adeilsonsilva/malware-injection
Official implementation for the paper "On deceiving malware classification with section injection"
This project helps cybersecurity researchers and malware analysts evaluate the robustness of their malware classification models. You provide a dataset of executable files, categorized as benign or malicious, and the tool will generate new, modified versions of these files with injected sections. These modified executables are then used to test how well machine learning models can still detect malware, even when it tries to hide itself.
No commits in the last 6 months.
Use this if you need to assess the resilience of your malware detection systems against sophisticated evasion techniques, specifically those involving section injection.
Not ideal if you are looking for a general-purpose malware analysis tool or an off-the-shelf solution for detecting new malware threats.
Stars
36
Forks
2
Language
Python
License
GPL-3.0
Category
Last pushed
Aug 16, 2022
Commits (30d)
0
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