Victor Duta (Vrije Universiteit Amsterdam), Fabian Freyer (University of California San Diego), Fabio Pagani (University of California, Santa Barbara), Marius Muench (Vrije Universiteit Amsterdam), Cristiano Giuffrida (Vrije Universiteit Amsterdam)

Backward-edge control-flow hijacking via stack buffer overflow is the holy grail of software exploitation. The ability to directly control critical stack data and the hijacked target makes this exploitation strategy particularly appealing for attackers. As a result, the community has deployed strong backward-edge protections such as shadow stacks or stack canaries, forcing attackers to resort to less ideal e.g., heap-based exploitation strategies. However, such mitigations commonly rely on one key assumption, namely an attacker relying on return address corruption to directly hijack control flow upon function return.

In this paper, we present *exceptions* to this assumption and show attacks based on backward-edge control-flow hijacking *without* the direct hijacking are possible. Specifically, we demonstrate that stack corruption can cause exception handling to act as a *confused deputy* and mount backward-edge control-flow hijacking attacks on the attacker’s behalf. This strategy provides overlooked opportunities to divert execution to attacker-controlled catch handlers (a paradigm we term Catch Handler Oriented Programming or CHOP) and craft powerful primitives such as arbitrary code execution or arbitrary memory writes. We find CHOP-style attacks to work across multiple platforms (Linux, Windows, macOS, Android and iOS). To analyze the uncovered attack surface, we survey popular open-source packages and study the applicability of the proposed exploitation techniques. Our analysis shows that suitable exception handling targets are ubiquitous in C++ programs and exploitable exception handlers are common. We conclude by presenting three end-to-end exploits on real-world software and proposing changes to deployed mitigations to address CHOP.

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Tianxi Ji (Texas Tech University), Erman Ayday (Case Western Reserve University), Emre Yilmaz (University of Houston-Downtown), Ming Li (CSE Department The University of Texas at Arlington), Pan Li (Case Western Reserve University)

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Shady Mansour (LMU Munich), Pascal Knierim (Universitat Innsbruck), Joseph O’Hagan (University of Glasgow), Florian Alt (University of the Bundeswehr Munich), Florian Mathis (University of Glasgow)

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Jacob Abbott (Indiana University), Jayati Dev (Indiana University), DongInn Kim (Indiana University), Shakthidhar Reddy Gopavaram (Indiana University), Meera Iyer (Indiana University), Shivani Sadam (Indiana University) , Shirang Mare (Western Washington University), Tatiana Ringenberg (Purdue University), Vafa Andalibi (Indiana University), and L. Jean Camp(Indiana University)

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RAI2: Responsible Identity Audit Governing the Artificial Intelligence

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

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