Pith. sign in

REVIEW 1 cited by

CovFUZZ: Coverage-based fuzzer for 4G&5G protocols

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2410.20958 v1 pith:H2V4WEPD submitted 2024-10-28 cs.CR

classification cs.CR
keywords fuzzingcoveragefuzzerprobabilitiesframeworkrandomalgorithmcots
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

4G and 5G represent the current cellular communication standards utilized daily by billions of users for various applications. Consequently, ensuring the security of 4G and 5G network implementations is critically important. This paper introduces an automated fuzzing framework designed to test the security of 4G and 5G attach procedure implementations. Our framework provides a comprehensive solution for uplink and downlink fuzzing in 4G, as well as downlink fuzzing in 5G, while supporting fuzzing on all layers except the physical layer. To guide the fuzzing process, we introduce a novel algorithm that assigns probabilities to packet fields and adjusts these probabilities based on coverage information from the device-under-test (DUT). For cases where coverage information from the DUT is unavailable, we propose a novel methodology to estimate it. When evaluating our framework, we first run the random fuzzing experiments, where the mutation probabilities are fixed throughout the fuzzing, and give an insight into how those probabilities should be chosen to optimize the Random fuzzer to achieve the best coverage. Next, we evaluate the efficiency of the proposed coverage-based algorithms by fuzzing open-source 4G stack (srsRAN) instances and show that the fuzzer guided by our algorithm outperforms the optimized Random fuzzer in terms of DUT's code coverage. In addition, we run fuzzing tests on 12 commercial off-the-shelf (COTS) devices. In total, we discovered vulnerabilities in 10 COTS devices and all of the srsRAN 4G instances.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. AI5GTest: AI-Driven Specification-Aware Automated Testing and Validation of 5G O-RAN Components

    cs.NI 2025-06 conditional novelty 6.0 of 10

    An LLM-based framework that generates expected O-RAN and 3GPP procedural flows from standards and validates captured signaling logs against them, reporting 100% accuracy on 15 testbed instances and under an hour per t...

Pith tools