Malware Analysis is a process to understand the behavior and purpose of a suspicious file, setup, attachment, URL or source code. Security analysts are asked to regularly check and balance a suspicious file to see whether it is legitimate or malicious. You can use these 7 best Python malware libraries that are a must-have for every ethical hacker in their arsenal and their ready-made scripts.
Now why it is important for incident responders to have such tools? Well:
- Like this false positives are reduced.
- Check code that may be malicious.
- It is understood how extensive the incident is or the damage it has done.
The main aim is to have a deep understanding of how a certain piece of malware functions so that a proper defense can be built to protect the network of the organization.
Different Phases of Malware Analysis
It is used to examine the specimen’s interaction with its environments like the file system, registry, network and other processes and components of the operating system.
It is used to reverse-engineer the program which is malicious with the purpose to understand the code which implements the behavior of the specimen.
It is used to examine the memory of the system which has been infected in order to extract artifacts relevant to the malicious program.
Advantages and Disadvantages of using Python for Malware Analysis
- When threat hunting it is rich in context.
- It improvises the efficacy of IOC alerts and notifications.
- It uncovers all the hidden indicators of compromise (IOCs) which need to be blocked.
There are many issues in this which have seen to be undecidable, these include the following:
- Detection of virus.
- Detection of unpacking execution.
- Matching of malware samples against set of given templates.
- Detecting trigger-based behavior.
How to Analyse Malware? (The right approach)
For this there are two ways to approach it:
- Static Analysis
In this the sample of malware is examined without denoting it.
- Dynamic Analysis
In this, the malware is executed in an environment that is controlled and isolated. You can use a virtual environment that you could create with VMWare or Hyper-V then install an IDE such as Ninja-IDE, PyCharm or IntelliJ.
Let’s have a glimpse of all the 5 crucial steps involved:
- First, you need to capture the malware.
- Once done, build a malware lab.
- Install all the required tools.
- Then record the baseline.
- After this put your results in the form of documentation.
7 Best and Ideal Libraries and Tools for Malware Analysis with Python
With Python being a popular and in-demand language, python developers are in demand in the cybersecurity industry. It is in various projects including Windows and Android keyloggers, weather predicting projects and text-to-speech AI/ML-based work. It is huge!
If you are a malware analyst then you need to have skills in reverse engineering as well as programming along with some familiarity with system operations and how they tend to work.
We have compiled for you a list of such tools, follow through to know more:
Yara-Python – Malware and Virus classifier
It is a library that allows you to use YARA from Python programs. It is a tool that is used to:
- Detect malware.
It lets you use YARA to identify and classify different malware present in malware programs.
Wondering how it is done? Well, they create descriptions of malware families which are based on textual or binary patterns. Moreover, it also carries modules to process PE, and ELF analysis.
This can be installed by running:
Paul@ninja-ide:~# apt-get install yara-python
Pyew – Disassembly Support
This is a python command line tool that is used to perform malware analysis.
To be precise it is a command-line hexadecimal editor and disassembler which is used to perform code analysis and let you write scripts by using an API in order to perform different kinds of malware and other analysis.
It has gained a lot of popularity and has been top of the list for more than 4 years in large malware analysis systems.
With this each day thousands of files are processed.
Malgazer – Malware Analysis powered by ML
It is another python library that is used for malware analysis along with machine learning.
Exefilter – Filteration of files
It is a python tool that comes in free and is open-source. A framework that is used to:
- Filter file formats in:
- Web pages.
- Detect many file formats and remove active content according to a configured policy.
Moreover, it is used to:
- Provide protection against malicious content present within the file.
- Filter out removable devices either in gateways which include email, web services, web and much more, or on user workstations.
It carries a whitelist algorithm and a huge list of supported file formats which makes it highly effective in controlling which format of the file is allowed to enter into a secured network.
Clamd (ClamAV) – Open-source Scanner
It is another python package that serves as an interface to Clamd which is the daemon for ClamAV anti-virus. With this what you can do is use this ClamAV anti-virus engine on the following:
- MacOSX and others.
Note: It needs a running instance of clamd daemon.
With this, you can add virus detection capabilities to all the python software or programs.
Install via apt-get:
Paul@ninja-ide:~# apt-get install clamd
r2pipe – Reverse Engineer galore
This is a Python API Radare2 which is a free toolchain or framework for:
- Reverse engineering.
- Analyzing binaries.
Now it is applied to low-level tasks which include the following:
- Software debugging.
- Software reverse engineering.
- Analyze malware.
- Simplify specific tasks.
- Emulate a code section.
- Decrypt strings.
- Reverse engineer multiple binaries.
It shall provide you with an easy yet effective way to script radare2 which carries one function which takes a string representing r2 command in order to run and then return the output as a string.
To install with apt-get:
Paul@ninja-ide:~# apt-get install r2pipe
angr – Binary analysis made easy
The last python framework on the list which is multi-architecture is used to analyze binaries that have the capability to perform dynamic symbolic execution and multiple static analyses.
It has been designed primarily to help reverse engineer and Analyze internal servers of complex and closed-source software by providing tools to tell the system to execute program behaviors along with analyzing them for potential vulnerabilities. Sound’s cool!
- Strings extraction.
- Data clustering.
- Instruction emulation.
- Symbolic execution.
- Find different bugs.
- Figure how code works.
- Exploit vulnerabilities.
Malware analysis is a hot topic due to the recent malware outbreaks and data breaches such as the T-Mobile one. Knowing how to analyze and reverse engineer the malware code can help you understand its inner workings and how to protect against it. It is like getting to know them inside the mechanism of a lock. You can use any of the 7 Malware analysis libraries and tools we shared to scan Python code or do your own research!