Сравнение на методи

	Динамично тестване за сигурност на приложения	Статичен анализ на сигурността на приложенията	Анализ на замърсяване
Област	Криптография	Криптография	Криптография
Семейство	Machine learning	Machine learning	Machine learning
Година на възникване	2000s	2000s	2005
Създател	Various researchers	Various researchers	James Newsome
Тип	runtime vulnerability detection	source code vulnerability detection	data flow tracking technique
Основополагащ източник	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.	Chess, B., & West, J. (2007). Secure Programming with Static Analysis. Addison-Wesley Professional. ISBN: 978-0321424778	Newsome, J., & Song, D. X. (2005). Dynamic taint analysis for automatic detection, analysis, and signature generation of exploits on commodity software. In Network and Distributed System Security Symposium (NDSS 2005).
Други названия	DAST, black-box testing, runtime security testing	SAST, white-box testing, source code analysis	taint analysis, information flow, data tainting
Свързани	3	3	3
Резюме	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.	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.	Taint analysis is a data flow analysis technique that tracks how untrusted (tainted) input flows through a program to identify vulnerabilities where tainted data reaches dangerous operations (sinks). Formalized by Newsome and Song in 2005, taint analysis marks input data as tainted and propagates taint labels through the program, alerting when tainted data reaches sensitive operations like SQL queries or system calls. Taint analysis is fundamental to detecting injection vulnerabilities and is widely used in dynamic analysis tools and security monitoring systems.