Researchers Break Digital Signatures For Most Desktop PDF Viewers

Peter Reutemann <[email protected]>
Newsgroups gmane.org.user-groups.linux.waikato
Message-ID <CAHoQ12LarS+Z-DmEEkhf_qiHO5bnpzWD9dFaDKfUC76T-Qmx+w@mail.gmail.com>
'A team of academics from the Ruhr-University Bochum in Germany say
they've managed to break the digital signing system and create fake
signatures on 21 of 22 desktop PDF viewer apps and five out of seven
online PDF digital signing services. This includes apps such as Adobe
Acrobat Reader, Foxit Reader, and LibreOffice, and online services
like DocuSign and Evotrust --just to name the most recognizable names.
The five-person research team has been working since early October
2018 together with experts from Germany's Computer Emergency Response
Team (BSI-CERT) to notify impacted services. The team went public with
their findings over the weekend after all affected app makers and
commercial companies finished patching their products. In research
published today, the Ruhr-University Bochum team described three
vulnerabilities that they found in the digital signing process used by
several desktop and web-based PDF signing services. Summarized, they
are:

1. Universal Signature Forgery (USF) -- vulnerability lets attackers
trick the signature verification process into showing users a fake
panel/message that the signature is valid.
2. Incremental Saving Attack (ISA) -- vulnerability lets attackers add
extra content to an already signed PDF document via the "incremental
saving (incremental update)" mechanism, but without breaking the
already-existing signature.
3. Signature Wrapping (SWA) -- vulnerability is similar to ISA, but
the malicious code also contains extra logic to fool the signature
validation process into "wrapping" around the attacker's extra
content, effectively digitally signing the incremental update.'

-- source: https://it.slashdot.org/story/19/02/25/2126208

Cheers, Peter
-- 
Peter Reutemann
Dept. of Computer Science
University of Waikato, NZ
+64 (7) 858-5174
http://www.cms.waikato.ac.nz/~fracpete/
http://www.data-mining.co.nz/
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