BaseSAFE: Baseband SAnitized Fuzzing through Emulation
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Abstract (arXiv)
Rogue base stations are an effective attack vector. Cellular basebands represent a critical part of the smartphone's security: they parse large amounts of data even before authentication. They can, therefore, grant an attacker a very stealthy way to gather information about calls placed and even to escalate to the main operating system, over-the-air. In this paper, we discuss a novel cellular fuzzing framework that aims to help security researchers find critical bugs in cellular basebands and similar embedded systems. BaseSAFE allows partial rehosting of cellular basebands for fast instrumented fuzzing off-device, even for closed-source firmware blobs. BaseSAFE's sanitizing drop-in allocator, enables spotting heap-based buffer-overflows quickly. Using our proof-of-concept harness, we fuzzed various parsers of the Nucleus RTOS-based MediaTek cellular baseband that are accessible from rogue base stations. The emulator instrumentation is highly optimized, reaching hundreds of executions per second on each core for our complex test case, around 15k test-cases per second in total. Furthermore, we discuss attack vectors for baseband modems. To the best of our knowledge, this is the first use of emulation-based fuzzing for security testing of commercial cellular basebands. Most of the tooling and approaches of BaseSAFE are also applicable for other low-level kernels and firmware. Using BaseSAFE, we were able to find memory corruptions including heap out-of-bounds writes using our proof-of-concept fuzzing harness in the MediaTek cellular baseband. BaseSAFE, the harness, and a large collection of LTE signaling message test cases will be released open-source upon publication of this paper.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 May 2020.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 0; 2026: 1.
3 papers.
- 2023Hermes: Unlocking Security Analysis of Cellular Network Protocols by Synthesizing Finite State Machines from Natural Language Specificationscited by 4
- 2024CellularLint: A Systematic Approach to Identify Inconsistent Behavior in Cellular Network Specificationscited by 3
- 2026Understanding Implicit Trust Errors in Core Carrier Networks through Multi-Agent Flaw Discovery and Analysiscited by 0
- 2026Understanding Implicit Trust Errors in Core Carrier Networks through Multi-Agent Flaw Discovery and Analysis11 Jul 2026
- 2024CellularLint: A Systematic Approach to Identify Inconsistent Behavior in Cellular Network Specifications18 Jul 2024
- 2023Hermes: Unlocking Security Analysis of Cellular Network Protocols by Synthesizing Finite State Machines from Natural Language Specifications6 Oct 2023