Christian Mainka (Ruhr University Bochum), Vladislav Mladenov (Ruhr University Bochum), Simon Rohlmann (Ruhr University Bochum)

Digitally signed PDFs are used in contracts and invoices to guarantee the authenticity and integrity of their content. A user opening a signed PDF expects to see a warning in case of *any* modification. In 2019, Mladenov et al. revealed various parsing vulnerabilities in PDF viewer implementations. They showed attacks that could modify PDF documents without invalidating the signature. As a consequence, affected vendors of PDF viewers implemented countermeasures preventing *all* attacks.

This paper introduces a novel class of attacks, which we call *shadow* attacks. The *shadow* attacks circumvent all existing countermeasures and break the integrity protection of digitally signed PDFs. Compared to previous attacks, the *shadow* attacks do not abuse implementation issues in a PDF viewer. In contrast, *shadow* attacks use the enormous flexibility provided by the PDF specification so that *shadow* documents remain standard-compliant. Since *shadow* attacks abuse only legitimate features, they are hard to mitigate.

Our results reveal that 16 (including Adobe Acrobat and Foxit Reader) of the 29 PDF viewers tested were vulnerable to *shadow* attacks. We introduce our tool *PDF-Attacker* which can automatically generate *shadow* attacks. In addition, we implemented *PDF-Detector* to prevent *shadow* documents from being signed or forensically detect exploits after being applied to signed PDFs.

View More Papers

From WHOIS to WHOWAS: A Large-Scale Measurement Study of...

Chaoyi Lu (Tsinghua University; Beijing National Research Center for Information Science and Technology), Baojun Liu (Tsinghua University; Beijing National Research Center for Information Science and Technology; Qi An Xin Group), Yiming Zhang (Tsinghua University; Beijing National Research Center for Information Science and Technology), Zhou Li (University of California, Irvine), Fenglu Zhang (Tsinghua University), Haixin Duan…

Read More

(Short) Spoofing Mobileye 630’s Video Camera Using a Projector

Ben Nassi, Dudi Nassi, Raz Ben Netanel and Yuval Elovici (Ben-Gurion University of the Negev)

Read More

WATSON: Abstracting Behaviors from Audit Logs via Aggregation of...

Jun Zeng (National University of Singapore), Zheng Leong Chua (Independent Researcher), Yinfang Chen (National University of Singapore), Kaihang Ji (National University of Singapore), Zhenkai Liang (National University of Singapore), Jian Mao (Beihang University)

Read More

Effects of Precise and Imprecise Value-Set Analysis (VSA) Information...

Laura Matzen, Michelle A Leger, Geoffrey Reedy (Sandia National Laboratories)

Read More