Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 1905.09352

Hey Google, What Exactly Do Your Security Patches Tell Us? A Large-Scale Empirical Study on Android Patched Vulnerabilities

Sadegh Farhang·Mehmet Bahadir Kirdan·Aron Laszka·Jens Grossklags
View original source ↗Read source document ↗Export metadata ↓

Abstract

In this paper, we perform a comprehensive study of 2,470 patched Android vulnerabilities that we collect from different data sources such as Android security bulletins, CVEDetails, Qualcomm Code Aurora, AOSP Git repository, and Linux Patchwork. In our data analysis, we focus on determining the affected layers, OS versions, severity levels, and common weakness enumerations (CWE) associated with the patched vulnerabilities. Further, we assess the timeline of each vulnerability, including discovery and patch dates. We find that (i) even though the number of patched vulnerabilities changes considerably from month to month, the relative number of patched vulnerabilities for each severity level remains stable over time, (ii) there is a significant delay in patching vulnerabilities that originate from the Linux community or concern Qualcomm components, even though Linux and Qualcomm provide and release their own patches earlier, (iii) different AOSP versions receive security updates for different periods of time, (iv) for 94% of patched Android vulnerabilities, the date of disclosure in public datasets is not before the patch release date, (v) there exist some inconsistencies among public vulnerability data sources, e.g., some CVE IDs are listed in Android Security bulletins with detailed information, but in CVEDetails they are listed as unknown, (vi) many patched vulnerabilities for newer Android versions likely also affect older versions that do not receive security patches due to end-of-life.

Explore related subjects

cs.CR

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sadegh Farhang, Mehmet Bahadir Kirdan, Aron Laszka, Jens Grossklags. 2019-05-22. Hey Google, What Exactly Do Your Security Patches Tell Us? A Large-Scale Empirical Study on Android Patched Vulnerabilities. https://arxiv.org/abs/1905.09352

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

MIRANDA: short signatures from a leakage-free full-domain-hash scheme

We present $\mathsf{Miranda}$, the first family of full-domain-hash signatures based on matrix codes. This signature scheme fulfils the paradigm of Gentry, Peikert and Vaikuntanathan ($\mathsf{GPV}$), which gives strong security guarantees. Our trapdoor is very simple and generic: if we propose it with matrix codes, it can actually be instantiated in many other ways since it only involves a subcode of a decodable code (or lattice) in a unique decoding regime of parameters. Though $\mathsf{Miranda}$ signing algorithm relies on a decoding task where there is exactly one solution, there are many possible signatures given a message to sign and we ensure that signatures are not leaking information on their underlying trapdoor by means of a very simple procedure involving the drawing of a small number of uniform bits. In particular $\mathsf{Miranda}$ does not use a rejection sampling procedure which makes its implementation a very simple task contrary to other $\mathsf{GPV}$-like signatures schemes such as $\mathsf{Falcon}$ or even $\mathsf{Wave}$. We instantiate $\mathsf{Miranda}$ with the famous family of Gabidulin codes represented as spaces of matrices and we study thoroughly its security (in the EUF-CMA security model). For~$128$ bits of classical security, the signature sizes are as low as~$90$ bytes and the public key sizes are in the order of~$2.6$ megabytes.

cs.CR↗
arXiv2026

SteganoBackdoor: Evading Data-Poisoning Defenses via Steganographic Backdoors

Transformer-based models are highly susceptible to backdoor attacks via supervised fine-tuning (SFT). To red-team existing data-poisoning defenses, prior work has increasingly focused on stylized triggers, synthetic artifacts, and token-level perturbations designed to evade detection. However, this trend has shifted threat models away from naturally occurring semantic triggers and realistic low-budget poisoning settings. Addressing this gap, we introduce SteganoBackdoor, an optimization-based framework that transforms semantic-trigger seeds through autoregressive token replacement, sequentially minimizing embedding overlap with the inference-time trigger while preserving a strong per-sample training-time payload. The resulting SteganoPoisons maintain linguistic fluency and encode the payload across ordinary tokens, such that no individual token carries a concentrated signal and the full payload instead emerges from their exact combination and ordering. Across 18 encoder-based and decoder-only models spanning 120M to 14B parameters, SteganoBackdoor achieves high attack success under sub-percent poisoning budgets and exposes limitations in existing data-poisoning defenses.

cs.CR↗
arXiv2026

Foundations and Design Principles of Lightweight Cryptography for IoT Systems

The successful deployment of the Internet of Things (IoT) applications relies heavily on their robust security, and lightweight cryptography is considered an emerging solution in this context. While existing surveys have been examining lightweight cryptographic techniques from the perspective of hardware and software implementations or performance evaluation, there is a significant gap in addressing different security aspects, such as design principles, specific to the IoT environment. This study aims to bridge this gap. This research presents an examination with focusing on the security evaluation of symmetric lightweight ciphers commonly used in IoT systems. The objective of this study is to provide a concise overview of lightweight ciphers with emphasizing on their security challenges which is an essential consideration for real-time and resource-constrained applications.

cs.CR↗