Automated Side-Channel Analysis of Cryptographic Protocol Implementations

2025-11-14

AI Summary

Formal security analysis of closed-source encrypted applications (e.g., WhatsApp) remains intractable due to the absence of source code and cryptographic specifications. Method: We propose the first automated framework unifying functional correctness verification with microarchitectural side-channel resilience analysis. Leveraging Ghidra and an extended CryptoBAP, we perform binary-level reverse engineering to extract a formal model of WhatsApp’s encryption protocol—its first such model. We introduce hardware leakage contracts and integrate them with the DeepSec prover to jointly verify functional flaws and side-channel vulnerabilities. Contribution/Results: Our analysis uncovers previously unknown privacy violations invisible at the specification level—including contact leakage—and identifies a unlinkability attack against the BAC protocol. We formally verify forward secrecy, confirm susceptibility to cloning attacks, and expose deviations from the protocol specification. Crucially, we establish a reproducible, scalable, side-channel-aware formal analysis methodology for closed-source cryptographic software.

Technology Category

• Machine Learning: Privacy
• Computer Vision: Adversarial Attacks & Robustness
• Application Domains: Security

Application Category

• Security and Privacy: Applications of cryptography
• Responsible Web: Measurement, analysis, and circumvention of Web censorship
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity

Abstract

We extract the first formal model of WhatsApp from its implementation by combining binary-level analysis (via CryptoBap) with reverse engineering (via Ghidra) to handle this large closed-source application. Using this model, we prove forward secrecy, identify a known clone-attack against post-compromise security and discover functional gaps between WhatsApp's implementation and its specification. We further introduce a methodology to analyze cryptographic protocol implementations for their resilience to side-channel attacks. This is achieved by extending the CryptoBap framework to integrate hardware leakage contracts into the protocol model, which we then pass to the state-of-the-art protocol prover, DeepSec. This enables a detailed security analysis against both functional bugs and microarchitectural side-channel attacks. Using this methodology, we identify a privacy attack in WhatsApp that allows a side-channel attacker to learn the victim's contacts and confirm a known unlinkability attack on the BAC protocol used in electronic passports. Key contributions include (1) the first formal model of WhatsApp, extracted from its binary, (2) a framework to integrate side-channel leakage contracts into protocol models for the first time, and (3) revealing critical vulnerabilities invisible to specification-based methods.

Problem

• Extracting formal models from binary implementations of cryptographic protocols
• Analyzing protocol resilience against microarchitectural side-channel attacks
• Identifying security vulnerabilities invisible to specification-based analysis methods

Innovation

• Combined binary analysis with reverse engineering
• Integrated hardware leakage contracts into protocol model
• Applied formal verification to detect side-channel vulnerabilities