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Cyber Security Intelligence
Automated Malware Analysis and
과학수사학과 디지털 포렌식 전공
최우석
AMA and Cyber Security Intelligence
2
 이름: 최우석
 소속
• 한국정보보호교육센터 f-NGS 연구소 팀장
• 성균관대학원 과학수사학과 3기
 본업
 사이버 시큐리티 연구
 집필
 Introduce myself
Coming
Soon
with
에이콘
 기타
• 컨설팅 (안전성 진단)
▪ 웹 사이트 진단
▪ 공격 시나리오 기반 컨설팅
• 강의
▪ 악성코드 분야
▪ NISA, 금보원, SKT, 넥슨, 머니투데이, 쿠
시스, 산업통상자원부, 융합보안지원센터
등
• 발표
▪ 코드엔진, 신한시큐어, 한국정보보호학회,
KISA, FIOS 등
• 커뮤니티 활동
▪ 포렌식 인사이트, S2M
역사 & 개론
개발 & 제작
유포 & 감염
조사 & 분석
복구 & 대응
예방 & 관리
AMA and Cyber Security Intelligence
3
 Goals of my life
Playing
Contents
 Cuckoo Sandbox Environment
 Introduction Cuckoo Sandbox
 Cyber Security Intelligence
 Conclusion
소목차
Cuckoo Sandbox
Environment
 Malware Trend
 Type of Malware Analysis's Method
 Open Source License
 Open Source License Comparison
 Sandbox
 Hypervisor
 Hypervisor in Cuckoo Sandbox
 Honeypot Project
 Type of Honeypot Project
Cuckoo Sandbox Environment
6
 Malware Trend
Total Malware New Malware
https://www.av-test.org/en/statistics/malware/
Cuckoo Sandbox Environment
7
 Type of Malware Analysis's Method
Basic
Static Analysis
AV Test
Calculating Hash
Detecting of
Packer/Obfuscation
Extracting of String
Basic
Dynamic Analysis
Process Monitoring
Network Monitoring
Analyzing File System
Analyzing Registry
Advanced
Static Analysis
Analyzing File Format
Analyzing implicit
linking DLL
Disassembling
Decompiling
Advanced
Dynamic Analysis
Debugging
Analyzing explicit
linking DLL
Analyzing Memory
Analyzing
hidden function
Initial Analysis Detail Analysis
Cuckoo Sandbox Environment
8
 Type of Malware Analysis's Method
 in Cuckoo Sandbox
Implementation
Unimplemented
Basic
Static Analysis
AV Test
Calculating Hash
Detecting of
Packer/Obfuscation
Extracting of String
Basic
Dynamic Analysis
Process Monitoring
Network Monitoring
Analyzing File System
Analyzing Registry
Advanced
Static Analysis
Analyzing File Format
Analyzing implicit
linking DLL
Disassembling
Decompiling
Advanced
Dynamic Analysis
Debugging
Analyzing explicit
linking DLL
Analyzing Memory
Analyzing
hidden function
Initial Analysis Detail Analysis
Cuckoo Sandbox Environment
9
 Open Source License
34%
25%
15%
6%
6%
14%
0% 5% 10% 15% 20% 25% 30% 35% 40%
GNU GPL 2.0 & 3.0
MIT
Apache 2.0
BSD 3
GNU LGPL 2.1
Other
2016 Open Source License Top 5
https://resources.whitesourcesoftware.com/blog-whitesource/top-10-open-source-software-licenses-of-2016-and-key-trends
Cuckoo Sandbox Environment
10
 Open Source License Comparison
Licenses Link Distribute Modify Patent Using Private Re-License Brand
GNU GPL Self Non-commercial Non-commercial O O Non-commercial O
MIT O O O X O O X
Apache O O O O O O X
BSD O O O X O O X
GNU LGPL Limit Non-commercial Non-commercial O O Non-commercial O
http://www.bloter.net/archives/209318
 Sandbox is mechanism for separating execution regions in the cyber security
 Controlled by hardware or software resources
 Sandbox mainly use virtualization
 Virtualization
• CPU-dependent
• Hypervisor
• Virtual Machines
Cuckoo Sandbox Environment
11
 Sandbox
 Type of Hypervisor
 Type 1 - VT-d support in CPU
 Type 2 - VT-x support in CPU
Cuckoo Sandbox Environment
12
 Hypervisor
Hardware Type 1 Hypervisor
OS
Hardware Host OS Type 2 Hypervisor
