Stealing in Stealth: Investigating a Python-based Evasive Malware Exela

The Forrester Wave™: Managed Detection and Response, Q2 2023

Stealing in Stealth: Investigating a Python-based Evasive Malware Exela

In an ever-evolving digital landscape, the persistence and adaptability of malicious actors continue to pose significant threats to cybersecurity. One such formidable adversary in the realm of cybercrime is the Exela Stealer, a sophisticated and elusive Python-based malware. 

This report serves as a comprehensive analysis of the Exela Stealer, focusing on both its Cyber Threat Intelligence (CTI) aspects and the intricate technical details that make it a potent and evasive threat. The Exela Stealer stands out as a prime example of the relentless innovation displayed by cybercriminals. Notably, this malware demonstrates a high level of sophistication through its advanced evasion techniques, including robust virtual machine (VM) and sandbox detection mechanisms.

Key findings include:

  • It employs obfuscation and utilizes a packing technique during compilation, making it exceptionally challenging to detect by conventional security solutions. 
  • To further obscure its malicious intent, the Exela Stealer employs a Windows digital signer, effectively masquerading as legitimate software. 
  • The report provides Indicators of Compromise (IOCs) and a YARA rule for detection, enabling security professionals to proactively defend against this resilient threat.
  • The report provides the MITRE ATT&CK techniques utilized by the Exela Stealer, offering insights into its tactics, techniques, and procedures (TTPs). 

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