Taint Analysis
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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- 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). · URL
- Schwartz, E. J., Avgerinos, T., & Brumley, D. (2010). All you ever wanted to know about dynamic taint analysis and forward symbolic execution (but might have been afraid to ask). In IEEE Symposium on Security and Privacy (SP), 2010, pp. 317-331. · DOI 10.1109/SP.2010.26
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.