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Raphael Isemann

dblp:232/2018 · DBLP profile ↗
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4ranked-venue papers
1as first author
4since 2021 · last 2025
0009-0002-6224-9795ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 3 · 3 since 2021Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
4 papers
Systems and software security · 64% Hardware security and side channels · 20% Privacy and data protection · 16%
Software engineering, system software, and programming languages
2 papers
Software testing · 36% Program analysis · 23% Concurrent programming · 23%
Computer architecture, parallel and distributed computing, and storage systems
2 papers
Electronic design automation · 90% Integrated circuit design · 10%

Topics — the 16 heaviest of 16, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Privacy and data protection › information leakage
data leakage detection
0.912025
Phantom Trails: Practical Pre-Silicon Discovery of Transient Data Leaks · USENIX Security Symposium 2025
Systems and software security
operating system security
0.912025
Dynamic Detection of Vulnerable DMA Race Conditions · CCS 2025
Hardware security and side channels › microarchitectural attacks
transient execution attack
0.912025
Phantom Trails: Practical Pre-Silicon Discovery of Transient Data Leaks · USENIX Security Symposium 2025
Concurrent programming › concurrency bug detection
data race detection
0.912025
Dynamic Detection of Vulnerable DMA Race Conditions · CCS 2025
Program analysis
dynamic analysis
0.912025
Dynamic Detection of Vulnerable DMA Race Conditions · CCS 2025
Electronic design automation
hardware verification and test
0.912025
Phantom Trails: Practical Pre-Silicon Discovery of Transient Data Leaks · USENIX Security Symposium 2025
Electronic design automation › hardware verification and test › functional verification
pre-silicon verification
0.912025
Phantom Trails: Practical Pre-Silicon Discovery of Transient Data Leaks · USENIX Security Symposium 2025
Systems and software security › memory safety
memory error detection
0.712023
FloatZone: Accelerating Memory Error Detection using the Floating Point Unit · USENIX Security Symposium 2023
Systems and software security
memory safety
0.712023
FloatZone: Accelerating Memory Error Detection using the Floating Point Unit · USENIX Security Symposium 2023
Systems and software security › program analysis
undefined behavior detection
0.712023
Don't Look UB: Exposing Sanitizer-Eliding Compiler Optimizations · Proc. ACM Program. Lang. 2023
Systems and software security
vulnerability discovery
0.712023
Don't Look UB: Exposing Sanitizer-Eliding Compiler Optimizations · Proc. ACM Program. Lang. 2023
Compilers and program optimization › compiler correctness
compiler optimization correctness
0.712023
Don't Look UB: Exposing Sanitizer-Eliding Compiler Optimizations · Proc. ACM Program. Lang. 2023
Software testing
compiler testing
0.712023
Don't Look UB: Exposing Sanitizer-Eliding Compiler Optimizations · Proc. ACM Program. Lang. 2023
Software testing
differential testing
0.712023
Don't Look UB: Exposing Sanitizer-Eliding Compiler Optimizations · Proc. ACM Program. Lang. 2023
Hardware security and side channels › hardware attacks
DMA attacks
0.312025
Dynamic Detection of Vulnerable DMA Race Conditions · CCS 2025
Integrated circuit design › digital circuit design › arithmetic circuit design
floating-point unit
0.212023
FloatZone: Accelerating Memory Error Detection using the Floating Point Unit · USENIX Security Symposium 2023

Methods — techniques the papers use, named apart from their topics

taint tracking · 1.7information flow tracking · 1.7dynamic analysis · 1.7static analysis · 1.3fuzzing · 1.3
YearPublicationVenuePosition
2025 Dynamic Detection of Vulnerable DMA Race Conditions
abstract
The drivers of modern operating systems use Direct Memory Access (DMA) to efficiently communicate with peripheral devices. Since the memory accessed by DMA is a shared resource between driver and device, it is a possible source of race conditions. Peripheral devices are also often untrusted, so these race conditions open up a new potential attack vector against a trusted OS kernel. In this paper, we present DMARacer, a dynamic detector called for these DMA-based race conditions in kernel code. DMARacer tracks memory accesses to DMA memory throughout the kernel's lifetime and analyses them for various indicators of race conditions. Additionally, upon detecting a race condition, DMARacer uses taint tracking to trace its impact and identify any potential vulnerabilities it may trigger, such as memory corruption or denial-of-service. We used DMARacer to search the drivers of the Linux kernel for DMA-based errors and find that DMA-based race conditions are a systemic issue in driver code. In total, DMARacer was able to detect 817 problematic memory accesses and 344 vulnerable operations in the scanned Linux kernel drivers.
Brian Johannesmeyer, Raphael Isemann, Cristiano Giuffrida, Herbert Bos
CCS2
2025 Phantom Trails: Practical Pre-Silicon Discovery of Transient Data Leaks
Alvise de Faveri Tron, Raphael Isemann, Hany Ragab, Cristiano Giuffrida, Klaus von Gleissenthall, Herbert Bos
USENIX Security Symposium2
2023 FloatZone: Accelerating Memory Error Detection using the Floating Point Unit
Floris Gorter, Enrico Barberis, Raphael Isemann, Erik van der Kouwe, Cristiano Giuffrida, Herbert Bos
USENIX Security Symposium3
2023 Don't Look UB: Exposing Sanitizer-Eliding Compiler Optimizations
abstract
Sanitizers are widely used compiler features that detect undefined behavior and resulting vulnerabilities by injecting runtime checks into programs. For better performance, sanitizers are often used in conjunction with optimization passes. But doing so combines two compiler features with conflicting objectives. While sanitizers want to expose undefined behavior, optimizers often exploit these same properties for performance. In this paper, we show that this clash can have serious consequences: optimizations can remove sanitizer failures, thereby hiding the presence of bugs or even introducing new ones. We present LookUB, a differential-testing based framework for finding optimizer transformations that elide sanitizer failures. We used our method to find 17 such sanitizer-eliding optimizations in Clang. Next, we used static analysis and fuzzing to search for bugs in open-source projects that were previously hidden due to sanitizer-eliding optimizations. This led us to discover 20 new bugs in Linux Containers, libmpeg2, NTFS-3G, and WINE. Finally, we present an effective mitigation strategy based on a customization of the Clang optimizer with an overhead increase of 4%.
Raphael Isemann, Cristiano Giuffrida, Herbert Bos, Erik van der Kouwe, Klaus von Gleissenthall
Proc. ACM Program. Lang.1