Patents Assigned to Praetorian
  • SYSTEM AND METHOD FOR AUTOMATICALLY DETECTING A SECURITY VULNERABILITY IN A SOURCE CODE USING A MACHINE LEARNING MODEL
    Publication number: 20230177170
    Abstract: There is disclosed a method of automatically detecting a security vulnerability in a source code using a machine learning model, characterized in that the method comprises: obtaining the source code from a client codebase, wherein the client codebase is a complete or an incomplete body of the source code for a given software program or an application; and using a machine learning (ML) model to perform a ML based analysis on an abstract syntax tree (AST) for detecting a first security vulnerability over a static source code, the machine learning based analysis comprise (i) flattening the abstract syntax tree (AST) into a sequence of structured tokens, wherein the sequence of structured tokens comprises a semantic structure and a syntactic structure of the source code, (ii) implementing a natural language processing technique on the sequence of structured tokens for mapping the sequence of structured tokens to one or more integers, (iii) pre-training the machine learning model using an unlabeled source code as
    Type: Application
    Filed: January 30, 2023
    Publication date: June 8, 2023
    Applicant: PRAETORIAN
    Inventors: Jeff Olson, Matthew Kindy, II
  • System and method for automatically detecting a security vulnerability in a source code using a machine learning model
    Patent number: 11568055
    Abstract: A method for (of) automatically detecting a security vulnerability in a source code using a machine learning model, characterized in that the method includes: obtaining the source code from a client codebase, wherein the client codebase is a complete or an incomplete body of the source code for a given software program or an application; and using a machine learning (ML) model to perform a ML based analysis on an abstract syntax tree (AST) for detecting a first security vulnerability over a static source code, the machine learning based analysis comprise (i) flattening the abstract syntax tree (AST) into a sequence of structured tokens, wherein the sequence of structured tokens includes a semantic structure and a syntactic structure of the source code, (ii) implementing a natural language processing technique on the sequence of structured tokens for mapping the sequence of structured tokens to one or more integers, (iii) pre-training the machine learning model using an unlabeled source code as an input to pre
    Type: Grant
    Filed: August 23, 2019
    Date of Patent: January 31, 2023
    Assignee: Praetorian
    Inventors: Jeff Olson, Matthew Kindy, II