Detecting Malicious JavaScript Code in Mozilla
ICECCS '05 Proceedings of the 10th IEEE International Conference on Engineering of Complex Computer Systems
JavaScript instrumentation for browser security
Proceedings of the 34th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
BrowserShield: Vulnerability-driven filtering of dynamic HTML
ACM Transactions on the Web (TWEB)
Leveraging honest users: stealth command-and-control of botnets
WOOT'13 Proceedings of the 7th USENIX conference on Offensive Technologies
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Malicious javascript frequently serves as a starting point of web-based attacks, in particular cross-site scripting. Thus detecting malicious javascript before execution can protect users from attacks such as malware infection, drive-by downloads, and even from participating in denial-of-service attacks as part of botnet sometimes. A large collection of malicious javascript would help with detector development, but by the time crawler arrives at blacklisted domains attackers and malicious scripts are often long gone. We have used classifiers to direct a web crawler better towards more likely locations of malicious scripts, and show how this targeted web crawler performs compared to crawler seed with blacklisted-domains.