International Association
for Cryptologic Research

Side-channel analysis is a powerful technique to extract secret data from cryptographic devices. However, this task heavily relies on experts and specialized tools, particularly in the case of simple power analysis (SPA). Meanwhile, ChatGPT, a leading example of large language models, has attracted great attention and been widely applied for assisting users with complex tasks. Despite this, ChatGPT’s capabilities for fully automated SPA, where prompts and traces are input only once, have yet to be systematically explored and improved. In this paper, we introduce a novel prompt template with three expert strategies and conduct a large-scale evaluation of ChatGPT’s capabilities for SPA. We establish a dataset comprising seven sets of real power traces from various implementations of public-key cryptosystems, including RSA, ECC, and Kyber, as well as eighteen sets of simulated power traces that illustrate typical SPA leakage patterns. The results indicate that ChatGPT fails to be directly used for SPA. However, by applying the expert strategies, we successfully recovered the private keys for all twenty-five traces, which demonstrate that non-experts can use ChatGPT with our expert strategies to perform fully automated SPA.