Lalaine: Measuring and Characterizing Non-Compliance of Apple Privacy Labels


Yue Xiao, Zhengyi Li, and Yue Qin, Indiana University Bloomington; Xiaolong Bai, Orion Security Lab, Alibaba Group; Jiale Guan, Xiaojing Liao, and Luyi Xing, Indiana University Bloomington


As a key supplement to privacy policies that are known to be lengthy and difficult to read, Apple has launched app privacy labels, which purportedly help users more easily understand an app's privacy practices. However, false and misleading privacy labels can dupe privacy-conscious consumers into downloading data-intensive apps, ultimately eroding the credibility and integrity of the labels. Although Apple releases requirements and guidelines for app developers to create privacy labels, little is known about whether and to what extent the privacy labels in the wild are correct and compliant, reflecting the actual data practices of iOS apps.

This paper presents the first systematic study, based on our new methodology named Lalaine, to evaluate data-flow to privacy-label flow-to-label consistency. Lalaine fully analyzed the privacy labels and binaries of 5,102 iOS apps, shedding lights on the prevalence and seriousness of privacy-label non-compliance. We provide detailed case studies and analyze root causes for privacy label non-compliance that complements prior understandings. This has led to new insights for improving privacy-label design and compliance requirements, so app developers, platform stakeholders, and policy-makers can better achieve their privacy and accountability goals. Lalaine is thoroughly evaluated for its high effectiveness and efficiency. We are responsibly reporting the results to stakeholders.

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

@inproceedings {287164,
author = {Yue Xiao and Zhengyi Li and Yue Qin and Xiaolong Bai and Jiale Guan and Xiaojing Liao and Luyi Xing},
title = {Lalaine: Measuring and Characterizing {Non-Compliance} of Apple Privacy Labels},
booktitle = {32nd USENIX Security Symposium (USENIX Security 23)},
year = {2023},
isbn = {978-1-939133-37-3},
address = {Anaheim, CA},
pages = {1091--1108},
url = {},
publisher = {USENIX Association},
month = aug

Presentation Video