Ammar Askar (Georgia Institute of Technology), Fabian Fleischer (Georgia Institute of Technology), Christopher Kruegel (University of California, Santa Barbara), Giovanni Vigna (University of California, Santa Barbara), Taesoo Kim (Georgia Institute of Technology)

Intents are the primary message-passing mechanism on Android, used for both communication between intra-app and inter-app components. Intents go across the trust boundary of applications and can break the security isolation between them. Due to their shared API with intra-app communication, apps may unintentionally expose functionality leading to important security bugs. MALintent is an open-source fuzzing framework that uses novel coverage instrumentation techniques and customizable bug oracles to find security issues in Android Intent handlers. MALintent is the first Intent fuzzer that applies greybox fuzzing on compiled closed-source Android applications. We demonstrate techniques widely compatible with many versions of Android and our bug oracles were able to find several crashes, vulnerabilities with privacy implications, and memory-safety issues in the top-downloaded Android applications on the Google Play store.

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The Philosopher’s Stone: Trojaning Plugins of Large Language Models

Tian Dong (Shanghai Jiao Tong University), Minhui Xue (CSIRO's Data61), Guoxing Chen (Shanghai Jiao Tong University), Rayne Holland (CSIRO's Data61), Yan Meng (Shanghai Jiao Tong University), Shaofeng Li (Southeast University), Zhen Liu (Shanghai Jiao Tong University), Haojin Zhu (Shanghai Jiao Tong University)

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Rediscovering Method Confusion in Proposed Security Fixes for Bluetooth

Maximilian von Tschirschnitz (Technical University of Munich), Ludwig Peuckert (Technical University of Munich), Moritz Buhl (Technical University of Munich), Jens Grossklags (Technical University of Munich)

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LAMP: Lightweight Approaches for Latency Minimization in Mixnets with...

Mahdi Rahimi (KU Leuven), Piyush Kumar Sharma (University of Michigan), Claudia Diaz (KU Leuven)

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Non-intrusive and Unconstrained Keystroke Inference in VR Platforms via...

Tao Ni (City University of Hong Kong), Yuefeng Du (City University of Hong Kong), Qingchuan Zhao (City University of Hong Kong), Cong Wang (City University of Hong Kong)

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