Corpus ID: 53115849

SAFE-PDF: Robust Detection of JavaScript PDF Malware Using Abstract Interpretation

@article{Jordan2018SAFEPDFRD,
  title={SAFE-PDF: Robust Detection of JavaScript PDF Malware Using Abstract Interpretation},
  author={Alexander Jordan and François Gauthier and Behnaz Hassanshahi and David Zhao},
  journal={ArXiv},
  year={2018},
  volume={abs/1810.12490}
}
The popularity of the PDF format and the rich JavaScript environment that PDF viewers offer make PDF documents an attractive attack vector for malware developers. PDF documents present a serious threat to the security of organizations because most users are unsuspecting of them and thus likely to open documents from untrusted sources. We propose to identify malicious PDFs by using conservative abstract interpretation to statically reason about the behavior of the embedded JavaScript code… Expand
SoK: Arms Race in Adversarial Malware Detection

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