Encrypted ZIP Scanning Using Header-Derived Password Detection
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Solution Overview
Problem
Anti-malware scanners face challenges in identifying and decrypting encrypted ZIP files, as malware authors exploit the unencrypted local headers within these files to evade detection, allowing malicious files to remain undetected and potentially execute after incorrect password attempts.
Innovation Solution
A method where an anti-malware scanner identifies potential passwords within unencrypted filenames in encrypted ZIP archives, uses these passwords to attempt decryption, and scans the contents for malware, flagging suspicious archives if decryption fails.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the scanner attempts to decrypt encrypted ZIP files using brute force methods, then decryption capability is improved, but resource consumption and processing time increase significantly
Solution Approach 1:
The scanner extracts and analyzes unencrypted local headers and filenames before attempting decryption. By preprocessing the encrypted ZIP file to identify potential password patterns in accessible metadata, the system prepares candidate passwords in advance, avoiding resource-intensive brute force attacks during the actual decryption process.
Solution Approach 2:
The scanner extracts specific unencrypted components (local headers, filenames, comments) from the encrypted ZIP file structure. By separating and analyzing these accessible metadata elements independently from the encrypted content, the system can identify password patterns without needing to decrypt the entire archive, significantly reducing computational resources required.
2Measurement precision
If the scanner analyzes all unencrypted data in encrypted archives, then malware detection accuracy is improved, but processing time increases
Solution Approach 1:
The scanner applies different analysis strategies to different parts of the ZIP file structure. Instead of uniformly processing all data, it focuses intensive pattern matching on specific high-value unencrypted regions (filenames, comments, local headers) that are most likely to contain password information or malware indicators, while skipping less relevant areas.
Solution Approach 2:
The scanner performs partial decryption and analysis by examining only the unencrypted metadata portions of the ZIP file (local headers, filenames, comments) rather than attempting to decrypt and analyze the entire archive content. This partial approach provides sufficient information for malware detection in many cases without the time cost of full decryption.
3Object-affected harmful factors
If malware authors use encrypted ZIP files with obfuscated passwords, then malware evasion capability is improved, but security vulnerability increases due to unencrypted local headers
Solution Approach 1:
The scanner converts the harmful aspect of unencrypted local headers (which malware authors use to hide passwords) into a beneficial detection opportunity. By specifically targeting and analyzing these same unencrypted metadata sections for password patterns and malware indicators, the system transforms the security weakness into a detection advantage, allowing it to uncover hidden passwords and malicious content that would otherwise remain concealed.
Data Source
AI summary
There is disclosed in one example a computing apparatus, including: a hardware platform including a processor and a memory; and one or more mediums including instructions to instruct the processor to provide a security scanner to: determine that an object to be inspected is an archive including a plurality of bundled files; determine that the archive is encrypted; identify unencrypted data within the encrypted archive that can be made visible to an end user after a failed decryption operation; scan the unencrypted data for a pattern that matches password data; and attempt to decrypt the archive according to the password data.