Paint It Black: Evaluating the Effectiveness of Malware Blacklists

Abstract

Blacklists are commonly used to protect computer systems against the tremendous number of malware threats. These lists include abusive hosts such as malware sites or botnet Command & Control and dropzone servers to raise alerts if suspicious hosts are contacted. Up to now, though, little is known about the effectiveness of malware blacklists.

In this paper, we empirically analyze 15 public malware blacklists and 4 blacklists operated by antivirus (AV) vendors. We aim to categorize the blacklist content to understand the nature of the listed domains and IP addresses. First, we propose a mechanism to identify parked domains in blacklists, which we find to constitute a substantial number of blacklist entries. Second, we develop a graph-based approach to identify sinkholes in the blacklists, i.e., servers that host malicious domains which are controlled by security organizations. In a thorough evaluation of blacklist effectiveness, we show to what extent real-world malware domains are actually covered by blacklists. We find that the union of all 15 public blacklists includes less than 20% of the malicious domains for a majority of prevalent malware families and most AV vendor blacklists fail to protect against malware that utilizes Domain Generation Algorithms.