Guest OS
 Purchasing a computer for each operating system is a waste
 Hardware cost, OS cost, Electronic cost, Resource waste in computer
 Malware analysis
 An isolated environment is required
 in Cuckoo Sandbox
 If host OS is the Ubuntu, it will be uncomfortable to use
• For this reason, use nested virtualization
• Nested virtualization support in the VMware Workstation (Type 2)
Cuckoo Sandbox Environment
13
 Hypervisor in Cuckoo Sandbox
Hardware
Host OS
(Windows 10)
Type 2 Hypervisor
(VMware Workstation) Guest OS
(Ubuntu Server)
Type 2 Hypervisor
(Virtualbox)
Sandboxes
Guest OS
(Ubuntu Desktop)
 Requirements
 Easily exposed to hackers
• Intentionally set to vulnerable
• Configure for a variety of situations
 Monitoring everything accessing the system
 Type of Honeypot Project
• Honeynet
▪ Build at the infrastructure level
▪ Early Honeypot Project
• Client Honeypot
▪ Same call HoneyClient
▪ Run at the client level
▪ Mainly Internet Security
Cuckoo Sandbox Environment
14
 Honeypot Project
 High interactivity client honeypot
 Similar to the real environment
• Pros
▪ Ability to detect new attacks
• Cons
▪ High performance deviation, High costs, A lot of time wasted
 Low interactivity client honeypot
 Simulation
• Pros
▪ Low performance deviation, Low cost, Fast detection
• Cons
▪ No new attack detection
 Hybrid client honeypot
 First detection use low interactivity honeypot, second detection use high interactivity honeypot
Cuckoo Sandbox Environment
15
 Type of Client Honeypot
소목차
Introduction
Cuckoo Sandbox
 History of Cuckoo Sandbox
 Analyzable file type
 Operating principle
 Pros and Cons
 Technology
 Functionalities
 Demonstration
Introduction Cuckoo Sandbox
17
 History of Cuckoo Sandbox
Rapid’s
Magnificent7
Malwr
Open
Cuckoo
Foundation
Brucon
2013
Malwr
Reload
New
Website
2012 2013 2014 2015
Dec
v0.5
Oct
v1.1.1Sep
v0.42
Aug
v0.41
Jul
v0.4
Apr
v0.6
Apr
v1.1
Jan
v1.0
Blackhat
2013
Consultancy
Service
Honey
Project
Google
SoC
Feb
v0.32
Dec
v0.3
Nov
v0.2
20112010
Feb
v0.1
Mar
v1.2
Jan
v2.0
2016 2017
Jan
v2.0
RC2
RC1
Jan
v2.0
 Basic Windows File
 Scriptable File
 Office File
 3rd Party Application
Introduction Cuckoo Sandbox
18
 Analyzable file types
Introduction Cuckoo Sandbox
19
 Operating principle
Submit Malware
Report
Analyzed
Data
Web Service Core Sandbox
Cuckoo Sandbox
 Pros
 Open source code
 Produced by python language
 Provides both CLI and GUI modes
 Provide REST API
• Control by HTTP protocol
• System connectivity
 Permanent bug patches and version upgrades
• User community & Feedback of researchers
 Multiple sandboxes can be configured
• If system resources remain...
 Feedback the latest malware issues
• ex, Added DDE analysis function
Introduction Cuckoo Sandbox
20
 Pros and Cons (1/2)
 Cons
 Core functionality is documented well, but additional functionality is insufficient
 If encounter problems, report any issue or self fix the source code
• Issue solving is optional
 Functionalities may be removed without prior consent
 Release progress even if unfinished
• Improvement by participant
• May affect business operations
 Not all malware is analyzed well
• Environment configuration is very important
• Weakness in anti-technology (Anti-Debugging, Anti-Virtualizing ...)
