Machine learned model for generating opinionated threat assessments of security vulnerabilities
US-2024411898-A1 · Dec 12, 2024 · US
US10324825B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10324825-B2 |
| Application number | US-201816102843-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 14, 2018 |
| Priority date | Sep 23, 2016 |
| Publication date | Jun 18, 2019 |
| Grant date | Jun 18, 2019 |
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A source code processing application may process source code and realize the results of the code in a map configuration. In one example, the map may be displayed with a number of stations and pathways between the stations to illustrate associations with classes of the source code. An example method of operation may include one or more of retrieving source code comprising a class from memory, processing the source code to identify an error associated with the class, creating a map with a station linked to the error, and displaying the map on a device.
Opening claim text (preview).
What is claimed is: 1. A method, comprising: identifying one or more errors associated with one or more classes that occur during an execution of source code; creating a map that visually displays a plurality of stations linked to the one or more errors, wherein each station represents a unique data flow location within the source code being executed; and labeling a station on the map to indicate code that shares a class with code represented by at least one other station from among the plurality of stations. 2. The method of claim 1 , further comprising generating semantic information of the one or more classes and linking the semantic information to the one or more classes. 3. The method of claim 1 , wherein the map further includes dynamic data flow paths between the stations that occur during the execution of the source code. 4. The method of claim 1 , wherein a single path between two stations on the map represents a plurality of dataflows between the two stations that occur while the source code is executing, wherein the map further comprises an indicator that indicates that the single path represents a plurality of data flows. 5. The method of claim 1 , further comprising creating metadata associated with a station, the metadata comprising one or more of an error associated with the station, a number of traces which flow through the station, and a severity level of the station. 6. The method of claim 1 , wherein a path between two stations on the map represents one or more of: an application programming interface (API) calling another API; and data sequentially flowing between a first API and a second API while the source code is executing. 7. The method of claim 1 , wherein one or more of the plurality of stations comprise multiple class stations which are linked to multiple classes. 8. An apparatus, comprising: a processor configured to: identify one or more errors associated with one or more classes that occur during an execution of source code; create a map that visually displays a plurality of stations linked to the one or more errors, wherein each station represents a unique data flow location within the source code being executed; and label a station on the map to indicate code that shares a class with code represented by at least one other station from among the plurality of stations. 9. The apparatus of claim 8 , wherein the processor is further configured to generate semantic information of the one or more classes and link the semantic information to the one or more classes. 10. The apparatus of claim 8 , wherein the map further includes dynamic data flow paths between the stations that occur during the execution of the source code. 11. The apparatus of claim 8 , wherein a single path between two stations on the map represents a plurality of dataflows between the two stations that occur while the source code is executing, wherein the map further comprises an indicator that indicates that the single path represents a plurality of data flows. 12. The apparatus of claim 8 , wherein the processor is further configured to create metadata associated with a station, and the metadata comprises one or more of an error associated with the station, a number of traces which flow through the station, and a severity level of the station. 13. The apparatus of claim 8 , wherein a path between two stations on the map represents one or more of: an application programming interface (API) that calls another API; and data sequentially flowing between a first API and a second API while the source code is executing. 14. The apparatus of claim 8 , wherein one or more of the plurality of stations comprise multiple class stations which are linked to multiple classes. 15. A non-transitory computer readable storage medium configured to store instructions that when executed cause a processor to perform: identifying one or more errors associated with one or more classes that occur during an execution of source code; creating a map that visually displays a plurality of stations linked to the one or more errors, wherein each station represents a unique data flow location within the source code being executed; and labeling a station on the map to indicate code that shares a class with code represented by at least one other station from among the plurality of stations. 16. The non-transitory computer readable storage medium of claim 15 , wherein the processor is further configured to perform generating semantic information of the one or more classes and linking the semantic information to the one or more classes. 17. The non-transitory computer readable storage medium of claim 15 , wherein the map further includes dynamic data flow paths between the stations that occur during the execution of the source code. 18. The non-transitory computer readable storage medium of claim 15 , wherein a single path between two stations on the map represents a plurality of dataflows between the two stations that occur while the source code is executing, wherein the map further comprises an indicator that indicates that the single path represents a plurality of data flows. 19. The non-transitory computer readable storage medium of claim 15 , wherein the processor is further configured to perform creating metadata associated with a station, and the metadata comprises one or more of an error associated with the station, a number of traces which flow through the station, and a severity level of the station. 20. The non-transitory computer readable storage medium of claim 15 , wherein a path between two stations on the map represents one or more of: an application programming interface (API) calling another API; and data sequentially flowing between a first API and a second API while the source code is executing.
Test or assess software · CPC title
Assessing vulnerabilities and evaluating computer system security · CPC title
Visualisation of programs or trace data · CPC title
Physics · mapped topic
Environments for analysis, debugging or testing of software · CPC title
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