Visible to the public Shellcode detector for malicious document hunting

TitleShellcode detector for malicious document hunting
Publication TypeConference Paper
Year of Publication2017
AuthorsChen, C. K., Lan, S. C., Shieh, S. W.
Conference Name2017 IEEE Conference on Dependable and Secure Computing
Date Publishedaug
ISBN Number978-1-5090-5569-2
Keywordsadvanced persistent threat attacks, advanced persistent threats, APT attack techniques, Computer crime, Detectors, document handling, Electronic mail, Encryption, feature extraction, Human Behavior, human factors, information retrieval, malicious document detector, malicious document hunting, malicious documents, Malware, network threat, object retrieval, open-source tools, phishing, Portable document format, pubcrawl, shellcode, shellcode detector, simple encryption method, Tools, Web site, Web sites
Abstract

Advanced Persistent Threat (APT) attacks became a major network threat in recent years. Among APT attack techniques, sending a phishing email with malicious documents attached is considered one of the most effective ones. Although many users have the impression that documents are harmless, a malicious document may in fact contain shellcode to attack victims. To cope with the problem, we design and implement a malicious document detector called Forensor to differentiate malicious documents. Forensor integrates several open-source tools and methods. It first introspects file format to retrieve objects inside the documents, and then automatically decrypts simple encryption methods, e.g., XOR, rot and shift, commonly used in malware to discover potential shellcode. The emulator is used to verify the presence of shellcode. If shellcode is discovered, the file is considered malicious. The experiment used 9,000 benign files and more than 10,000 malware samples from a well-known sample sharing website. The result shows no false negative and only 2 false positives.

URLhttp://ieeexplore.ieee.org/document/8073875/
DOI10.1109/DESEC.2017.8073875
Citation Keychen_shellcode_2017