方法对比
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| 动态应用程序安全测试× | 模糊测试× | |
|---|---|---|
| 领域 | 密码学 | 密码学 |
| 方法族 | Machine learning | Machine learning |
| 起源年份≠ | 2000s | 1990 |
| 提出者≠ | Various researchers | Barton Miller |
| 类型≠ | runtime vulnerability detection | random input-based testing technique |
| 开创性文献≠ | Kals, S., Kirda, E., Kruegel, C., & Jovanovic, N. (2006). Secubat: A web vulnerability scanner. In Proceedings of the 15th International Conference on World Wide Web (WWW 2006), pp. 247-256. DOI ↗ | 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 ↗ |
| 别名 | DAST, black-box testing, runtime security testing | fuzz testing, fuzzer, mutation testing |
| 相关 | 3 | 3 |
| 摘要≠ | Dynamic Application Security Testing (DAST) is a security analysis technique that tests a running application by sending various inputs and observing responses to identify vulnerabilities and security flaws. Developed in the 2000s as a complement to static analysis, DAST exercises the application at runtime, finding vulnerabilities that only manifest during execution such as authentication bypass, insecure redirects, and logic flaws. DAST is commonly used for web application testing and is considered a black-box testing approach since the tester requires no knowledge of internal code structure. | 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. |
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