Book Image

Learning Malware Analysis

By : Monnappa K A
5 (1)
Book Image

Learning Malware Analysis

5 (1)
By: Monnappa K A

Overview of this book

Malware analysis and memory forensics are powerful analysis and investigation techniques used in reverse engineering, digital forensics, and incident response. With adversaries becoming sophisticated and carrying out advanced malware attacks on critical infrastructures, data centers, and private and public organizations, detecting, responding to, and investigating such intrusions is critical to information security professionals. Malware analysis and memory forensics have become must-have skills to fight advanced malware, targeted attacks, and security breaches. This book teaches you the concepts, techniques, and tools to understand the behavior and characteristics of malware through malware analysis. It also teaches you techniques to investigate and hunt malware using memory forensics. This book introduces you to the basics of malware analysis, and then gradually progresses into the more advanced concepts of code analysis and memory forensics. It uses real-world malware samples, infected memory images, and visual diagrams to help you gain a better understanding of the subject and to equip you with the skills required to analyze, investigate, and respond to malware-related incidents.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
Dedication
Packt Upsell
Contributors
Preface
Index

2. Malware Encryption


Malware authors often use simple encoding techniques, because it is just enough to obscure the data, but sometimes, attackers also use encryption. To identify the use of cryptographic functionality in the binary, you can look for cryptographic indicators (signatures) such as:

  • Strings or imports that reference cryptographic functions
  • Cryptographic constants
  • Unique sequences of instructions used by cryptographic routines

2.1 Identifying Crypto Signatures Using Signsrch

A useful tool to search for the cryptographic signatures in a file or process is Signsrch, which can be downloaded from http://aluigi.altervista.org/mytoolz.htm. This tool relies on cryptographic signatures to detect encryption algorithms.  The cryptographic signatures are located in a text file, signsrch.sig. In the following output, when signsrch is run with the -e option, it displays the relative virtual addresses where the DES signatures were detected in the binary:

C:\signsrch>signsrch.exe -e kav.exe...