End-to-end ai asset remediation
A system and method for end-to-end AI asset remediation are presented. The method includes analyzing a plurality of identified security risks, compliance risks, and security posture gaps to determine an optimal remediation path; constructing a remediation plan based on the optimal remediation path, whereby the constructed remediation plan comprises a plurality of generated corrective actions; performing one or more simulations of the plurality of generated corrective actions to verify one or more underlying root causes and to assess potential operational and security impacts; executing the plurality of generated corrective actions across internal and external systems; and performing post-action reevaluation to validate success of the executed plurality of generated corrective actions.
1 . A method for end-to-end artificial intelligence (AI) asset remediation, comprising:
analyzing a plurality of identified security risks, compliance risks, and security posture gaps to determine an optimal remediation path;
constructing a remediation plan based on the optimal remediation path, whereby the constructed remediation plan comprises a plurality of generated corrective actions;
prior to executing the plurality of generated corrective actions, performing one or more simulations of the plurality of generated corrective actions within a controlled environment that mirrors a production environment to verify one or more underlying root causes and to assess potential operational, security, and stability impacts of the plurality of generated corrective actions;
executing the plurality of generated corrective actions across internal and external systems; and
performing post-action reevaluation to validate that execution of the plurality of generated corrective actions neutralized and resolved at least one of the plurality of identified security risks, the plurality of identified compliance risks, and the plurality of identified security posture gaps.
2 . The method of claim 1 , further comprising:
reconstructing the constructed remediation plan based on results of the performed one or more simulations, wherein the simulation results indicate at least one of: a different or deeper root cause, an unintended operational or security impact, a requirement that one or more corrective actions include additional steps or revised sequencing, a determination that one or more corrective actions are unnecessary, or a need to reevaluate compliance or governance requirements.
3 . The method of claim 1 , wherein analyzing the plurality of identified security risks, compliance risks, and security posture gaps to determine the optimal remediation path comprises using, at least in part, a remediation intelligence engine to maximize risk reduction across an enterprise environment.
4 . The method of claim 1 , wherein performing the post-action reevaluation to validate the success of the executed plurality of generated corrective actions comprises using, at least in part, a reasoning model to implement a closed-loop verification process.
5 . The method of claim 1 , wherein executing the plurality of generated corrective actions across the internal and external systems comprises using, at least in part, a reasoning model to autonomously deploy the plurality of generated corrective actions.
6 . The method of claim 1 , wherein constructing the remediation plan based on the optimal remediation path comprises using, at least in part, a reasoning model to perform advanced reasoning to analyze the plurality of identified security risks, compliance risks, and security posture gaps, established platform integrations, organizational policies, and a textual recipe book.
7 . The method of claim 1 , wherein performing the one or more simulations of the plurality of generated corrective actions comprises using, at least in part, a reasoning model to apply the plurality of generated corrective actions within a controlled environment.
8 . The method of claim 1 , wherein the success of the executed plurality of generated corrective actions is determined based on resolving the plurality of identified security risks, compliance risks, and security posture gaps across a plurality of discovered AI assets in an enterprise environment.
9 . The method of claim 1 , wherein performing the post-action reevaluation further comprises:
reperforming a posture management process; and
reperforming a runtime protection process.
10 . The method of claim 1 , further comprising:
implementing a closed-loop verification process that uses results of the performed post-action reevaluation to update remediation logic for future remediation efforts.
11 . The method of claim 8 , wherein a discovered AI asset comprises any one of: a tool, a data source, or an other AI asset.
12 . The method of claim 1 , wherein the plurality of identified security risks, compliance risks, and security posture gaps are identified through a performed posture management process and a performed runtime protection process.
