This paper proposes a unified framework for analyzing side-channel key recovery attacks. The framework includes a theoretical model and application methodology to evaluate cryptographic implementations and adversaries. The model is based on hypotheses about side-channel leakages and allows quantifying the effect of leakage functions using information-theoretic and security metrics. These metrics measure the quality of an implementation and the strength of an adversary, respectively. Theoretical connections between these metrics are discussed, as well as their practical implications for analyzing side-channel attacks. The framework aims to provide a sound and systematic approach to evaluating implementations and adversaries, enabling more meaningful comparisons. The model is applied to various scenarios, including Gaussian leakage distributions, and is shown to be effective in capturing the impact of different leakage functions on the success of side-channel attacks. The paper also discusses the limitations of the model and the importance of combining information-theoretic and security metrics for a comprehensive evaluation of side-channel attacks. The framework is intended to bridge the gap between theoretical understanding and practical implementation in side-channel analysis.This paper proposes a unified framework for analyzing side-channel key recovery attacks. The framework includes a theoretical model and application methodology to evaluate cryptographic implementations and adversaries. The model is based on hypotheses about side-channel leakages and allows quantifying the effect of leakage functions using information-theoretic and security metrics. These metrics measure the quality of an implementation and the strength of an adversary, respectively. Theoretical connections between these metrics are discussed, as well as their practical implications for analyzing side-channel attacks. The framework aims to provide a sound and systematic approach to evaluating implementations and adversaries, enabling more meaningful comparisons. The model is applied to various scenarios, including Gaussian leakage distributions, and is shown to be effective in capturing the impact of different leakage functions on the success of side-channel attacks. The paper also discusses the limitations of the model and the importance of combining information-theoretic and security metrics for a comprehensive evaluation of side-channel attacks. The framework is intended to bridge the gap between theoretical understanding and practical implementation in side-channel analysis.