Jens Müller (Ruhr University Bochum), Dominik Noss (Ruhr University Bochum), Christian Mainka (Ruhr University Bochum), Vladislav Mladenov (Ruhr University Bochum), Jörg Schwenk (Ruhr University Bochum)

PDF is the de-facto standard for document exchange. It is common to open PDF files from potentially untrusted sources such as email attachments or downloaded from the Internet. In this work, we perform an in-depth analysis of the capabilities of malicious PDF documents. Instead of focusing on implementation bugs, we abuse legitimate features of the PDF standard itself by systematically identifying dangerous paths in the PDF file structure. These dangerous paths lead to attacks that we categorize into four generic classes: (1) Denial-of-Service attacks affecting the host that processes the document. (2) Information disclosure attacks leaking personal data out of the victim’s computer. (3) Data manipulation on the victim’s system. (4) Code execution on the victim’s machine. An evaluation of 28 popular PDF processing applications shows that 26 of them are vulnerable at least one attack. Finally, we propose a methodology to protect against attacks based on PDF features systematically.

View More Papers

As Strong As Its Weakest Link: How to Break...

Kai Li (Syracuse University), Jiaqi Chen (Syracuse University), Xianghong Liu (Syracuse University), Yuzhe Tang (Syracuse University), XiaoFeng Wang (Indiana University Bloomington), Xiapu Luo (Hong Kong Polytechnic University)

Read More

Data Poisoning Attacks to Deep Learning Based Recommender Systems

Hai Huang (Tsinghua University), Jiaming Mu (Tsinghua University), Neil Zhenqiang Gong (Duke University), Qi Li (Tsinghua University), Bin Liu (West Virginia University), Mingwei Xu (Tsinghua University)

Read More

Demo #4: Attacking Tesla Model X’s Autopilot Using Compromised...

Ben Nassi (Ben-Gurion University of the Negev), Yisroel Mirsky (Ben-Gurion University of the Negev, Georgia Tech), Dudi Nassi, Raz Ben Netanel (Ben-Gurion University of the Negev), Oleg Drokin (Independent Researcher), and Yuval Elovici (Ben-Gurion University of the Negev) Best Demo Award Winner ($300 cash prize)!

Read More