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Advanced malware analysis training session6 malware sandbox analysis

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Advanced malware analysis training session6 malware sandbox analysis

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Disclaimer The Content, Demonstration, Source Code and Programs presented here is "AS IS" without any warranty or conditions of any kind. Also the views/ideas/knowledge expressed here are solely of the trainer’s only and nothing to do with the company or the organization in which the trainer is currently working. However in no circumstances neither the Trainer nor Cysinfo is responsible for any damage or loss caused due to use or misuse of the information presented here.
Acknowledgement  Special thanks to Null community for their extended support and co-operation.  Special thanks to ThoughtWorks for the beautiful venue.  Thanks to all the trainers who have devoted their precious time and countless hours to make it happen.
Advanced Malware Analysis Training This presentation is part of our Advanced Malware Analysis Training program. Currently it is delivered only during our local meets for FREE of cost.
Who am I? Monnappa  Member, Cysinfo  Info Security Investigator @ Cisco  Reversing, Malware Analysis, Memory Forensics.  Email: monnappa22@gmail.com  Twitter: @monnappa22  LinkedIn: http://www.linkedin.com/pub/monnappa-ka-grem-ceh/42/45a/1b8
 Sandbox Overview  Why Sandbox Analysis  Sandbox Architecture  Online Sandboxes  Custom Sandbox (Sandbox.py)  Sandbox.py working  Sandbox.py report  Demo 1&2 (Sandbox Analysis)
 Execute malware in a controlled/monitored environment  Monitors file system, registry, process and network activity  Outputs the results in multiple formats  Examples of Sandboxes ◦ Cuckoo Sandbox ◦ ThreatExpert ◦ Anubis ◦ CWSandbox
To determine:  The nature and purpose of the malware  Interaction with the file system  Interaction with the registry  Interaction with the network  To determine identifiable patterns
Controller Reports ArtifactsPCAPS Host Machine Analysis Machine (VM) Reports Launch Sample Samples Submit Monitoring tools
 Automates static, dynamic and Memory analysis using open source tools  Written in python  Can be run in sandbox mode or internet mode  In sandbox mode it can simulate internet services (this is the default mode)  Allows you to set the timeout for the malware to run (default is 60 seconds)  Stores final reports, pcaps, desktop screeshot , and malicious artifacts for later analysis
 Takes sample as input  Performs static analysis  Reverts VM to clean snapshot  Starts the VM  Transfers the malware to VM  Runs the monitoring tools ( to monitor process, registry, file system, network activity)  Executes the malware for the specified time
 Stops the monitoring tools  Suspends the VM  Acquires the memory image  Performs memory analysis using Volatility framework  Stores the results (Final reports, destkop screenshot, pcaps and malicious artifacts for later analysis)
Static analysis results:  File type (uses magic python module)  Cryptographic hash (md5sum – uses hashlib python module)  VirusTotal results (python script using VirusTotal’s public api)  Determines packers used by malware (uses yara-python)  Determines the capabilities of the malware like IRC, P2P etc etc (uses yara-python module)
Dynamic analysis results:  Determines File system activity  Determines Process activity  Determines Registry activity  Monitor Network activity  Displays DNS summary  Shows TCP conversations  Displays HTTP requests & HTTP request tree
Memory analysis results:  uses Volatility advanced memory forensics framework  displays process, hidden process in memory  displays network connections, terminated network connections  displays listening sockets  determines api hooks, code injection and embedded executable in memory  displays DLL’s loaded by the process memory  displays services in memory  displays the registry keys (like run registry key)
The below screenshot shows the sandbox.py help option
The below screenshot shows the sandbox.py taking sample as input to run it for 30 seconds
The below screenshot shows the static analysis results after executing the sample
The below screenshot shows the dynamic analysis results after executing the sample
The below screenshot shows the network activity after executing the sample
The below screenshot shows the memory analysis results after executing the sample
Thank You !

