Abstract: Systems, methods, and computer-readable media for telemetry intercept and analysis tools to work with programming languages that do not provide kernel access are provided. Programming languages such as Go do not provide kernel access and do not call standard library functions during operation of the application executable. A library constructor can be used to modify the application executable so that telemetry data can be obtained by an interception library even though the application executable does not call any functions in the interception library.

Abstract: Systems, methods, and computer-readable media for intercepting telemetry events obtained during operation of an application and analyzing the telemetry events are provided. The telemetry events are intercepted at the library level by interposing on application calls to a native library. The telemetry events are collected and transmitted to a platform that analyzes the collected events and presents information based on the analysis.

Abstract: Systems, methods, and computer-readable media for intercepting telemetry events obtained during operation of an application and analyzing the telemetry events are provided. The analysis can generate vulnerability reports that are supplemented with contextual data to assist a user in remediation efforts.

Abstract: Systems, methods, and computer-readable media for intercepting telemetry events obtained during operation of an application and analyzing the telemetry events are provided. The analysis can generate drift reports that can inform users at which point in time a particular change to the software affected an operation thereof.

Abstract: Systems, methods, and computer-readable media for operationalizing standard bill of material (SBOM) content for a software application and providing SBOM analysis. Embodiments discussed herein also remediate vulnerable components contained in the SBOM by identifying vulnerable components within the SBOM and updating those components with a fixed version thereof to produce an updated build of the application.

Abstract: Systems, methods, and computer-readable media for operationalizing standard bill of material (SBOM) content for software and providing SBOM analysis. Embodiments discussed herein can receive vulnerabilities from the at least one CVE source, determine whether the SBOM contains SBOM components associated with at least one of the vulnerabilities, and prevent an SBOM component from being used in an application build for the application when a vulnerability associated with that SBOM component exceeds a threshold.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive mapping operations with respect to a ground-truth database table. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive mapping operations utilizing a hierarchical string matching machine learning framework using at least one or more of an exact match model, a probabilistic match model, a disjoint match model, and an embedding-based match model.

Abstract: Various embodiments of the present invention disclose techniques for orchestrating a complex data processing scheme for an investigative process using a machine-learning based orchestration model that is trained to optimize the use of computing resources based at least in part on a feedback loop. An input data object associated with an investigative process can be selected for investigation; a predictive data analysis sub-routine for processing the input data object can be intelligently selected from a plurality of predictive data analysis sub-routines by the machine-learning based orchestration model; and a processing orchestration action can be initiated based at least in part on an investigative score output by the predictive data analysis sub-routine. The processing orchestration action can include closing the input data object, continuing to process the input data object with additional predictive data analysis sub-routines, or passing the input data object to a predictive entity for further processing.

Abstract: Various embodiments of the present invention disclose techniques for optimizing a plurality of machine-learning based models for an end-to-end investigative process. The techniques include generating a profile for an input data object associated with an investigative process. A first machine-learning based model is used to select a predictive data analysis sub-routine for processing the profile. A second machine-learning based model is used to determine a predictive entity for performing an investigative process for the profile. An investigative outcome is received from the predictive entity. A historical optimization data object is augmented with the investigative outcome, the profile, the predictive data analysis sub-routine, or the predictive entity and the first machine-learning based model and the second machine-learning based model are trained using the historical optimization object.

Abstract: Systems, methods, and computer-readable media for intercepting telemetry events obtained during operation of an application and analyzing the telemetry events are provided. The telemetry events are intercepted at the library level by interposing on application calls to a native library. The telemetry events are collected and transmitted to a platform that analyzes the collected events and presents information based on the analysis.

Abstract: Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive data analysis, wherein an opportunity prediction is generated for an input data object using a relationship matrix database object and based at least in part on a network segment associated with the input data object.

Abstract: Systems, methods, and computer-readable media for performing web app scans of an application are provided. Telemetry events derived from the web app scan are intercepted by a runtime that has been instrumented in conjunction with the application. The telemetry events are collected and transmitted to a platform that analyzes the collected events and presents information based on the analysis.

Abstract: Systems, methods, and computer-readable media for intercepting telemetry events obtained during operation of an application and analyzing the telemetry events are provided. The telemetry events are intercepted at the library level by interposing on application calls to a native library. The telemetry events are collected and transmitted to a platform that analyzes the collected events and presents information based on the analysis.

Abstract: Systems, methods, and computer-readable media for intercepting telemetry events obtained during operation of an application and analyzing the telemetry events are provided. The telemetry events are intercepted at the library level by interposing on application calls to a native library. The telemetry events are collected and transmitted to a platform that analyzes the collected events and presents information based on the analysis.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive mapping operations with respect to a ground-truth database table. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive mapping operations utilizing a hierarchical string matching machine learning framework using at least one or more of an exact match model, a probabilistic match model, a disjoint match model, and an embedding-based match model.

Abstract: Systems, methods, and computer-readable media for intercepting telemetry events obtained during operation of an application and analyzing the telemetry events are provided. The telemetry events are intercepted at the library level by interposing on application calls to a native library. The telemetry events are collected and transmitted to a platform that analyzes the collected events and presents information based on the analysis.

Abstract: Systems, methods, and computer-readable media for intercepting telemetry events obtained during operation of an application and analyzing the telemetry events are provided. The telemetry events are intercepted at the library level by interposing on application calls to a native library. The telemetry events are collected and transmitted to a platform that analyzes the collected events and presents information based on the analysis.

Abstract: Systems, methods, and computer-readable media for intercepting telemetry events obtained during operation of an application and analyzing the telemetry events are provided. The telemetry events are intercepted at the library level by interposing on application calls to a native library. The telemetry events are collected and transmitted to a platform that analyzes the collected events and presents information based on the analysis.

Abstract: Systems, methods, and computer-readable media for performing web app scans of an application are provided. Telemetry events derived from the web app scan are intercepted by a runtime that has been instrumented in conjunction with the application. The telemetry events are collected and transmitted to a platform that analyzes the collected events and presents information based on the analysis.

Abstract: Systems, methods, and computer-readable media for intercepting telemetry events obtained during operation of an application and analyzing the telemetry events are provided. The telemetry events are intercepted at the library level by interposing on application calls to a native library. The telemetry events are collected and transmitted to a platform that analyzes the collected events and presents information based on the analysis.