# US 12,762,249 B2 · Systems and methods for remediation of unknown digital assets > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,762,249 B2 - Document ID: US12762249B2 - Status: Granted - Kind: B2 - Application number: 18/913,760 - Filed: 2024-10-11 - Published: 2026-04-16 - Granted: 2026-10-13 - Earliest claimed: 2024-10-11 - Assignees: Sap SE - Applicants: Sap SE - Inventors: Meenakshi; Sreekanth Kozhisseri Pattath; Ayush Jain; Sanjeev Peddi Reddi Gari; Rajwin Victor Jesudason; Sreeram V; Shivkumar Chakkenchath - Web page: https://patentgrep.com/patent/US12762249B2 ## CPC - G06F 21/577: {Assessing vulnerabilities and evaluating computer system security} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Described herein are techniques for the prioritization and remediation of unknown digital assets in computing environments. Unknown digital assets may be analyzed by one or more prioritization rules to generate a risk level for each unknown digital asset. Based on the risk level, a remediation action may be performed on the unknown digital asset. The remediation action to be performed on a remediation date that is also dependent on the risk level. Strategically decommissioning unknown assets may mitigate security risks and improve the operational efficiency of the computing environment. ## Claims ### Claim 1 A method, comprising: receiving, from one or more cloud service application programming interfaces (APIs), attribute data associated with a plurality of digital assets in a computing environment deployed within a computing environment comprising a plurality of virtual resources; identifying, by an asset management module, a subset of the plurality of digital assets having unknown ownership based on the received attribute data, wherein identifying the subset includes analyzing metadata associated with the plurality of digital assets to determine whether ownership information corresponding to a digital asset is absent or untraceable; determining, by a prioritization rules engine, a risk level for each digital asset in the subset of digital assets based on the received attribute data, wherein the risk level measures a susceptibility of each digital asset to potential attacks, wherein the determining the risk level for each digital asset includes: applying a plurality of prioritization rules to a digital asset from the subset of digital assets to generate a plurality of priority scores; and generating the risk level for the digital asset based on the plurality of priority scores; calculating, by a remediation module, a remediation date for the digital asset based on the risk level corresponding to the digital asset; and performing a remediation action on each digital asset in the subset of digital assets, wherein the remediation action is based on the risk level of each digital asset. ### Claim 2 (depends on 1) The method as in claim 1, further comprising transmitting a notification associated with a digital asset from the subset of digital assets when the risk level corresponding to the digital asset is greater than a predefined threshold. ### Claim 3 (depends on 1) The method as in claim 1, wherein performing the remediation action includes: calculating a remediation date based on the risk level of a digital asset, wherein the remediation date corresponds to a date to decommission the digital asset; and notifying an owner of the digital asset of the remediation date. ### Claim 4 (depends on 1) The method as in claim 1, wherein a prioritization rule classifies the digital asset into one of a plurality of predefined categories based on a type parameter of the digital asset, a functionality of the digital asset, and a criticality parameter of the digital asset. ### Claim 5 (depends on 1) The method as in claim 1, wherein a prioritization rule determines whether the digital asset is actively managed, monitored, deprecated, or supervised. ### Claim 6 (depends on 1) The method as in claim 1, wherein a prioritization rule determines an activity level of the digital asset. ### Claim 7 (depends on 1) The method as in claim 1, wherein a prioritization rule determines a network segment within which the digital asset resides. ### Claim 8 (depends on 1) The method as in claim 1, wherein a prioritization rule analyzes a completeness and an accuracy of metadata belonging to the digital asset. ### Claim 9 (depends on 1) The method as in claim 1, wherein a prioritization rule evaluates resource consumption of the digital asset. ### Claim 10 (depends on 1) The method as in claim 1, wherein a prioritization rule evaluates whether the digital asset complies with a regulatory standard, an internal policy, or an industry regulation. ### Claim 11 (depends on 1) The method as in claim 1, wherein determining the risk level for each digital asset includes applying a machine learning model to the received attribute data corresponding to a digital asset from the subset of digital assets to generate a risk level. ### Claim 12 (depends on 11) The method as in claim 11, further comprising visualizing a decision tree within the machine learning model on a graphical user interface of a display. ### Claim 13 (depends on 11) The method as in claim 11, wherein the machine learning model is validated using a confusion matrix. ### Claim 14 (depends on 11) The method as in claim 11, further comprising generating SHAP values corresponding to the received attribute data and determining one or more important features within the received attribute data based on SHapley Additive explanations values. ### Claim 15 A system comprising: one or more processors; a non-transitory computer-readable medium storing a program executable by the one or more processors, the program comprising sets of instructions for operations comprising: receiving, from one or more cloud service application programming interfaces (APIs), attribute data associated with a plurality of digital assets in a computing environment deployed within a computing environment comprising a plurality of virtual resources; identifying, by an asset management module, a subset of the plurality of digital assets having unknown ownership based on the received attribute data, wherein identifying the subset includes analyzing metadata associated with the plurality of digital assets to determine whether ownership information corresponding to a digital asset is absent or untraceable; determining, by a prioritization rules engine, a risk level for each digital asset in the subset of digital assets based on the received attribute data, wherein the risk level measures a susceptibility of each digital asset to potential attacks, wherein the determining the risk level for each digital asset includes: applying a plurality of prioritization rules to a digital asset from the subset of digital assets to generate a plurality of priority scores; and generating the risk level for the digital asset based on the plurality of priority scores; calculating, by a remediation module, a remediation date for the digital asset based on the risk level corresponding to the digital asset; and performing a remediation action on each digital asset in the subset of digital assets, wherein the remediation action is based on the risk level of each digital asset. ### Claim 16 (depends on 15) The system of claim 15, wherein the program further comprises sets of instructions for transmitting a notification associated with a digital asset from the subset of digital assets when the risk level corresponding to the digital asset is greater than a predefined threshold. ### Claim 17 A non-transitory computer-readable medium storing a program executable by one or more processors, the program comprising sets of instructions for performing operations comprising: receiving, from one or more cloud service application programming interfaces (APIs), attribute data associated with a plurality of digital assets in a computing environment deployed within a computing environment comprising a plurality of virtual resources; identifying, by an asset management module, a subset of the plurality of digital assets having unknown ownership based on the received attribute data, wherein identifying the subset includes analyzing metadata associated with the plurality of digital assets to determine whether ownership information corresponding to a digital asset is absent or untraceable; determining, by a prioritization rules engine, a risk level for each digital asset in the subset of digital assets based on the received attribute data, wherein the risk level measures a susceptibility of each digital asset to potential attacks, wherein the determining the risk level for each digital asset includes: applying a plurality of prioritization rules to a digital asset from the subset of digital assets to generate a plurality of priority scores; and generating the risk level for the digital asset based on the plurality of priority scores; calculating, by a remediation module, a remediation date for the digital asset based on the risk level corresponding to the digital asset; and performing a remediation action on each digital asset in the subset of digital assets, wherein the remediation action is based on the risk level of each digital asset. ### Claim 18 (depends on 17) The non-transitory computer-readable medium of claim 17, wherein the program further comprises sets of instructions for transmitting a notification associated with a digital asset from the subset of digital assets when the risk level corresponding to the digital asset is greater than a predefined threshold.