.rodata · NUL-terminated strings · hover a byte to light its character
Yiyue Zhang
I take software apart to find out what it actually does — not what its source claims.
Integrated M.S.–Ph.D. student at SecAI Lab, Sungkyunkwan University. Binary analysis and reverse engineering.
.shstrtab
$ readelf -SW yiyue
| [Nr] | Name | Type | Address | Off | Size | Flg |
|---|---|---|---|---|---|---|
| [ 6] | .dynsym | DYNSYM | 00000000000003c0 | 0003c0 | 0000f0 | A |
| [11] | .plt | PROGBITS | 0000000000001020 | 001020 | 000030 | AX |
| [13] | .text | PROGBITS | 0000000000001060 | 001060 | 0003a2 | AX |
| [15] | .rodata | PROGBITS | 0000000000002000 | 002000 | 0000b8 | A |
| [16] | .note | NOTE | 00000000000020b8 | 0020b8 | 000048 | A |
| [19] | .init_array | INIT_ARRAY | 0000000000003d90 | 002d90 | 000018 | WA |
| [25] | .comment | PROGBITS | 0000000000000000 | 003032 | 00002b | MS |
.comment
who produced this
About
I'm an integrated M.S.–Ph.D. student in the Department of Software at Sungkyunkwan University, working in SecAI Lab under Prof. Hyungjoon (Kevin) Koo. I joined the lab in Fall 2024 and begin the Ph.D. stage in September 2026.
Most of what I do involves reading code that was never meant to be read: stripped binaries, aggressively optimized builds, deliberately obfuscated targets. I'm interested in the seam where automated analysis gives up and someone still has to sit down with a disassembler — and in how much of that gap we can actually close.
.text
what actually executes
Research
SecAI Lab studies practical security across both offensive and defensive dimensions — understanding attacks such as code injection and code reuse, designing defenses such as attack surface reduction and moving target defense, and examining security-relevant artifacts. To reason about code semantics, the lab works through the stages an executable binary passes through:
- code generation
transforming high-level source into machine code
- obfuscation
techniques that deliberately hinder analysis
- static & dynamic analysis
reasoning about structural and behavioral properties
- bug discovery
inspecting program behavior to uncover vulnerabilities
- patching
fixing security flaws
- decompilation
reconstructing higher-level representations to support reversing
The direction I find most compelling is the one the lab frames as an AI-driven pipeline: unifying stages that have traditionally been treated as separate problems, so that analysis of benign and malicious software becomes both scalable and resilient. The lab's second track — securing AI models themselves across the lifecycle, against poisoning, backdoors, evasion, extraction, inversion, and membership inference — sits on the other side of the same question.
.plt
calls out to the world
Contact
- yiyue AT g.skku.edu
- GitHub
- github.com/Yii-99
- Lab
- SecAI Lab, SKKU