PATENT CLAIM ANALYSIS

Application Number: 16027383
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2018-11
Patent Classification: ["726", "025000"]

Abstract:
A method for automatically mitigating vulnerabilities in a source code of an application is provided in the present invention. The method includes the following steps. First, the source code is complied, and a path graph is built according to the compiled source code. The path graph includes a plurality of paths traversing from sources to sinks, and each of the paths includes a plurality of nodes. Then, at least one tainted path is identified by enabling a plurality of vulnerability rules. Each of the at least one tainted path corresponds to a vulnerability, and each of the at least one vulnerability corresponds to a sanitization method. Then, the at least one vulnerability is determined if it is mitigable. If the at least one vulnerability is mitigable, the at least one vulnerability is mitigated automatically. Furthermore, the method may be implemented as a system and a computer program product.

Claim (Index 4):
The method of  claim 3 , wherein the step of setting the first node with the maximum confidence score as the target node in the first tainted path comprises:\n setting the first node with the maximum confidence score and closest to the sink as the target node in the first tainted path.

Metadata:
- Claim Count in Document: 3.0
- Percentile: 95.0
- Lexical Diversity: 2.3913
- Patent Class: 726.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['13905096', '15465603', '14845281', '12792747', '13746407']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3748451173663448
- 35 USC 102 Novelty (BERT): 0.5678808227588565
- Combined Prediction Score: 0.394148687905596
- Mean Citation Score: 408.6708
- Max Citation Score: 538.0287
- Similarity Product: 342.1517348877847

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test