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Advanced malware analysis training session6 malware sandbox analysis

  • 1.
  • 2. Disclaimer The Content, Demonstration, Source Code and Programs presented here is "AS IS" without any warranty or conditions of any kind. Also the views/ideas/knowledge expressed here are solely of the trainer’s only and nothing to do with the company or the organization in which the trainer is currently working. However in no circumstances neither the Trainer nor Cysinfo is responsible for any damage or loss caused due to use or misuse of the information presented here.
  • 3. Acknowledgement  Special thanks to Null community for their extended support and co-operation.  Special thanks to ThoughtWorks for the beautiful venue.  Thanks to all the trainers who have devoted their precious time and countless hours to make it happen.
  • 4. Advanced Malware Analysis Training This presentation is part of our Advanced Malware Analysis Training program. Currently it is delivered only during our local meets for FREE of cost.
  • 5. Who am I? Monnappa  Member, Cysinfo  Info Security Investigator @ Cisco  Reversing, Malware Analysis, Memory Forensics.  Email: monnappa22@gmail.com  Twitter: @monnappa22  LinkedIn: http://www.linkedin.com/pub/monnappa-ka-grem-ceh/42/45a/1b8
  • 6.  Sandbox Overview  Why Sandbox Analysis  Sandbox Architecture  Online Sandboxes  Custom Sandbox (Sandbox.py)  Sandbox.py working  Sandbox.py report  Demo 1&2 (Sandbox Analysis)
  • 7.  Execute malware in a controlled/monitored environment  Monitors file system, registry, process and network activity  Outputs the results in multiple formats  Examples of Sandboxes ◦ Cuckoo Sandbox ◦ ThreatExpert ◦ Anubis ◦ CWSandbox
  • 8. To determine:  The nature and purpose of the malware  Interaction with the file system  Interaction with the registry  Interaction with the network  To determine identifiable patterns
  • 9. Controller Reports ArtifactsPCAPS Host Machine Analysis Machine (VM) Reports Launch Sample Samples Submit Monitoring tools
  • 10.
  • 11.
  • 12.
  • 13.  Automates static, dynamic and Memory analysis using open source tools  Written in python  Can be run in sandbox mode or internet mode  In sandbox mode it can simulate internet services (this is the default mode)  Allows you to set the timeout for the malware to run (default is 60 seconds)  Stores final reports, pcaps, desktop screeshot , and malicious artifacts for later analysis
  • 14.  Takes sample as input  Performs static analysis  Reverts VM to clean snapshot  Starts the VM  Transfers the malware to VM  Runs the monitoring tools ( to monitor process, registry, file system, network activity)  Executes the malware for the specified time
  • 15.  Stops the monitoring tools  Suspends the VM  Acquires the memory image  Performs memory analysis using Volatility framework  Stores the results (Final reports, destkop screenshot, pcaps and malicious artifacts for later analysis)
  • 16. Static analysis results:  File type (uses magic python module)  Cryptographic hash (md5sum – uses hashlib python module)  VirusTotal results (python script using VirusTotal’s public api)  Determines packers used by malware (uses yara-python)  Determines the capabilities of the malware like IRC, P2P etc etc (uses yara-python module)
  • 17. Dynamic analysis results:  Determines File system activity  Determines Process activity  Determines Registry activity  Monitor Network activity  Displays DNS summary  Shows TCP conversations  Displays HTTP requests & HTTP request tree
  • 18. Memory analysis results:  uses Volatility advanced memory forensics framework  displays process, hidden process in memory  displays network connections, terminated network connections  displays listening sockets  determines api hooks, code injection and embedded executable in memory  displays DLL’s loaded by the process memory  displays services in memory  displays the registry keys (like run registry key)
  • 19.
  • 20. The below screenshot shows the sandbox.py help option
  • 21. The below screenshot shows the sandbox.py taking sample as input to run it for 30 seconds
  • 22. The below screenshot shows the static analysis results after executing the sample
  • 23. The below screenshot shows the dynamic analysis results after executing the sample
  • 24. The below screenshot shows the network activity after executing the sample
  • 25. The below screenshot shows the memory analysis results after executing the sample