 Limitation of detail analysis
• Can not analyze functions according to specific commands
Introduction Cuckoo Sandbox
21
 Pros and Cons (2/2)
 Cuckoo Core Server
 Ubuntu 16.04 LTS Desktop 64 bit
 CPU 4 Core, Memory 16 GB
 Sandbox x 5
 Win7 SP1 64 bit
 CPU 1 Core, Memory 1024 MB
 Cuckoo Sandbox Application
 2.0.5.3
Introduction Cuckoo Sandbox
22
 Environment
Introduction Cuckoo Sandbox
23
 Infrastructure
Host OS Type 2 Hypervisor
Type 2 Hypervisor
Cuckoo Core Service
(Ubuntu 16.04 Desktop)
Other Service
(Ubuntu 16.04 Server)
 Database
 Scheduling - RDBMS(SQLite, PostgreSQL, MariaDB)
 Web - NoSQL(MongoDB)
 Search - NoSQL(ElasticSearch)
 Support type of hypervisor
 Type 1 - XenServer, VMware(ESX, vSphere), KVM, Qemu
 Type 2 - VMware(Workstation), Virtualbox
 Physical Sandbox - Fog Project
 Android Emulate - AVD
 Memory
 Volatility (with baseline Analysis)
Introduction Cuckoo Sandbox
24
 Technology (1/3)
 Pattern and Signature
 Network Pattern - Snort, Suricata
 Static Binary Pattern - Yara
 Behavior Log Pattern - Only use in Cuckoo Sandbox with python coding
 Network
 Type of Network Line - Proxy, VPN, Tor Network
 Analyzing - Moloch, MiTMProxy
 Server
 Main Web Service - Django
 Distributed and API Service - Werkzeug
 Change server type - Nginx + uWSGI
• Increase Stability
Introduction Cuckoo Sandbox
25
 Technology (2/3)
 Behavior Analysis
 The agent communicates with Cuckoo Core using XML-RPC protocol
 Type of Reports
 HTML, PDF, JSON, Web Service
 Intelligence
 MISP
 System Management
 ICINGA, Supervisord
 Supporting Android Analysis
 GooglePlay, Droidmon, ApkInfo,
 ETC
 VirusTotal, Certification Pinning at PE
Introduction Cuckoo Sandbox
26
 Technology (3/3)
 Hash for malware
 ssdeep, imphash
 Support of archive type malware
 E-Mail, OLE, ZIP
 Analyzing Lateral Movement
 Announce 2.0-RC1, but not implementation
 Network routing
 no routing, drop routing, dirty line, InetSim, Tor, VPN
 TLS/HTTPS capturing and decrypting
 MiTMProxy, HTTPReplay
• But, it has some problem
• HTTPReply is not implementation Certification Pinning
Introduction Cuckoo Sandbox
27
 Functionalities (1/5)
 Baseline analysis in analyzing memory
 It's not documentation!!
 Only in JSON report (not view in Web report)
 Extracting URL in process memory
 When I test with a memory DNS malware, this function is not extract URL.
 Static Binary Pattern and Behavior Log Pattern
 Static Binary Pattern uses YARA
 Behavior Log Pattern should use Cuckoo's dependent functions
• To need python programming
 YARA 3.7.1 can use the Cuckoo Sandbox dependency function.
• But, Cuckoo Sandbox 2.0.5.3 is not support YARA 3.7.1
Introduction Cuckoo Sandbox
28
 Functionalities (2/5)
 Malicious quantify
 Using Behavior Log Pattern
 Max is 10 but possible over 10
 Comparing malware
 Using API call order
 It is well implemented in 1.x version, but in 2.x version
 Implementing a distributed system
 It's not documentation!!
 Implementation using REST API service
 Provide dedicated web services
 Gevent for asynchronous systems, Greenlet for coroutine
 Not enough
• Not support integrated database, only analyzing a file type
Introduction Cuckoo Sandbox
29
 Functionalities (3/5)
Introduction Cuckoo Sandbox
30
 Functionalities (4/5)
 Mass analysis
 Ability to separate functions
Introduction Cuckoo Sandbox
31
 Functionalities (5/5)
Start
Submit
Start analyzing
End analyzing
Generate report
End
Core(analyzing and reporting)
Yes
No
Other Malware
Start
Submit
Start analyzing
End analyzing
End
Generate report
End
Core(analyzing)
Sub Core(reporting)
No No
Yes Yes
Other Malware Other report
 http://192.168.0.100:8000
Introduction Cuckoo Sandbox
32
 Demonstration
 JOESandbox Cloud- https://joesecurity.org/joe-security-products
 BASIC version - (Only Online) Windows + Android
 PRO version - (Standalone) + macOS + iOS + API + Cookbook (Virtual and physical support) + ...
