On the vulnerability of anti-malware solutions to DNS attacks

Computers & Security(2022)

引用 2|浏览2
暂无评分
摘要
Anti-malware agents typically communicate with their remote services to share information about suspicious files. These remote services use their up-to-date information and global context (view) to help classify the files and instruct their agents to take a predetermined action (e.g., delete or quarantine). In this study, we provide a security analysis of a specific form of communication between anti-malware agents and their services, which takes place entirely over the insecure DNS protocol. These services, which we denote DNS anti-malware list (DNSAML) services, affect the classification of files scanned by anti-malware agents, therefore potentially putting their consumers at risk due to known integrity and confidentiality flaws of the DNS protocol. By analyzing a large-scale DNS traffic dataset made available to the authors by a well-known CDN provider, we identify anti-malware solutions that seem to make use of DNSAML services. We found that these solutions, deployed on almost three million machines worldwide, exchange hundreds of millions of DNS requests daily. These requests carry sensitive file scan information, often - as we demonstrate - without any additional safeguards to compensate for the insecurities of the DNS protocol. As a result, these anti-malware solutions that use DNSAML are vulnerable to DNS attacks. For instance, an attacker capable of tampering with DNS queries gains the ability to alter the classification of scanned files, without a presence on the scanning machine. We showcase three attacks applicable to at least three anti-malware solutions that could result in the disclosure of sensitive information and improper behavior by the anti-malware agent, such as ignoring detected threats. Finally, we propose and review a set of countermeasures for anti-malware solution providers to prevent attacks stemming from the use of DNSAML services.
更多
查看译文
关键词
Anti-malware,DNS,Information disclosure
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要