Improved Preimage Attack on One-block MD4

We propose an improved preimage attack on one-block MD4 with the time complexity $2^{94.98}$ MD4 compression function operations, as compared to $2^{107}$ in \cite{AokiS-sac08}. We research the attack procedure in \cite{AokiS-sac08} and formulate the complexity for computing a preimage attack on one-block MD4. We attain the result mainly through the following two aspects with the help of the complexity formula. First, we continue to compute two more steps backward to get two more chaining values for comparison during the meet-in-the-middle attack. Second, we search two more neutral words in one independent chunk, and then propose the multi-neutral-word partial-fixing technique to get more message freedom and skip ten steps for partial-fixing, as compared to previous four steps. We also use the initial structure technique and apply the same idea to improve the pseudo-preimage and preimage attacks on Extended MD4 with $2^{25.2}$ and $2^{12.6}$ improvement factor, as compared to previous attacks in \cite{SasakiA-acisp09}, respectively

Hash Gone Bad: Automated discovery of protocol attacks that exploit hash function weaknesses

Most cryptographic protocols use cryptographic hash functions as a building block. The security analyses of these protocols typically assume that the hash functions are perfect (such as in the random oracle model). However, in practice, most widely deployed hash functions are far from perfect -- and as a result, the analysis may miss attacks that exploit the gap between the model and the actual hash function used. We develop the first methodology to systematically discover attacks on security protocols that exploit weaknesses in widely deployed hash functions. We achieve this by revisiting the gap between theoretical properties of hash functions and the weaknesses of real-world hash functions, from which we develop a lattice of threat models. For all of these threat models, we develop fine-grained symbolic models. Our methodology's fine-grained models cannot be directly encoded in existing state-of-the-art analysis tools by just using their equational reasoning. We therefore develop extensions for the two leading tools, Tamarin and Proverif. In extensive case studies using our methodology, the extended tools rediscover all attacks that were previously reported for these protocols and discover several new variants