 Report Sample
Introduction Cuckoo Sandbox
33
 Other automated malware analysis tools (1/3)
 Hybrid-analysis - https://www.hybrid-analysis.com/
 Free Service - Only Win7, Only File, Analysis submit limit 30, Sample download
 Private Cloud - Win 10, IoC, YARA, URL, Various reports
 Full Standalone - SIEM system integration(CEF syslog), Custom signature test, Memory dump
 Report Sample
Introduction Cuckoo Sandbox
34
 Other automated malware analysis tools (2/3)
 any run - https://any.run/
 Semi automated cloud malware analysis tools
• Free
• Live access to the virtual machines
 Report Sample
Introduction Cuckoo Sandbox
35
 Other automated malware analysis tools (3/3)
소목차
Cyber Security
Intelligence
 Other automated malware analysis tools
 Cyber Security Intelligence
 Used by many intelligence analysts
 Binary intelligence & limitation
 Purpose
 Identify attacker
 Predict the future through the past
• Incident Response(Establish preventive policy)
Cyber Security Intelligence
37
 Cyber Security Intelligence
Tactics, Techniques and Procedures
https://en.wikipedia.org/wiki/PLA_Unit_61398
http://detect-respond.blogspot.kr/2013/03/the-pyramid-of-pain.html
 Automated malware analysis and Cyber Security Intelligence
 Purpose
• Automatically analyze numerous malware and accumulate analytical data
 Used by many intelligence analysts
 VirusTotal used Cuckoo Sandbox
Cyber Security Intelligence
38
 Cyber Security Intelligence
 Used by many intelligencer in cyber security
Cyber Security Intelligence
39
 Cyber Security Intelligence
https://digital-forensics.sans.org/summit-archives/DFIR_Summit/Open-Source-Threat-Intelligence-Kyle-Maxwell.pdf
 Used by many intelligencer in cyber security
Cyber Security Intelligence
40
 Cyber Security Intelligence
https://www.rsaconference.com/writable/presentations/file_upload/anf-t10_implementing-an-automated-incident-response-architecture.pdf
 Used by many intelligencer in cyber security
Cyber Security Intelligence
41
 Cyber Security Intelligence
https://sector.ca/wp-content/uploads/presentations16/simmons%20Open%20Source%20Malware%20Lab%20SecTor.pdf
 Papers related to Cuckoo Sandbox
Cyber Security Intelligence
42
 Cyber Security Intelligence
www.cs.ucsb.edu/~vigna/publications/2014_USENIX_BareCloud.pdf
adamdoupe.com/publications/towards-automated-threat-intelligence-fusion-cic2016.pdf
2016, IEEE
nsl.cs.waseda.ac.jp/~mori/papers/ccnc15-fujino-sumitted.pdf
2015, IEEE
arxiv.org/pdf/1709.08753.pdf
2017, IEEE
2014,
USENIX
 Binary intelligence
 Same mean client-side intelligence but, not strictly
 Various attack type statistics used by binaries
 If collect a lot of malware, can analyze the association
 Limitation of binary intelligence
 Counter intelligence
• Vulnerability of evidence
 More data to overcome
• Need server-side intelligence
▪ But, no ownership and investigation
Cyber Security Intelligence
43
 Binary intelligence & limitation
소목차
Conclusion
 Matthew Effect
 [OR] Next Project
 with Digital Forensics
Conclusion
45
 Matthew Effect
The Matthew Effect
= much data is good quality information
Conclusion
46
 with Digital Forensics
 Include Digital Forensics process in Incident Response
 Importance of DFIR
• But, availability vs. integrity
 So many question (Can ~ be evidence?)
 Can information gathered from the Internet be evidence?
 Can malware analysis information be evidence?
 Can data without a chain of custody be evidence?
