Optimized Password Recovery for Encrypted RAR on GPUs

TL;DR

This paper presents a GPU-accelerated approach to significantly speed up password recovery for encrypted RAR files by optimizing SHA-1 hashing computations with coarse-grained parallelism and other techniques.

Contribution

It introduces a GPU-based brute-force password recovery method for RAR encryption, employing specific optimizations to overcome SHA-1 parallelization challenges.

Findings

Achieved 43-57x speedup over CPU implementation

Optimized GPU parallelization with asynchronous CPU-GPU execution

Effective reduction of redundant calculations and register usage

Abstract

RAR uses classic symmetric encryption algorithm SHA-1 hashing and AES algorithm for encryption, and the only method of password recovery is brute force, which is very time-consuming. In this paper, we present an approach using GPUs to speed up the password recovery process. However, because the major calculation and time-consuming part, SHA-1 hashing, is hard to be parallelized, so this paper adopts coarse granularity parallel. That is, one GPU thread is responsible for the validation of one password. We mainly use three optimization methods to optimize this parallel version: asynchronous parallel between CPU and GPU, redundant calculations and conditional statements reduction, and the usage of registers optimization. Experiment result shows that the final version reaches 43~57 times speedup on an AMD FirePro W8000 GPU, compared to a well-optimized serial version on Intel Core i5 CPU.