Working at the intersection of computer security and program analysis, our lab is actively developing systems and techniques for assuring software security. Our research interests include automatic reverse engineering, exploit verification, malware analysis, fuzzing, and symbolic execution. We use the following approaches:

  1. We analyze programs to find vulnerabilities.
  2. We study offensive hacking techniques in order to develop defensive mechanisms.
  3. We engineer software systems that are secure and reliable.

News

Sep. 2024

Received ACM Distinguished Paper Award in ISSTA 2024!

Hyungseok Kim, Soomin Kim, Jungwoo Lee, and Sang Kil Cha
In Proceedings of the International Symposium on Software Testing and Analysis, 2024

See this.

Jul. 2024

Our work will appear in ISSTA 2024

AsFuzzer: Differential Testing of Assemblers with Error-Driven Grammar Inference

Hyungseok Kim, Soomin Kim, Jungwoo Lee, and Sang Kil Cha
In Proceedings of the International Symposium on Software Testing and Analysis, 2024

Jun. 2024

Our work will appear in Black Hat USA 2024

PyLingual: A Python Decompilation Framework for Evolving Python Versions

Josh Wiedemeier, Elliot Tarbet, Max Zheng, Jerry Teng, Ximeng Liu, Muhyun Kim, Sang Kil Cha, Jessica Ouyang, and Kangkook Jee
In Proceedings of the Black Hat USA, 2024
A free online service is available at https://pylingual.io

Jun. 2024

Jung Hyun will present a poster in SVCC 2024

PoE: A Domain-Specific Language for Exploitation

Jung Hyun Kim, Steve Gustaman, and Sang Kil Cha
In Proceedings of the Silicon Valley Cybersecurity Conference, 2024

May. 2024

A paper will appear in FSE 2024

Evaluating Directed Fuzzers: Are We Heading in the Right Direction?

Tae Eun Kim, Jaeseung Choi, Seongjae Im, Kihong Heo, and Sang Kil Cha
In Proceedings of the International Symposium on Foundations of Software Engineering, 2024

Nov. 2023

A paper will appear in APSEC 2023

On the Effectiveness of Synthetic Benchmarks for Evaluating Directed Grey-box Fuzzers

Haeun Lee, Hee Dong Yang, Su Geun Ji, and Sang Kil Cha
In Proceedings of the Asia-Pacific Software Engineering Conference, 2023

Oct. 2023

An article will appear in CACM

Boosting Fuzzer Efficiency: An Information Theoretic Perspective

Marcel Böhme, Valentin Jean Marie Manès, and Sang Kil Cha
CACM, Volume 66, Issue 11, Nov. 2023

Aug. 2023

A paper will appear in FSE 2023

FunProbe: Probing Functions from Binary Code through Probabilistic Analysis

Soomin Kim, Hyungseok Kim, and Sang Kil Cha
In Proceedings of the International Symposium on Foundations of Software Engineering, 2023


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People

Sang Kil Cha
Professor
[homepage]

Ph.D. Students

Soomin Kim
Ph.D. Student
[homepage]
JungHyun Kim
Ph.D. Student
[homepage]

Master Students

Sanghyun Park
Master Student
Jungwoo Lee
Master Student
[homepage]
Steve Gustaman
Master Student
Geonwoo Park
Master Student
Daeseok Kim
Master Student
Junhak Lee
Master Student
Sangjun Park
Master Student
[homepage]
Sehoon Kim
Master Student
Zunnoor Awan
Master Student

Former Ph.D. Students

Publications

You may access a complete list of publications on DBLP: [link], Google Scholar: [link].

Contact

KAIST N5 #2310
291 Daehak-ro, Yuseong-gu
Daejeon 34141
South Korea