Chongqing Lei (Southeast University), Zhen Ling (Southeast University), Yue Zhang (Jinan University), Kai Dong (Southeast University), Kaizheng Liu (Southeast University), Junzhou Luo (Southeast University), Xinwen Fu (University of Massachusetts Lowell)

Android accessibility service was designed to assist individuals with disabilities in using Android devices. However, it has been exploited by attackers to steal user passwords due to design shortcomings. Google has implemented various countermeasures to make it difficult for these types of attacks to be successful on modern Android devices. In this paper, we present a new type of side channel attack called content queries (CONQUER) that can bypass these defenses. We discovered that Android does not prevent the content of passwords from being queried by the accessibility service, allowing malware with this service enabled to enumerate the combinations of content to brute force the password. While this attack seems simple to execute, there are several challenges that must be addressed in order to successfully launch it against real-world apps. These include the use of lazy query to differentiate targeted password strings, active query to determine the right timing for the attack, and timing- and state-based side channels to infer case-sensitive passwords. Our evaluation results demonstrate that the CONQUER attack is effective at stealing passwords, with an average one-time success rate of 64.91%. This attack also poses a threat to all Android versions from 4.1 to 12, and can be used against tens of thousands of apps. In addition, we analyzed the root cause of the CONQUER attack and discussed several countermeasures to mitigate the potential security risks it poses.

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 66 ) ) ) [post__not_in] => Array ( [0] => 13188 ) )

Detection and Resolution of Control Decision Anomalies

Prof. Kang Shin (Kevin and Nancy O'Connor Professor of Computer Science, and the Founding Director of the Real-Time Computing Laboratory (RTCL) in the Electrical Engineering and Computer Science Department at the University of Michigan)

Read More

I Still Know What You Watched Last Sunday: Privacy...

Carlotta Tagliaro (TU Wien), Florian Hahn (University of Twente), Riccardo Sepe (Guess Europe Sagl), Alessio Aceti (Sababa Security SpA), Martina Lindorfer (TU Wien)

Read More

He-HTLC: Revisiting Incentives in HTLC

Sarisht Wadhwa (Duke University), Jannis Stoeter (Duke University), Fan Zhang (Duke University, Yale University), Kartik Nayak (Duke University)

Read More

Ghost Domain Reloaded: Vulnerable Links in Domain Name Delegation...

Xiang Li (Tsinghua University), Baojun Liu (Tsinghua University), Xuesong Bai (University of California, Irvine), Mingming Zhang (Tsinghua University), Qifan Zhang (University of California, Irvine), Zhou Li (University of California, Irvine), Haixin Duan (Tsinghua University; QI-ANXIN Technology Research Institute; Zhongguancun Laboratory), Qi Li (Tsinghua University; Zhongguancun Laboratory)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)