 Can data collected from untrusted tools be evidence?
 ...
 No!
 Digital evidence is very regrettable in Korea
• And, too difficult to follow the speed of rapid development
• Rapid of singularity!!
 Information collected by intelligence activities can not be evidence
Q & A
The End

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Automated Malware Analysis and Cyber Security Intelligence

  • 1. Cyber Security Intelligence Automated Malware Analysis and 과학수사학과 디지털 포렌식 전공 최우석
  • 2. AMA and Cyber Security Intelligence 2  이름: 최우석  소속 • 한국정보보호교육센터 f-NGS 연구소 팀장 • 성균관대학원 과학수사학과 3기  본업  사이버 시큐리티 연구  집필  Introduce myself Coming Soon with 에이콘  기타 • 컨설팅 (안전성 진단) ▪ 웹 사이트 진단 ▪ 공격 시나리오 기반 컨설팅 • 강의 ▪ 악성코드 분야 ▪ NISA, 금보원, SKT, 넥슨, 머니투데이, 쿠 시스, 산업통상자원부, 융합보안지원센터 등 • 발표 ▪ 코드엔진, 신한시큐어, 한국정보보호학회, KISA, FIOS 등 • 커뮤니티 활동 ▪ 포렌식 인사이트, S2M
  • 3. 역사 & 개론 개발 & 제작 유포 & 감염 조사 & 분석 복구 & 대응 예방 & 관리 AMA and Cyber Security Intelligence 3  Goals of my life Playing
  • 4. Contents  Cuckoo Sandbox Environment  Introduction Cuckoo Sandbox  Cyber Security Intelligence  Conclusion
  • 5. 소목차 Cuckoo Sandbox Environment  Malware Trend  Type of Malware Analysis's Method  Open Source License  Open Source License Comparison  Sandbox  Hypervisor  Hypervisor in Cuckoo Sandbox  Honeypot Project  Type of Honeypot Project
  • 6. Cuckoo Sandbox Environment 6  Malware Trend Total Malware New Malware https://www.av-test.org/en/statistics/malware/
  • 7. Cuckoo Sandbox Environment 7  Type of Malware Analysis's Method Basic Static Analysis AV Test Calculating Hash Detecting of Packer/Obfuscation Extracting of String Basic Dynamic Analysis Process Monitoring Network Monitoring Analyzing File System Analyzing Registry Advanced Static Analysis Analyzing File Format Analyzing implicit linking DLL Disassembling Decompiling Advanced Dynamic Analysis Debugging Analyzing explicit linking DLL Analyzing Memory Analyzing hidden function Initial Analysis Detail Analysis
  • 8. Cuckoo Sandbox Environment 8  Type of Malware Analysis's Method  in Cuckoo Sandbox Implementation Unimplemented Basic Static Analysis AV Test Calculating Hash Detecting of Packer/Obfuscation Extracting of String Basic Dynamic Analysis Process Monitoring Network Monitoring Analyzing File System Analyzing Registry Advanced Static Analysis Analyzing File Format Analyzing implicit linking DLL Disassembling Decompiling Advanced Dynamic Analysis Debugging Analyzing explicit linking DLL Analyzing Memory Analyzing hidden function Initial Analysis Detail Analysis
  • 9. Cuckoo Sandbox Environment 9  Open Source License 34% 25% 15% 6% 6% 14% 0% 5% 10% 15% 20% 25% 30% 35% 40% GNU GPL 2.0 & 3.0 MIT Apache 2.0 BSD 3 GNU LGPL 2.1 Other 2016 Open Source License Top 5 https://resources.whitesourcesoftware.com/blog-whitesource/top-10-open-source-software-licenses-of-2016-and-key-trends
  • 10. Cuckoo Sandbox Environment 10  Open Source License Comparison Licenses Link Distribute Modify Patent Using Private Re-License Brand GNU GPL Self Non-commercial Non-commercial O O Non-commercial O MIT O O O X O O X Apache O O O O O O X BSD O O O X O O X GNU LGPL Limit Non-commercial Non-commercial O O Non-commercial O http://www.bloter.net/archives/209318
  • 11.  Sandbox is mechanism for separating execution regions in the cyber security  Controlled by hardware or software resources  Sandbox mainly use virtualization  Virtualization • CPU-dependent • Hypervisor • Virtual Machines Cuckoo Sandbox Environment 11  Sandbox
  • 12.  Type of Hypervisor  Type 1 - VT-d support in CPU  Type 2 - VT-x support in CPU Cuckoo Sandbox Environment 12  Hypervisor Hardware Type 1 Hypervisor OS Hardware Host OS Type 2 Hypervisor Guest OS
