Paper 2026/660

QED-Lite: Lightweight Detection of Quantum-Vulnerable ELF Binaries via Cryptographic Library Version Fingerprinting

Abstract

The advancement of quantum computing poses a serious threat to widely-used public-key cryptographic systems, leaving organizations with the challenge of identifying quantum-vulnerable (QV) executables within their systems and migrating to post-quantum cryptography (PQC). The prior work QED achieves high detection precision through angr-based static call graph analysis (P3), but its processing time of a few to over ten minutes per dataset and RAM consumption of up to 5 GB pose practical limitations on exhaustive screening in largescale environments. In this paper, we propose QED-Lite, a lightweight approximation tool that lightens the analysis stages that incur high computational overhead relative to their detection precision, replacing them with version-based PQC support determination of cryptographic libraries. QED-Lite introduces a newly built PQC risk classification database for 11 major cryptographic libraries and is implemented with a single dependency on pyelftools. Experimental results on the Network dataset show that QED-Lite achieves an execution time up to 855× faster (0.84 seconds) and reduces memory usage by 228× (22.9 MB) compared to QED, while maintaining a TPR of 100%. QED-Lite delivers practical value relative to its cost as a first-pass screening tool that is operationally viable in large-scale organizational environments.