Malicious file hash detection and drive-by download attacks

Abstract

Malicious web content has become the essential tool used by cybercriminals to accomplish their attacks on the Internet. In addition, attacks that target web clients, in comparison to infrastructure components, have become prevalent. Malware drive-by downloads are a recent challenge, as their spread appears to be increasing substantially in malware distribution attacks. In this paper we present our methodology for detecting any malicious file downloaded by one of the network hosts. Our detection method is based on a blacklist of malicious file hashes. We process the network traffic, analyze all connections, and calculate MD5, SHA1, and SHA256 hash for each new file seen being transferred over a connection. Then we match the calculated hashes with the blacklist. The blacklist of malicious file hashes is automatically updated each day and the detection is in the real time.