  • 13.  Purchasing a computer for each operating system is a waste  Hardware cost, OS cost, Electronic cost, Resource waste in computer  Malware analysis  An isolated environment is required  in Cuckoo Sandbox  If host OS is the Ubuntu, it will be uncomfortable to use • For this reason, use nested virtualization • Nested virtualization support in the VMware Workstation (Type 2) Cuckoo Sandbox Environment 13  Hypervisor in Cuckoo Sandbox Hardware Host OS (Windows 10) Type 2 Hypervisor (VMware Workstation) Guest OS (Ubuntu Server) Type 2 Hypervisor (Virtualbox) Sandboxes Guest OS (Ubuntu Desktop)
  • 14.  Requirements  Easily exposed to hackers • Intentionally set to vulnerable • Configure for a variety of situations  Monitoring everything accessing the system  Type of Honeypot Project • Honeynet ▪ Build at the infrastructure level ▪ Early Honeypot Project • Client Honeypot ▪ Same call HoneyClient ▪ Run at the client level ▪ Mainly Internet Security Cuckoo Sandbox Environment 14  Honeypot Project
  • 15.  High interactivity client honeypot  Similar to the real environment • Pros ▪ Ability to detect new attacks • Cons ▪ High performance deviation, High costs, A lot of time wasted  Low interactivity client honeypot  Simulation • Pros ▪ Low performance deviation, Low cost, Fast detection • Cons ▪ No new attack detection  Hybrid client honeypot  First detection use low interactivity honeypot, second detection use high interactivity honeypot Cuckoo Sandbox Environment 15  Type of Client Honeypot
  • 16. 소목차 Introduction Cuckoo Sandbox  History of Cuckoo Sandbox  Analyzable file type  Operating principle  Pros and Cons  Technology  Functionalities  Demonstration
  • 17. Introduction Cuckoo Sandbox 17  History of Cuckoo Sandbox Rapid’s Magnificent7 Malwr Open Cuckoo Foundation Brucon 2013 Malwr Reload New Website 2012 2013 2014 2015 Dec v0.5 Oct v1.1.1Sep v0.42 Aug v0.41 Jul v0.4 Apr v0.6 Apr v1.1 Jan v1.0 Blackhat 2013 Consultancy Service Honey Project Google SoC Feb v0.32 Dec v0.3 Nov v0.2 20112010 Feb v0.1 Mar v1.2 Jan v2.0 2016 2017 Jan v2.0 RC2 RC1 Jan v2.0
  • 18.  Basic Windows File  Scriptable File  Office File  3rd Party Application Introduction Cuckoo Sandbox 18  Analyzable file types
  • 19. Introduction Cuckoo Sandbox 19  Operating principle Submit Malware Report Analyzed Data Web Service Core Sandbox Cuckoo Sandbox
  • 20.  Pros  Open source code  Produced by python language  Provides both CLI and GUI modes  Provide REST API • Control by HTTP protocol • System connectivity  Permanent bug patches and version upgrades • User community & Feedback of researchers  Multiple sandboxes can be configured • If system resources remain...  Feedback the latest malware issues • ex, Added DDE analysis function Introduction Cuckoo Sandbox 20  Pros and Cons (1/2)
  • 21.  Cons  Core functionality is documented well, but additional functionality is insufficient  If encounter problems, report any issue or self fix the source code • Issue solving is optional  Functionalities may be removed without prior consent  Release progress even if unfinished • Improvement by participant • May affect business operations  Not all malware is analyzed well • Environment configuration is very important • Weakness in anti-technology (Anti-Debugging, Anti-Virtualizing ...)  Limitation of detail analysis • Can not analyze functions according to specific commands Introduction Cuckoo Sandbox 21  Pros and Cons (2/2)
  • 22.  Cuckoo Core Server  Ubuntu 16.04 LTS Desktop 64 bit  CPU 4 Core, Memory 16 GB  Sandbox x 5  Win7 SP1 64 bit  CPU 1 Core, Memory 1024 MB  Cuckoo Sandbox Application  2.0.5.3 Introduction Cuckoo Sandbox 22  Environment
