Generating remediation strategies for responding to security deficiencies using generative machine learning models

1 . A method comprising:

receiving, by a processor, an identifier associated with a security deficiency, wherein the security deficiency is associated with a computer system;

determining, by the processor and based on the identifier, text data associated with the identifier;

determining, by the processor, a text prompt, wherein the text prompt comprises an instruction segment and the text data, and wherein the instruction segment comprises first text data identifying a remediation strategy detection task and second text data identifying an output constraint, and wherein the output constraint represents a requirement about a structure of output data generated by a generative machine learning model;

providing, by the processor, the text prompt to the generative machine learning model;

receiving, by the processor and from the generative machine learning model, a set of outputs including a first output identifying a first remediation strategy associated with addressing the security deficiency and a second output identifying a second remediation strategy associated with addressing the security deficiency;

validating, by the processor, the first output based on determining that the first output satisfies the output constraint;

determining, by the processor, that the second output is invalid based on determining that the second output fails to satisfy the output constraint;

determining, by the processor and based on validating the first output, a final output representing the first remediation strategy; and

providing, by the processor, the final output using an output interface.

2 . The method of claim 1 , wherein the remediation strategy detection task comprises identifying a software patch associated with the security deficiency.

3 . The method of claim 1 , wherein the remediation strategy detection task comprises identifying a software version update associated with the security deficiency.

4 . The method of claim 1 , wherein the remediation strategy detection task comprises identifying a software code update associated with the security deficiency.

5 . The method of claim 1 , wherein:

the instruction segment identifies a set of remediation strategies including the first remediation strategy and the second remediation strategy; and

the output constraint is associated with inclusion of a remediation strategy from the set of remediation strategies.

6 . The method of claim 1 , wherein the output constraint is associated with using a text structure.

7 . The method of claim 1 , wherein determining the text data comprises:

querying an advisory database based on the identifier.

8 . The method of claim 1 , further comprising:

receiving third text data;

determining a second text prompt based on the third text data;

providing the second text prompt to the generative machine learning model;

receiving a second set of outputs including a third output from the generative machine learning model;

determining that the second text prompt satisfies at least one of the output constraint or a second output constraint identified by the second text prompt; and

determining the final output based on the first output and the third output.

9 . The method of claim 8 , wherein determining the final output comprises:

determining a third text prompt based on the first output and the third output;

providing the third text prompt to the generative machine learning model;

receiving, from the generative machine learning model, a fourth output; and

determining the final output based on the fourth output.

10 . The method of claim 9 , wherein:

determining the fourth output comprises combining the first output and the second output.

11 . The method of claim 1 , wherein the first remediation strategy comprises the second remediation strategy.

12 . A system comprising:

one or more processors; and

one or more computer-readable media storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

receiving an identifier associated with a security deficiency, wherein the security deficiency is associated with a computer system;

determining, based on the identifier, text data associated with the identifier;

determining a text prompt, wherein the text prompt comprises an instruction segment and the text data, and wherein the instruction segment comprises first text data identifying a remediation strategy detection task and second text data identifying an output constraint, and wherein the output constraint represents a requirement about a structure of output data generated by a generative machine learning model;

providing the text prompt to the generative machine learning model;

receiving, from the generative machine learning model, a set of outputs including a first output identifying a first remediation strategy associated with addressing the security deficiency and a second output identifying a second remediation strategy associated with addressing the security deficiency;

validating the first output based on determining that the first output satisfies the output constraint;

determining that the second output is invalid based on determining that the second output fails to satisfy the output constraint;

determining, based on validating the first output, a final output representing the first remediation strategy; and

providing the final output using an output interface.

13 . The system of claim 12 , wherein the remediation strategy detection task comprises identifying a software patch associated with the security deficiency.

14 . The system of claim 12 , wherein the remediation strategy detection task comprises identifying a software version associated with the security deficiency.

15 . The system of claim 12 , wherein the remediation strategy detection task comprises identifying a software code update associated with the security deficiency.

16 . The system of claim 12 , wherein:

the instruction segment identifies a set of remediation strategies including the first remediation strategy and the second remediation strategy; and

the output constraint is associated with inclusion of a remediation strategy from the set of remediation strategies.

17 . One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

receiving an identifier associated with a security deficiency, wherein the security deficiency is associated with a computer system;

determining, based on the identifier, text data associated with the identifier;

determining a text prompt, wherein the text prompt comprises an instruction segment and the text data, and wherein the instruction segment comprises first text data identifying a remediation strategy detection task and second text data identifying an output constraint, and wherein the output constraint represents a requirement about a structure of output data generated by a generative machine learning model;

providing the text prompt to the generative machine learning model;

receiving, from the generative machine learning model, a set of outputs including a first output identifying a first remediation strategy associated with addressing the security deficiency and a second output identifying a second remediation strategy associated with addressing the security deficiency;

validating the first output based on determining that the first output satisfies the output constraint;

determining that the second output is invalid based on determining that the second output fails to satisfy the output constraint;

determining, based on validating the first output, a final output representing the first remediation strategy; and

providing the final output using an output interface.

18 . The one or more non-transitory computer-readable media of claim 17 , wherein the remediation strategy detection task comprises identifying a software patch associated with the security deficiency.

19 . The one or more non-transitory computer-readable media of claim 17 , wherein the remediation strategy detection task comprises identifying a software version associated with the security deficiency.

20 . The one or more non-transitory computer-readable media of claim 17 , wherein the remediation strategy detection task comprises identifying a software code update associated with the security deficiency.