The MalSource Dataset: Quantifying Complexity and Code Reuse in Malware Development
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Abstract (arXiv)
During the last decades, the problem of malicious and unwanted software (malware) has surged in numbers and sophistication. Malware plays a key role in most of today's cyber attacks and has consolidated as a commodity in the underground economy. In this work, we analyze the evolution of malware from 1975 to date from a software engineering perspective. We analyze the source code of 456 samples from 428 unique families and obtain measures of their size, code quality, and estimates of the development costs (effort, time, and number of people). Our results suggest an exponential increment of nearly one order of magnitude per decade in aspects such as size and estimated effort, with code quality metrics similar to those of benign software.We also study the extent to which code reuse is present in our dataset. We detect a significant number of code clones across malware families and report which features and functionalities are more commonly shared. Overall, our results support claims about the increasing complexity of malware and its production progressively becoming an industry.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Nov 2018.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 3; 2025: 2; 2026: 1.
7 papers.
- 2022Jigsaw Puzzle: Selective Backdoor Attack to Subvert Malware Classifierscited by 14
- 2024Evaluating the Efficacy of Large Language Models in Identifying Phishing Attemptscited by 2
- 2024PBP: Post-training Backdoor Purification for Malware Classifierscited by 2
- 2025MASCOT: Analyzing Malware Evolution Through A Well-Curated Source Code Datasetcited by 2
- 2024Counteracting Concept Drift by Learning with Future Malware Predictionscited by 1
- 2025Uplifted Attackers, Human Defenders: The Cyber Offense-Defense Balance for Trailing-Edge Organizationscited by 0
- 2026MASCOT-Android: A Curated Dataset and Automated Collection Pipeline for Android Malware Source Code Specimenscited by 0
- 2026MASCOT-Android: A Curated Dataset and Automated Collection Pipeline for Android Malware Source Code Specimens15 Jun 2026
- 2025MASCOT: Analyzing Malware Evolution Through A Well-Curated Source Code Dataset30 Nov 2025
- 2025Uplifted Attackers, Human Defenders: The Cyber Offense-Defense Balance for Trailing-Edge Organizations14 Aug 2025
- 2024PBP: Post-training Backdoor Purification for Malware Classifiers4 Dec 2024
- 2024Evaluating the Efficacy of Large Language Models in Identifying Phishing Attempts23 Apr 2024
- 2024Counteracting Concept Drift by Learning with Future Malware Predictions14 Apr 2024
- 2022Jigsaw Puzzle: Selective Backdoor Attack to Subvert Malware Classifiers11 Feb 2022