The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
All You Ever Wanted to Know about Dynamic Taint Analysis and Forward Symbolic Execution (but Might Have Been Afraid to Ask)
Open accessAbstract
Dynamic taint analysis and forward symbolic execution are quickly becoming staple techniques in security analyses. Example applications of dynamic taint analysis and forward symbolic execution include malware analysis, input filter generation, test case generation, and vulnerability discovery. Despite the widespread usage of these two techniques, there has been little effort to formally define the algorithms and summarize the critical issues that arise when these techniques are used in typical security contexts. The contributions of this paper are two-fold. First, we precisely describe the algorithms for dynamic taint analysis and forward symbolic execution as extensions to the run-time semantics of a general language. Second, we highlight important implementation choices, common pitfalls, and considerations when using these techniques in a security context.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Language-based information-flow security
Sabelfeld, A., & Myers, A. C. (2003) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2002.806121 · Cited by 1,907
Cited by
Enck (2014) · doi:10.1145/2619091 · Cited by 1,203
A survey of symbolic execution techniques
Baldoni, R., Coppa, E., D’elia, D. C., Demetrescu, C., & Finocchi, I. (2019) · ACM Computing Surveys · doi:10.1145/3182657 · Cited by 708
(2021) · doi:10.1109/tse.2019.2946563 · Cited by 574
Dynamic Malware Analysis in the Modern Era—A State of the Art Survey
Or-Meir, O., Nissim, N., Elovici, Y., & Rokach, L. (2020) · ACM Computing Surveys · doi:10.1145/3329786 · Cited by 384
Information flow control for secure cloud computing
Bacon, J., Eyers, D., Pasquier, T. F. J.-M., Singh, J., Papagiannis, I., & Pietzuch, P. (2014) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2013.122313.130423 · Cited by 105
Metadata
- Authors
- Schwartz, E. J., Avgerinos, T., & Brumley, D.
- Venue
- 2010 IEEE Symposium on Security and Privacy
- Publisher
- IEEE
- Published
- 2010
- Pages
- 317-331
- ISSN
- 1081-6011 (ISSN-L)
- OpenAlex
- W2138788987
- Cited by
- 717
- References
- 1
- FWCI
- 23.13
- Type
- conference paper
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: All You Ever Wanted to Know about Dynamic Taint Analysis and Forward Symbolic Execution (but Might Have Been Afraid to Ask). https://app.cochat.ai/papers/10.1109/sp.2010.26
- The paper
- 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). 2010 IEEE Symposium on Security and Privacy. https://doi.org/10.1109/sp.2010.26
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.