13 . A system for end-to-end artificial intelligence (AI) asset remediation comprising:
one or more processors configured to:
analyze a plurality of identified security risks, compliance risks, and security posture gaps to determine an optimal remediation path;
construct a remediation plan based on the optimal remediation path, whereby the constructed remediation plan comprises a plurality of generated corrective actions;
prior to executing the plurality of generated corrective actions, perform one or more simulations of the plurality of generated corrective actions within a controlled environment that mirrors a production environment to verify one or more underlying root causes and to assess potential operational, security, and stability impacts of the plurality of generated corrective actions;
execute the plurality of generated corrective actions across internal and external systems; and
perform post-action reevaluation to validate that execution of the plurality of generated corrective actions neutralized and resolved at least one of the plurality of identified security risks, the plurality of identified compliance risks, and the plurality of identified security posture gaps.
14 . The system of claim 13 , wherein the one or more processors are further configured to:
reconstruct the constructed remediation plan based on results of the performed one or more simulations, wherein the simulation results indicate at least one of: a different or deeper root cause, an unintended operational or security impact, a requirement that one or more corrective actions include additional steps or revised sequencing, a determination that one or more corrective actions are unnecessary, or a need to reevaluate compliance or governance requirements.
15 . The system of claim 13 , wherein the one or more processors, when analyzing the plurality of identified security risks, compliance risks, and security posture gaps to determine the optimal remediation path, are configured to use, at least in part, a remediation intelligence engine to maximize risk reduction across an enterprise environment.
16 . The system of claim 13 , wherein the one or more processors, when performing the post-action reevaluation to validate the success of the executed plurality of generated corrective actions, are configured to use, at least in part, a reasoning model to implement a closed-loop verification process.
17 . The system of claim 13 , wherein the one or more processors, when executing the plurality of generated corrective actions across the internal and external systems, are configured to use, at least in part, a reasoning model to autonomously deploy the plurality of generated corrective actions.
18 . The system of claim 13 , wherein the one or more processors, when constructing the remediation plan based on the optimal remediation path, are configured to use, at least in part, a reasoning model to perform advanced reasoning to analyze the plurality of identified security risks, compliance risks, and security posture gaps, established platform integrations, organizational policies, and a textual recipe book.
19 . The system of claim 13 , wherein the one or more processors, when performing the one or more simulations of the plurality of generated corrective actions, are configured to use, at least in part, a reasoning model to apply the plurality of generated corrective actions within a controlled environment.
20 . The system of claim 13 , wherein the success of the executed plurality of generated corrective actions is determined based on resolving the plurality of identified security risks, compliance risks, and security posture gaps across a plurality of discovered AI assets in an enterprise environment.
21 . The system of claim 20 , wherein a discovered AI asset comprises any one of: a tool, a data source, or an other AI asset.
22 . The system of claim 13 , wherein the one or more processors, when performing the post-action reevaluation, are configured to:
reperform a posture management process; and
reperform a runtime protection process.
23 . The system of claim 13 , wherein the one or more processors are further configured to:
implement a closed-loop verification process that uses results of the performed post-action reevaluation to update remediation logic for future remediation efforts.
24 . The system of claim 13 , wherein the plurality of identified security risks, compliance risks, and security posture gaps are identified through a performed posture management process and a performed runtime protection process.
25 . A non-transitory computer-readable medium storing a set of instructions for end-to-end artificial intelligence (AI) asset remediation, the set of instructions comprising:
one or more instructions that, when executed by one or more processors of a device, cause the device to:
analyze a plurality of identified security risks, compliance risks, and security posture gaps to determine an optimal remediation path;
construct a remediation plan based on the optimal remediation path, whereby the constructed remediation plan comprises a plurality of generated corrective actions;
prior to executing the plurality of generated corrective actions, perform one or more simulations of the plurality of generated corrective actions within a controlled environment that mirrors a production environment to verify one or more underlying root causes and to assess potential operational security, and stability impacts of the plurality of generated corrective actions;
execute the plurality of generated corrective actions across internal and external systems; and
perform post-action reevaluation to validate that execution of the plurality of generated corrective actions neutralized and resolved at least one of the plurality of identified security risks, the plurality of identified compliance risks, and the plurality of identified security posture gaps.