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IEEE Transactions on Reliability
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IEEE Transactions on Reliability
Article . 2018 . Peer-reviewed
License: IEEE Copyright
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Finding Bugs in Cryptographic Hash Function Implementations

Authors: Nicky Mouha; Mohammad S. Raunak; D. Richard Kuhn; Raghu Kacker;

Finding Bugs in Cryptographic Hash Function Implementations

Abstract

Cryptographic hash functions are security-critical algorithms with many practical applications, notably in digital signatures. Developing an approach to test them can be particularly difficult, and bugs can remain unnoticed for many years. We revisit the NIST hash function competition, which was used to develop the SHA-3 standard, and apply a new testing strategy to all available reference implementations. Motivated by the cryptographic properties that a hash function should satisfy, we develop four tests. The Bit-Contribution Test checks if changes in the message affect the hash value, and the Bit-Exclusion Test checks that changes beyond the last message bit leave the hash value unchanged. We develop the Update Test to verify that messages are processed correctly in chunks, and then use combinatorial testing methods to reduce the test set size by several orders of magnitude while retaining the same fault-detection capability. Our tests detect bugs in 41 of the 86 reference implementations submitted to the SHA-3 competition, including the rediscovery of a bug in all submitted implementations of the SHA-3 finalist BLAKE. This bug remained undiscovered for seven years, and is particularly serious because it provides a simple strategy to modify the message without changing the hash value returned by the implementation. We detect these bugs using a fully-automated testing approach.

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    35
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
35
Top 10%
Top 10%
Top 10%
hybrid