http://mysimuran.ru/forum/kZsjOiDMFb/,text/plainhttp://c.hit.ua/hit?i=59278&g=0&x=2 89.184.81.35 http://mysimuran.ru/forum/kZsjOiDMFb/,image/gifhttp://f-wake.browser-checks.info:28001/d1x/3/87475b26a521024ce78d7ea73164140a/http%3A%2F%2Fagency.accordinga.pw%2Fremain%2Funknown.html%3Fmods%3D8%26id%3D26 46.254.16.209 http://mysimuran.ru/forum/kZsjOiDMFb/,text/html
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Redirect Example{ ’28001 ’ : {’ s tep1 ’ : {
’ d i r e c t o r i e s ’ : [ ’ forum ’ , ’ kZsjOiDMFb ’ , ’ epygFrFsoU ’ ] ,’ arguments ’ : [ ] ,’ f i l e s ’ : [ ’ ’ ] ,’ ip ’ : [ ’ 8 9 . 1 1 1 . 1 7 8 . 3 3 ’ ] ,’ domains ’ : [ ’ mysimuran . ru ’ ] } ,’ s tep2 ’ : {
’ d i r e c t o r i e s ’ : [ ’ forum ’ , ’ kZsjOiDMFb ’ , ’ epygFrFsoU ’ , ’kJXshWOMNC’ ] ,’ arguments ’ : [ ’ 4231 ’ , ’7697 ’ , ’9741 ’ ] ,’ f i l e s ’ : [ ’ j s . j s ’ , ’ cnt . html ’ ] ,’ ip ’ : [ ’ 8 9 . 1 1 1 . 1 7 8 . 3 3 ’ ] ,’ domains ’ : [ ’ mysimuran . ru ’ ] } ,’ s tep3 ’ : {’ d i r e c t o r i e s ’ : [ ] ,’ arguments ’ : [ ’ i ’ , ’ g ’ , ’ x ’ ] ,’ f i l e s ’ : [ ’ h i t ’ ] ,’ ip ’ : [ ’ 8 9 . 1 8 4 . 8 1 . 3 5 ’ ] ,’ domains ’ : [ ’ c . h i t . ua ’ ] } ,’ s tep4 ’ : {’ d i r e c t o r i e s ’ : [ ’ d1x ’ , ’ 3 ’ , ’87475 b26a521024ce78d7ea73164140a ’ , ’ d36eb1fc80ebe9df515d043be1557f57 ’ ] ,’ arguments ’ : [ ] ,’ f i l e s ’ : [ ’ h t tp%3A%2F%2Fagency . a c c o r d i n g a . pw%2Fremain%2Funknown . html%3Fmods%3D8%26i d%3D26 ’ , ’ h t tp%3A%2F%2Fs t ruck . l ookeda . pw%2Fcongre s s%2Fp r e s i d e n t . html%3F lo s e%3D21%26amid%3D463 ’ ] ,’ ip ’ : [ ’ 4 6 . 2 5 4 . 1 6 . 2 0 9 ’ ] ,’ domains ’ : [ ’ f−wake . browser−checks . i n f o ’ , ’ a−oprzay . browser−checks . pw ’ ] }
}}
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
IOCs
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
IOCs3
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
IOCs viz
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
IOCs viz(02)
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
IOCs viz(3)
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
IOCs viz(4)
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
IOCs viz(5)
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Nuclear sploitpack
f u n c t i o n see_user_agent ( ){va r r ep lace_use r_agent =
[ ’ Lunascape ’ , ’ iPhone ’ , ’ Macintosh ’ , ’ L inux ’ , ’ iPad ’ , ’ F l ock ’ , ’ SeaMonkey ’ , ’ Nokia ’ , ’ S l imBrowser ’ , ’AmigaOS ’ , ’ Andro id ’ , ’ FreeBSD ’ , ’ Chrome ’ , ’ IEMob i l e ’ , ’ S e r i e s 4 0 ’ , ’ SymbianOS ’ , ’ Avant ’ , ’ Chromium ’ , ’ F i r e f o x ’ , ’Maxthon ’ , ’ B l a ckBe r r y ’ ] ;va r low_user_agent = f a l s e ;f o r ( va r i i n r ep lace_use r_agent ) {i f ( s t r i p o s ( n a v i g a t o r . userAgent , r ep lace_use r_agent [ i ] ) ) {low_user_agent = true ;break ;
}}return low_user_agent
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Sourcing External IOCsI CIF - https:
//code.google.com/p/collective-intelligence-framework/I feeds (with scrappers):
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Sourcing External IOCsI feed your scrappers:
https://zeustracker.abuse.ch/blocklist.php?download=badipshttp://malc0de.com/database/https://reputation.alienvault.com/reputation.data . . .
