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Στατική Δοκιμή Ασφάλειας Εφαρμογών×Ανάλυση Μόλυνσης Δεδομένων×
ΠεδίοΚρυπτογραφίαΚρυπτογραφία
ΟικογένειαMachine learningMachine learning
Έτος προέλευσης2000s2005
ΔημιουργόςVarious researchersJames Newsome
Τύποςsource code vulnerability detectiondata flow tracking technique
Θεμελιώδης πηγήChess, B., & West, J. (2007). Secure Programming with Static Analysis. Addison-Wesley Professional. ISBN: 978-0321424778Newsome, 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). link ↗
Εναλλακτικές ονομασίεςSAST, white-box testing, source code analysistaint analysis, information flow, data tainting
Συναφείς33
ΣύνοψηStatic 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.
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ScholarGateΣύγκριση μεθόδων: Static Application Security Testing · Taint Analysis. Ανακτήθηκε στις 2026-06-15 από https://scholargate.app/el/compare