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Communication Dans Un Congrès Année : 2012

XSS Vulnerability Detection Using Model Inference Assisted Evolutionary Fuzzing

Résumé

We present an approach to detect web injection vulnerabilities by generating test inputs using a combination of model inference and evolutionary fuzzing. Model inference is used to obtain a knowledge about the application behavior. Based on this understanding, inputs are generated using genetic algorithm (GA). GA uses the learned formal model to automatically generate inputs with better fitness values towards triggering an instance of the given vulnerability.
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Dates et versions

hal-00857294 , version 1 (09-09-2013)

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Fabien Duchene, Roland Groz, Sanjay Rawat, Jean-Luc Richier. XSS Vulnerability Detection Using Model Inference Assisted Evolutionary Fuzzing. SECTEST 2012 - 3rd International Workshop on Security Testing (affiliated with ICST), Apr 2012, Montreal, Canada. pp.815-817, ⟨10.1109/ICST.2012.181⟩. ⟨hal-00857294⟩
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