I VT intelligence
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Sourcing IOCs Internally
I honeypot feedsI log analysisI traffic analysis
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Where to look for IOCs internally
I Outbound Network TrafficI User Activities/Failed LoginsI User profile foldersI Administrative AccessI Access from unsual IP addressesI Database IO: excessive READsI Size of responses of web pagesI Unusual access to particular files within Web Application (backdoor)I Unusual port/protocol connectionsI DNS and HTTP traffic requestsI Suspicious Scripts, Executables and Data Files
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Challenges
Why we need IOCs? because it makes it easier to systematically describeknowledge about breaches.
I Identifying intrusions is hardI Unfair game:
I defender should protect all the assetsI attacker only needs to ’poop’ one system.
I Identifying targeted, organized intrusions is even harderI Minor anomalous events are important when put togetherI Seeing global picture is a mastI Details matterI Attribution is hard
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Use honeypots
I Running honeypots gives enormous advantage in detecting emerging
threatsI Stategically placing honeypots is extemely important
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
HPfeeds, Hpfriends and more
Compromise Indicator Magic: Living with Compromise Affilations: Academia Sinica, o0o.nu, chroot.org
Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
HPFeeds Architecture
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
HPFeeds API in nutshell:
import pygeo ipimport hp f e ed simport j s o n
HOST=’ b rok e r ’PORT = 20000CHANNELS= [ ’ g eo l o c . e v en t s ’ ]IDENT=’ i d e n t ’SECRET=’ s e c r e t ’g i = pygeo ip . GeoIP ( ’ GeoL i t eC i t y . dat ’ )hpc = hp f e ed s . new (HOST, PORT, IDENT , SECRET)msg = { ’ l a t i t u d e ’ : g i . record_by_addr ( i p ) [ ’ l a t i t u d e ’ ] ,
’ l o n g i t u d e ’ : g i . record_by_addr ( i p ) [ ’ l o n g i t u d e ’ ] ,’ t ype ’ : ’ honeypot ␣ h i t ’ }
hpc . p u b l i s h (CHANNELS, j s o n . dumps (msg ) )
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
hpfeeds integration
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
NTP probe collector
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
HPFeeds and honeymap
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Applying IOCs to your detection processmoloch moloch moloch :)
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Tools for Dynamic Detection of IOC
I SnortI Yara + yara-enabled toolsI MolochI Splunk/Log searchI roll-your-own:p
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Moloch
Moloch is awesome:
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Open-source tools
OpenIOC manipulationhttps://github.com/STIXProject/openioc-to-stixhttps://github.com/tklane/openiocscriptsMantis Threat Intelligence Frameworkhttps://github.com/siemens/django-mantis.git Mantis supportsSTIX/CybOX/IODEF/OpenIOC etc via importers:https://github.com/siemens/django-mantis-openioc-importerSearch splunk data for IOC indicators:https://github.com/technoskald/splunk-searchOur framework: http://github.com/fygrave/iocmap/
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
iocmap
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
MISP
I http://www.secure.edu.pl/pdf/2013/D2_1530_A_Socha.pdfI https://github.com/MISP
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Tools for Dynamic Detection
I MolochI Moloch supports Yara (IOCs can be directly applied)I Moloch has awesome tagger plugin:
# tagge r . so# p r o v i d e s a b i l i t y to impor t t e x t f i l e s w i th IP and/ or hostnames# i n t o a s e n s o r t ha t would cause au to t agg i ng o f a l l matching s e s s i o n sp l u g i n s=tagge r . sot a g g e r I p F i l e s=b l a c k l i s t , tag , tag , tag . . .t a gge rDoma inF i l e s=doma i n b a s e db l a c k l i s t s , tag , tag , tag
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Moloch pluginsMoloch is easily extendable with your own plugins
