International Association
for Cryptologic Research

Differential Fault Analysis (DFA) is considered as the most popular fault analysis method. While there are techniques that provide a fault analysis automation on the cipher level to some degree, it can be shown that when it comes to software implementations, there are new vulnerabilities, which cannot be found by observing the cipher design specification.This work bridges the gap by providing a fully automated way to carry out DFA on assembly implementations of symmetric block ciphers. We use a customized data flow graph to represent the program and develop a novel fault analysis methodology to capture the program behavior under faults. We establish an effective description of DFA as constraints that are passed to an SMT solver. We create a tool that takes assembly code as input, analyzes the dependencies among instructions, automatically attacks vulnerable instructions using SMT solver and outputs the attack details that recover the last round key (and possibly the earlier keys). We support our design with evaluations on lightweight ciphers SIMON, SPECK, and PRIDE, and a current NIST standard, AES. By automated assembly analysis, we were able to find new efficient DFA attacks on SPECK and PRIDE, exploiting implementation specific vulnerabilities, and previously published DFA on SIMON and AES. Moreover, we present a novel DFA on multiplication operation that has never been shown for symmetric block ciphers before. Our experimental evaluation also shows reasonable execution times that are scalable to current cipher designs and can easily outclass the manual analysis. Moreover, we present a method to check the countermeasure-protected implementations in a way that helps implementers to decide how many rounds should be protected. We note that this is the first work that automatically carries out DFA on cipher implementations without any plaintext or ciphertext information and therefore, can be generally applied to any input data to the cipher.

Over the past decades, fault injection attacks have been extensively studied due to their capability to efficiently break cryptographic implementations. Fault injection attack models are normally determined by analyzing the cipher structure and finding exploitable spots in non-linear and permutation layers. However, this level of abstraction is often too high to distinguish vulnerable parts of software implementations, due to specific operations and optimizations. On the other hand, manually analyzing the assembly code requires non-negligible amount of time and expertise. In this paper, we propose an automated approach for analyzing cipher implementations in assembly. We represent the whole assembly program as a data flow graph so that the vulnerable spots can be found efficiently. Fault propagation is analyzed in a subgraph constructed from each vulnerable spot, allowing equations for Differential Fault Analysis (DFA) to be automatically generated. We have created a tool that implements our approach: DATAC – DFA Automation Tool for Assembly Code. We have successfully used this tool for attacking PRESENT- 80, being able to find implementation-specific vulnerabilities that can be exploited in order to recover the last round key with 16 faults. Our results show that DATAC is useful in finding attack spots that are not visible from the cipher structure, but can be easily exploited when dealing with real-world implementations.