  • 23. Introduction Cuckoo Sandbox 23  Infrastructure Host OS Type 2 Hypervisor Type 2 Hypervisor Cuckoo Core Service (Ubuntu 16.04 Desktop) Other Service (Ubuntu 16.04 Server)
  • 24.  Database  Scheduling - RDBMS(SQLite, PostgreSQL, MariaDB)  Web - NoSQL(MongoDB)  Search - NoSQL(ElasticSearch)  Support type of hypervisor  Type 1 - XenServer, VMware(ESX, vSphere), KVM, Qemu  Type 2 - VMware(Workstation), Virtualbox  Physical Sandbox - Fog Project  Android Emulate - AVD  Memory  Volatility (with baseline Analysis) Introduction Cuckoo Sandbox 24  Technology (1/3)
  • 25.  Pattern and Signature  Network Pattern - Snort, Suricata  Static Binary Pattern - Yara  Behavior Log Pattern - Only use in Cuckoo Sandbox with python coding  Network  Type of Network Line - Proxy, VPN, Tor Network  Analyzing - Moloch, MiTMProxy  Server  Main Web Service - Django  Distributed and API Service - Werkzeug  Change server type - Nginx + uWSGI • Increase Stability Introduction Cuckoo Sandbox 25  Technology (2/3)
  • 26.  Behavior Analysis  The agent communicates with Cuckoo Core using XML-RPC protocol  Type of Reports  HTML, PDF, JSON, Web Service  Intelligence  MISP  System Management  ICINGA, Supervisord  Supporting Android Analysis  GooglePlay, Droidmon, ApkInfo,  ETC  VirusTotal, Certification Pinning at PE Introduction Cuckoo Sandbox 26  Technology (3/3)
  • 27.  Hash for malware  ssdeep, imphash  Support of archive type malware  E-Mail, OLE, ZIP  Analyzing Lateral Movement  Announce 2.0-RC1, but not implementation  Network routing  no routing, drop routing, dirty line, InetSim, Tor, VPN  TLS/HTTPS capturing and decrypting  MiTMProxy, HTTPReplay • But, it has some problem • HTTPReply is not implementation Certification Pinning Introduction Cuckoo Sandbox 27  Functionalities (1/5)
  • 28.  Baseline analysis in analyzing memory  It's not documentation!!  Only in JSON report (not view in Web report)  Extracting URL in process memory  When I test with a memory DNS malware, this function is not extract URL.  Static Binary Pattern and Behavior Log Pattern  Static Binary Pattern uses YARA  Behavior Log Pattern should use Cuckoo's dependent functions • To need python programming  YARA 3.7.1 can use the Cuckoo Sandbox dependency function. • But, Cuckoo Sandbox 2.0.5.3 is not support YARA 3.7.1 Introduction Cuckoo Sandbox 28  Functionalities (2/5)
  • 29.  Malicious quantify  Using Behavior Log Pattern  Max is 10 but possible over 10  Comparing malware  Using API call order  It is well implemented in 1.x version, but in 2.x version  Implementing a distributed system  It's not documentation!!  Implementation using REST API service  Provide dedicated web services  Gevent for asynchronous systems, Greenlet for coroutine  Not enough • Not support integrated database, only analyzing a file type Introduction Cuckoo Sandbox 29  Functionalities (3/5)
  • 30. Introduction Cuckoo Sandbox 30  Functionalities (4/5)
  • 31.  Mass analysis  Ability to separate functions Introduction Cuckoo Sandbox 31  Functionalities (5/5) Start Submit Start analyzing End analyzing Generate report End Core(analyzing and reporting) Yes No Other Malware Start Submit Start analyzing End analyzing End Generate report End Core(analyzing) Sub Core(reporting) No No Yes Yes Other Malware Other report
  • 33.  JOESandbox Cloud- https://joesecurity.org/joe-security-products  BASIC version - (Only Online) Windows + Android  PRO version - (Standalone) + macOS + iOS + API + Cookbook (Virtual and physical support) + ...  Report Sample Introduction Cuckoo Sandbox 33  Other automated malware analysis tools (1/3)