I https://github.com/fygrave/moloch_zmq - makes it easy tointegrate other things with moloch via zmq queue pub/sub or push/pull model
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Moloch ZMQ example
CEP-based analysis of network-traffic (using ESPER):https://github.com/fygrave/clj-esptool/
( esp : add " c r e a t e ␣ con t e x t ␣SegmentedBySrc␣ p a r t i t i o n ␣by␣ s r c ␣ fromWebDataEvent" )( esp : add " con t e x t ␣SegmentedBySrc␣ s e l e c t ␣ s r c , ␣ r a t e (30) ␣ as ␣ ra t e ,avg ( r a t e ( 30 ) ) ␣ as ␣ avgRate ␣ from␣WebDataEvent . win : t ime (30) ␣ hav ingr a t e (30) ␣<␣avg ( r a t e ( 30 ) ) ␣∗␣ 0 .75 ␣ output ␣ snapshot ␣ e v e r y ␣60␣ sec " )( f u t u r e−c a l l s t a r t−coun t i ng )
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Sources of IOCs
I ioc bucket:
http://iocbucket.com
I Public blacklists/trackers could also be used as source:
https://zeustracker.abuse.ch/blocklist.php?download=ipblocklisthttps://zeustracker.abuse.ch/blocklist.php?download=domainblocklist
I Eset IOC repository
https://github.com/eset/malware-iocmore coming?
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
where to mine IOC
I passive HTTP (keep your data recorded)I passive DNS
These platforms provide ability to mine traffic or patterns from the past basedon IOC similarityshow me all the packets similar to this IOCWe implemented a whois service for IOC look-ups
whois −h i o c . ho s t . com a t t r i b u t e : v a l u e+a t t r i b u t e : v a l u e
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Mining IOCs from your own data
I find and investigate incidentI Or even read paperI determine indicators and test it in YOUR EnvironmentI use new indicators in the future
see IOC cycle we mentioned earlier
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Example
If event chain leads to compromiseht tp : // l i a p o l a s e n s [ . ] i n f o / indexm . html
h t tp : // l i a p o l a s e n s [ . ] i n f o / coun t e r . php? t=f&v=win%2011 ,7 ,700 ,169&a=t r u e
ht tp : // l i a p o l a s e n s [ . ] i n f o /354 RIcx
h t tp : // l i a p o l a s e n s [ . ] i n f o /054 RIcx
What to do?
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Use YARA, or tune your own tools
r u l e susp_params_in_ur l_k ind_of_f i l e l e ss_bot_dr ive_by{
meta :date = " oct ␣2013"d e s c r i p t i o n = "Landing ␣hxxp :// j d a t a s t o r e l ame . i n f o / indexm . html ␣␣ 04 .10 . 2013 ␣ 13 :14 ␣␣ 108 . 62 . 112 . 84 ␣␣"d e s c r i p t i o n 1 = "␣Java ␣ S p l o i t ␣ hxxp :// j d a t a s t o r e l ame . i n f o /054RIwj ␣␣␣␣␣"
s t r i n g s :$ s t r i n g 0 = " ht tp "$ s t r i n g 1 = " indexm . html "$ s t r i n g 2 = "054RI"
c o n d i t i o n :a l l o f them
}
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Use snort to catch suspicious traffic:
# many plugX dep loyments connect to goog l e DNS when not i n usea l e r t tcp !$DNS_SERVERS any −> 8 . 8 . 8 . 8 53 (msg : "APT␣ p o s s i b l e ␣PlugX␣Google ␣DNS␣TCPpo r t ␣53␣ connec t i o n ␣ attempt " ; c l a s s t y p e : misc−a c t i v i t y ; s i d : 500000112 ;r e v : 1 ; )
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
GRR: Google Rapid Response:http://code.google.com/p/grr/Hunting IOC artifacts with GRR
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
GRR: Creating rules
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
GRR: hunt in progress
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Campaign walkthrough
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
An Example
A Network compromise case study:I Attackers broke via a web vuln.I Attackers gained local admin accessI Attackers created a local userI Attackers started probing other machines for default user idsI Attackers launched tunneling tools – connecting back to C2I Attackers installed RATs to maintain access
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Indicators
So what are the compromise indicators here?
