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.

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Доверя́й, но проверя́й: SFI safety for native-compiled Wasm

Evan Johnson (University of California San Diego), David Thien (University of California San Diego), Yousef Alhessi (University of California San Diego), Shravan Narayan (University Of California San Diego), Fraser Brown (Stanford University), Sorin Lerner (University of California San Diego), Tyler McMullen (Fastly Labs), Stefan Savage (University of California San Diego), Deian Stefan (University of California…

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User Expectations and Understanding of Encrypted DNS Settings

Alexandra Nisenoff, Nick Feamster, Madeleine A Hoofnagle†, Sydney Zink. (University of Chicago and †Northwestern)

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Demo #3: Detecting Illicit Drone Video Filming Using Cryptanalysis

Ben Nassi, Raz Ben-Netanel (Ben-Gurion University of the Negev), Adi Shamir (Weizmann Institute of Science), and Yuval Elovic (Ben-Gurion University of the Negev)

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