File Packing from the Malware Perspective: Techniques, Analysis Approaches, and Directions for Enhancements

Trivikram Muralidharan, Aviad Cohen, Noa Gerson, Nir Nissim

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


With the growing sophistication of malware, the need to devise improved malware detection schemes is crucial. The packing of executable files, which is one of the most common techniques for code protection, has been repurposed for code obfuscation by malware authors as a means of evading malware detectors (mainly static analysis-based detectors). This paper provides statistics on the use of packers based on an extensive analysis of 24,000 PE files (both malicious and benign files) for the past 10 years, which allowed us to observe trends in packing use during that time and showed that packing is still widely used in malware. This paper then surveys 23 methods proposed in academic research for the detection and classification of packed portable executable (PE) files and highlights various trends in malware packing. The paper highlights the differences between the methods and their abilities to detect and identify various aspects of packing. A taxonomy is presented, classifying the methods as static, dynamic, and hybrid analysis-based methods. The paper also sheds light on the increasing role of machine learning methods in the development of modern packing detection methods. We analyzed and mapped the different packing methods and identified which of them can be countered by the detection methods surveyed in this paper.

Original languageEnglish
Article number108
JournalACM Computing Surveys
Issue number5
StatePublished - 3 Dec 2022


  • PE file
  • Packing
  • analysis
  • detection
  • identification
  • malware
  • packer

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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