Abstract: A system for automated malicious software detection includes a computing device, the computing device configured to receive a software component, identify at least an element of software component metadata corresponding to the software component, determine a malicious quantifier as a function of the software component metadata, wherein determining the malicious quantifier further comprises obtaining a source repository, the source repository including at least an element of source metadata, and determining the malicious quantifier as a function of the at least an element of software component metadata and the at least an element of source repository metadata using a malicious machine-learning model, and transmit a notification as a function of the malicious quantifier and a predictive threshold.
Type:
Grant
Filed:
August 12, 2022
Date of Patent:
July 11, 2023
Assignee:
SOOS LLC
Inventors:
Joshua Holden Jennings, Timothy Paul Kenney
Abstract: A system for version control is presented. The system includes a computing device, wherein the computing device is configured to receive a package build, wherein the package build a package build manifest, identify a package syntax element from the package build perform a manifest search as a function of the package syntax element, produce a universal version element as a function of the manifest search, verify the universal version element as a function of a version authenticator, and install the package build as a function of the verification.
Abstract: A system for automated malicious software detection includes a computing device, the computing device configured to receive a software component, identify at least an element of software component metadata corresponding to the software component, determine a malicious quantifier as a function of the software component metadata, wherein determining the malicious quantifier further comprises obtaining a source repository, the source repository including at least an element of source metadata, and determining the malicious quantifier as a function of the at least an element of software component metadata and the at least an element of source repository metadata using a malicious machine-learning model, and transmit a notification as a function of the malicious quantifier and a predictive threshold.
Type:
Application
Filed:
August 12, 2022
Publication date:
January 19, 2023
Applicant:
SOOS LLC
Inventors:
Joshua Holden Jennings, Timothy Paul Kenney
Abstract: A system for automated malicious software detection includes a computing device, the computing device configured to receive a software component, identify at least an element of software component metadata corresponding to the software component, determine a malicious quantifier as a function of the software component metadata, wherein determining the malicious quantifier further comprises obtaining a source repository, the source repository including at least an element of source metadata, and determining the malicious quantifier as a function of the at least an element of software component metadata and the at least an element of source repository metadata using a malicious machine-learning model, and transmit a notification as a function of the malicious quantifier and a predictive threshold.
Type:
Grant
Filed:
August 30, 2021
Date of Patent:
September 6, 2022
Assignee:
SOOS LLC
Inventors:
Joshua Holden Jennings, Timothy Paul Kenney