DALC-CT: Dynamic Analysis of Low-Level Code Traces for Constant-Time Verification

2026-04-18

AI Summary

Existing constant-time verification approaches either fail to accurately capture real-world execution behavior or are highly susceptible to environmental noise. This work proposes a lightweight, reliable, and hardware-agnostic dynamic analysis method that assesses constant-time compliance by comparing the consistency of instruction-mix distributions derived from low-level instruction traces of binary programs executed under varying secret inputs. By leveraging logical execution analysis, the approach effectively mitigates noise interference and precisely captures actual program behavior. Evaluated on multiple benchmarks comprising both known correct and non-constant-time implementations, the method achieves a 100% detection rate, demonstrating its effectiveness and robustness.

Technology Category

• Machine Learning: Evaluation and Analysis
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust

Application Category

• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

Timing side-channel attacks exploit variations in program execution time to recover sensitive information. Cryptographic implementations are especially vulnerable to these attacks, since even small timing differences in operations such as modular exponentiation or key comparisons can be exploited to extract highly sensitive information, such as secret keys. To mitigate this threat, implementations of programs that handle sensitive information are often expected to adhere to constant-time principles, ensuring that execution behavior does not depend on secret inputs. However, validating the constant-time property of programs remains a major challenge in cryptography development. Formal method approaches to verify constant-time implementations rely on abstractions that often fail to capture real execution behavior, while timing-based measurement techniques are highly sensitive to noise from other programs and even hardware environments. In this work, we propose a novel approach for verifying constant-time programs based on dynamic analysis of low-level execution traces. Our method measures instruction sequences across multiple input values for any given binary and targeted function. Any variations in the instruction mix distribution for any given pair of traces indicate a deviation from the constant-time principle and behavior. We developed an open-source tool called DALC-CT, for the constant-time verification of programs using this approach. We evaluated it on a set of well-known constant-time and non-constant-time examples, achieving a perfect detection of issues. Our results demonstrate that analyzing the logical execution of programs via instruction trace comparisons provides a lightweight and reliable way to verify the constant-time property of programs.

Problem

• constant-time
• timing side-channel attacks
• verification
• low-level code traces
• cryptographic implementations

Innovation

• constant-time verification
• dynamic analysis
• low-level code traces
• timing side-channel
• instruction trace comparison