JavaScript engine security test method and JavaScript engine security test system
A security testing and testing system technology, applied in software testing/debugging, biological neural network model, neural architecture, etc., can solve problems such as infeasibility, omission, and inability to trigger the deep logic of the engine, and achieve the effect of high grammatical correctness
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Embodiment 1
[0036] see figure 1 , a JavaScript engine security testing method provided in this embodiment includes:
[0037] S1. Acquiring JavaScript test cases;
[0038]The input data for the present invention are test cases. The data set selected in this embodiment is the JavaScript code (https: / / www.sri.inf.ethz.ch / js150) obtained on Github, and the ECMAScript test set Test262 (https: / / github.com / tc39 / test262 ).
[0039] S2. Perform grammatical analysis on the test case to generate a corpus;
[0040] The syntax parsing part can be subdivided into three steps of renaming, parsing and conversion.
[0041] 1) renaming refers to each of the test cases, according to the order of appearance of the variables and function names in the test case, renaming the variables and the function names to obtain a renamed test case;
[0042] In order to enable the model to generate the second half of the sequence based on the first half of the sequence, or to generate a new sequence from scratch, the...
Embodiment 2
[0068] For the above method, the present invention also discloses a JS engine security testing system based on a syntax analyzer and a variational learner, please refer to Figure 4 , the system includes:
[0069] The test case obtaining module 201 is used for obtaining test cases.
[0070] The syntax analysis module 202 is configured to perform syntax analysis on the test case and generate a corpus. The tool for parsing code into AST is esprima.
[0071] The variational learner module 203 is used for training the learner and generating new corpus according to the corpus. The hardware information used by the learner is: graphics card Tesla V100 (single core), processor Intel Xeon CPU2.00GHz, memory 25GB.
[0072] The corpus assembly module 204 is used to assemble the new corpus output by the learner to obtain new test cases. The tool used to generate code from AST is escodegen.
[0073] The scanning and monitoring module 205 is used to input test cases into the JS engine ...
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