방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 퍼징× | 정적 애플리케이션 보안 테스팅× | |
|---|---|---|
| 분야 | 암호학 | 암호학 |
| 계열 | Machine learning | Machine learning |
| 기원 연도≠ | 1990 | 2000s |
| 창시자≠ | Barton Miller | Various researchers |
| 유형≠ | random input-based testing technique | source code vulnerability detection |
| 원전≠ | Miller, B. P., Fredriksen, L., & So, B. (1990). An empirical study of the reliability of UNIX utilities. Communications of the ACM, 33(12), 32-44. DOI ↗ | Chess, B., & West, J. (2007). Secure Programming with Static Analysis. Addison-Wesley Professional. ISBN: 978-0321424778 |
| 별칭 | fuzz testing, fuzzer, mutation testing | SAST, white-box testing, source code analysis |
| 관련 | 3 | 3 |
| 요약≠ | Fuzzing is a software testing technique that inputs large numbers of random or semi-random test cases to a program to find bugs, crashes, and security vulnerabilities. Pioneered by Barton Miller in 1990, fuzzing has become a primary method for discovering zero-day vulnerabilities in complex software. Modern fuzzing tools like libFuzzer, AFL, and HoneyPot combine coverage-guided mutation with instrumentation to efficiently explore program paths and trigger vulnerabilities. Fuzzing has discovered thousands of critical vulnerabilities in major software including browsers, compilers, and cryptographic libraries. | Static Application Security Testing (SAST) is a security analysis technique that examines source code or compiled binaries without executing the program to identify vulnerabilities, code quality issues, and security flaws. Developed in the 2000s, SAST analyzes code structure, data flow, and control flow to detect potential bugs such as SQL injection, buffer overflows, and insecure cryptographic usage. SAST is widely integrated into development workflows as a shift-left security practice, enabling early detection of vulnerabilities before code reaches production. |
| ScholarGate데이터셋 ↗ |
|
|