I Where did attackers come from? (IP)I What vulnerability was exploited? (pattern)I What web backdoor was used? (pattern, hash)I What tools were uploaded? (hashes)I What users were created locally? (username)I What usernames were probed on other machines
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Good or Bad?F i l e Name : RasTls . exeF i l e S i z e : 105 kBF i l e Mod i f i c a t i o n Date/Time : 2009 :02 :09 19 :42 :05+08:00F i l e Type : Win32 EXEMIME Type : a p p l i c a t i o n / octe t−st reamMachine Type : I n t e l 386 or l a t e r , and compa t i b l e sTime Stamp : 2009 :02 :02 13 :38 :37+08:00PE Type : PE32L i n k e r Ve r s i on : 8 . 0Code S i z e : 49152I n i t i a l i z e d Data S i z e : 57344U n i n i t i a l i z e d Data S i z e : 0Entry Po in t : 0 x3d76OS Ve r s i on : 4 . 0Image Ve r s i on : 0 . 0Subsystem Ve r s i on : 4 . 0Subsystem : Windows GUIF i l e Ve r s i on Number : 1 1 . 0 . 4 0 10 . 7Product Ve r s i on Number : 1 1 . 0 . 4 0 10 . 7F i l e OS : Windows NT 32− b i tObject F i l e Type : Execu tab l e a p p l i c a t i o nLanguage Code : Eng l i s h (U. S . )Cha r a c t e r Set : Windows , La t i n1Company Name : Symantec Co rpo r a t i o nF i l e D e s c r i p t i o n : Symantec 802 .1 x Supp l i c a n tF i l e Ve r s i on : 1 1 . 0 . 4 0 10 . 7I n t e r n a l Name : do t 1 x t r a y
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
It really depends on contextRasTls . DLLRasTls . DLL . mscRasTls . exe
http://msdn.microsoft.com/en-us/library/ms682586(v=VS.85).aspxDynamic-Link Library Search Order
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Catagorization based on public souces
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Catagorization based on historical data
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Catagorization based on cross source correlation
Visualizing the Threats
Filtering noisy extras
Making decisions
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Investigating using known IOCs
Investigating Static host based IOCs
Investigating Dynamic host based IOCs
Investigating Static network IOCs
Investigating Dynamic network IOCs
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Analyzing network traffic and DNS
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
analyzing HTTP traffic
I User agentsI suspicious domainsI static analysis of HTTP headers
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Analyzing AV logs
23 . 01 . 13 19 :56 Detected : Trojan−Spy . Win32 . Zbot . aymrC: / Documents and S e t t i n g s / u s e r 1 / App l i c a t i o n Data/Sun/ Java /Deployment/ cache /6.0/27/4169865b−641d53c9/UPX23 . 01 . 13 19 :56 Detected : Trojan−Downloader . Java . OpenConnect ion . ckC: / Documents and S e t t i n g s / u s e r 1 / App l i c a t i o n Data/Sun/ Java /Deployment/ cache /6.0/48/38388 f30−4a676b87/bpac/b . c l a s s23 . 01 . 13 19 :56 Detected : Trojan−Downloader . Java . OpenConnect ion . c sC : / Documents and S e t t i n g s / u s e r 1 / App l i c a t i o nData/Sun/ Java /Deployment/ cache /6.0/48/38388 f30−4a676b87/ ot / p i z d i . c l a s s23 . 01 . 13 19 :58 Detected : HEUR: E x p l o i t . Java .CVE−2013−0422. genC: / Documents and S e t t i n g s / u s e r 1 / Loca l S e t t i n g s /Temp/ jar_cache3538799837370652468 . tmp
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Analyzing AV logs
01/14/13 06:57 PM 178.238.141.19 http://machete0-yhis.me/ pictures/demos/OAggq application/x-java-archive01/14/13 06:57 PM 178.238.141.19 http://machete0-yhis.me/pictures/demos/OAggq application/x-java-archive01/14/13 06:57 PM 178.238.141.19 http://loretaa0-shot.co/career...45 application/octet-stream
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Analyzing AV logs
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Analyzing AV logs
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Analyzing AV logs
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Creating host based IOCs
hashes, mutexes, threatexpert
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Introduction IOC Standards V:IOCs mining IOCs Applying IOCs Case studies Categirizing Incidents Practical tasks Analysing Network traffic Analyzing HTTP logs Analyzing AV logs Creating 0wn IOCs EOF
Questions
And answers :)
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