  • 34.  Hybrid-analysis - https://www.hybrid-analysis.com/  Free Service - Only Win7, Only File, Analysis submit limit 30, Sample download  Private Cloud - Win 10, IoC, YARA, URL, Various reports  Full Standalone - SIEM system integration(CEF syslog), Custom signature test, Memory dump  Report Sample Introduction Cuckoo Sandbox 34  Other automated malware analysis tools (2/3)
  • 35.  any run - https://any.run/  Semi automated cloud malware analysis tools • Free • Live access to the virtual machines  Report Sample Introduction Cuckoo Sandbox 35  Other automated malware analysis tools (3/3)
  • 36. 소목차 Cyber Security Intelligence  Other automated malware analysis tools  Cyber Security Intelligence  Used by many intelligence analysts  Binary intelligence & limitation
  • 37.  Purpose  Identify attacker  Predict the future through the past • Incident Response(Establish preventive policy) Cyber Security Intelligence 37  Cyber Security Intelligence Tactics, Techniques and Procedures https://en.wikipedia.org/wiki/PLA_Unit_61398 http://detect-respond.blogspot.kr/2013/03/the-pyramid-of-pain.html
  • 38.  Automated malware analysis and Cyber Security Intelligence  Purpose • Automatically analyze numerous malware and accumulate analytical data  Used by many intelligence analysts  VirusTotal used Cuckoo Sandbox Cyber Security Intelligence 38  Cyber Security Intelligence
  • 39.  Used by many intelligencer in cyber security Cyber Security Intelligence 39  Cyber Security Intelligence https://digital-forensics.sans.org/summit-archives/DFIR_Summit/Open-Source-Threat-Intelligence-Kyle-Maxwell.pdf
  • 40.  Used by many intelligencer in cyber security Cyber Security Intelligence 40  Cyber Security Intelligence https://www.rsaconference.com/writable/presentations/file_upload/anf-t10_implementing-an-automated-incident-response-architecture.pdf
  • 41.  Used by many intelligencer in cyber security Cyber Security Intelligence 41  Cyber Security Intelligence https://sector.ca/wp-content/uploads/presentations16/simmons%20Open%20Source%20Malware%20Lab%20SecTor.pdf
  • 42.  Papers related to Cuckoo Sandbox Cyber Security Intelligence 42  Cyber Security Intelligence www.cs.ucsb.edu/~vigna/publications/2014_USENIX_BareCloud.pdf adamdoupe.com/publications/towards-automated-threat-intelligence-fusion-cic2016.pdf 2016, IEEE nsl.cs.waseda.ac.jp/~mori/papers/ccnc15-fujino-sumitted.pdf 2015, IEEE arxiv.org/pdf/1709.08753.pdf 2017, IEEE 2014, USENIX
  • 43.  Binary intelligence  Same mean client-side intelligence but, not strictly  Various attack type statistics used by binaries  If collect a lot of malware, can analyze the association  Limitation of binary intelligence  Counter intelligence • Vulnerability of evidence  More data to overcome • Need server-side intelligence ▪ But, no ownership and investigation Cyber Security Intelligence 43  Binary intelligence & limitation
  • 44. 소목차 Conclusion  Matthew Effect  [OR] Next Project  with Digital Forensics
  • 45. Conclusion 45  Matthew Effect The Matthew Effect = much data is good quality information
  • 46. Conclusion 46  with Digital Forensics  Include Digital Forensics process in Incident Response  Importance of DFIR • But, availability vs. integrity  So many question (Can ~ be evidence?)  Can information gathered from the Internet be evidence?  Can malware analysis information be evidence?  Can data without a chain of custody be evidence?  Can data collected from untrusted tools be evidence?  ...  No!  Digital evidence is very regrettable in Korea • And, too difficult to follow the speed of rapid development • Rapid of singularity!!  Information collected by intelligence activities can not be evidence
  • 47. Q & A