Abstract
AutoRand automatically transforms Java applications to use SQL keyword randomization to defend against SQL injection vulnerabilities. AutoRand is completely automatic. Unlike previous approaches it requires no manual modifications to existing code and does not require source (it works directly on Java bytecode). It can thus easily be applied to the large numbers of existing potentially insecure applications without developer assistance. Our key technical innovation is augmented strings. Augmented strings allow extra information (such as random keys) to be embedded within a string. AutoRand transforms string operations so that the extra information is transparent to the program, but is always propagated with each string operation. AutoRand checks each keyword at SQL statements for the random key. Experimental results on large, production Java applications and malicious inputs provided by an independent evaluation team hired by an agency of the United States government showed that AutoRand successfully blocked all SQL injection attacks and preserved transparent execution for benign inputs, all with low overhead.
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Notes
- 1.
We use the term keyword to include keywords, operators and comment tokens.
- 2.
For simplicity, we use the term ‘string’ to refer to objects of all three classes.
- 3.
The requirement assumes that the key does not occur in S. The space of keys ensures a sufficiently small probability that the key occurs in the application code or data by happenstance.
- 4.
The full test suite runs in a special environment and is difficult to instrument. The subset allowed for more manageable experiments.
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Acknowledgements
We thank the MITRE Corporation test and evaluation team for creating an automatic and thorough testing apparatus. We thank Stephen Fitzpatrick and Eric McCarthy of Kestrel Institute for their contributions to the project. We thank Michael Gordon of Aarno Labs for comments that greatly improved the manuscript.
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Perkins, J., Eikenberry, J., Coglio, A., Willenson, D., Sidiroglou-Douskos, S., Rinard, M. (2016). AutoRand: Automatic Keyword Randomization to Prevent Injection Attacks. In: Caballero, J., Zurutuza, U., Rodríguez, R. (eds) Detection of Intrusions and Malware, and Vulnerability Assessment. DIMVA 2016. Lecture Notes in Computer Science(), vol 9721. Springer, Cham. https://doi.org/10.1007/978-3-319-40667-1_3
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