Capital One Services, LLC

Shannon Reid

Mohamed Seck

Grant Michael Iwan

Krystan R Franzen

Sesha Sowmya Nadiminti

In some implementations, an exception system may receive an indication of a security vulnerability associated with a cloud environment. The exception system may provide a data structure that represents the security vulnerability to a machine learning model in order to receive a suggested exception justification. The exception system may output, to a user device associated with a user assigned to the security vulnerability, a draft exception request that includes the suggested exception justification. The exception system may receive, from the user device, a request to submit an exception request based on the draft exception request. The exception system may transmit a command to tag the security vulnerability as excepted.

Automated vulnerability exception process

In some implementations, a compliance system may receive, from a pipeline system, a set of properties associated with configuration of a cloud infrastructure. Additionally, the compliance system may receive, from a code repository, a set of computer code associated with the cloud infrastructure. The compliance system may provide the set of properties and the set of computer code to a machine learning model to receive a set of compliance indicators and a set of severity levels. Each compliance indicator in the set of compliance indicators being associated with a corresponding severity level in the set of severity levels. The compliance system may selectively deploy the cloud infrastructure in response to receiving the set of severity levels.

Automatic compliance assessment of cloud infrastructure code

In some implementations, a compliance server may receive a set of data structures associated with one or more compliance activities. The compliance server may apply a machine learning model to the set of data structures in order to generate one or more automation estimates corresponding to the one or more compliance activities. The compliance server may output the one or more automation estimates to a user device. The compliance server may receive, from the user device, an indication of a selected compliance activity from the one or more compliance activities. The compliance server may generate an automation script for the selected compliance activity in response to the indication.

Compliance for cloud-based applications and computer systems using machine learning

In some implementations, an instruction management system may receive, from a plurality of user devices, a set of feedback associated with the instruction document. The instruction management system may identify a compliance activity associated with the instruction document and identify at least one location in the instruction document based on the set of feedback. The instruction management system may trigger an instruction to a tracking system to open a ticket associated with the compliance activity and the at least one location.

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Richmond, VA, United States of America

Shannon Reid