R. Sekar’s research while affiliated with Stony Brook University and other places

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Publications (4)


Scalable, Sound, and Accurate Jump Table Analysis
  • Conference Paper

September 2024

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11 Reads

Huan Nguyen

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R. Sekar



Citations (3)


... By contrast, DISASLLM also computes such probability but DISASLLM relies on LLM-based approach instead of any heuristic. The disassembler of SAFER [59] also leverages a probability-based approach combined with static analysis using a prioritized error correction algorithm. XDA [57] pretrained an encoder transformer with dataset of byte sequences in the compiled binaries, using masked token prediction as the training objective, which was then fine-tuned for instruction address identification. ...

Reference:

Disassembling Obfuscated Executables with LLM
Accurate Disassembly of Complex Binaries Without Use of Compiler Metadata
  • Citing Conference Paper
  • February 2024

... In addition to proprietary software that may only be available in binary form, most Linux software is distributed in binary form, thus making binary instrumentation very attractive even for opensource software. These factors have prompted a great deal of research in binary analysis and instrumentation techniques in recent years [3,5,12,14,17,29,41,50,51,54,55,57,58,62]. ...

Practical Fine-Grained Binary Code Randomization†
  • Citing Conference Paper
  • December 2020

... Many prior works [15,19,21,31] rely on additional compiler-generated information that is unavailable in stripped binaries, such as the symbol table. Recent works have shown [37,40] that exception-handling metadata can be used to accurately identify functions. Many tools such as GHIDRA [44] and JIMA [2] also rely on exception-handling metadata. ...

On the Impact of Exception Handling Compatibility on Binary Instrumentation
  • Citing Conference Paper
  • November 2020