Anomalous asset detection based on open ports
Disclosed herein are methods, systems, and processes to detect anomalous computing assets based on open ports. Security data associated with computing assets executing in a computing environment is received from an agent executing on the computing assets. Open port information associated with the computing assets is extracted from the security data. The open port information and a list of computing assets with the open port information is used to generate a type similarity model and an open port model. The type similarity model clusters the computing assets and the open port model determines whether a port associated with a computing asset with the open port information is likely to be open or should be open in the computing environment, permitting detection of anomalous computing assets in the computing environment.
1. A computer-implemented method to detect anomalous computing assets, comprising:
receiving security data associated with a plurality of computing assets executing in a computing environment from an agent executing on each of the plurality of computing assets;
extracting open port information associated with each of one or more of the plurality of computing assets from the security data;
providing the open port information and a list of the one or more of the plurality of computing assets associated with the open port information to a processor executing instructions stored on a memory to generate: (1) a type similarity model and (2) an open port model;
receiving from the type similarity model, one or more clusters of computing assets of the plurality of computing assets, and from the open port model, information indicating whether each port associated with the one or more of the plurality of computing assets with the open port information should be open in the computing environment; and
detecting one or more anomalous computing assets in the computing environment.
2. The computer-implemented method of claim 1 , further comprising:
in response to the vulnerability scanner detecting the one or more anomalous computing assets, transmitting to the agent executing on each of the one or more anomalous computing assets, instructions to close their respective open ports.
3. The computer-implemented method of claim 1 , wherein
the one or more clusters of computing assets are generated by the type similarity model by clustering the plurality of computing assets using k-means clustering based on a type similarity characteristic of each of the plurality of computing assets, and
the type similarity characteristic comprises a role type, a use case type, a job type, a team type, a group type, or a department type.
4. The computer-implemented method of claim 1 , wherein
extracting the open port information from the security data is based on parsing the security data based on port type.
5. The computer-implemented method of claim 1 , wherein
the information indicating whether each port associated with the one or more of the plurality of computing assets with the open port information should be open is generated by the open port model based on a historical frequency of each port of each of the one or more of the plurality of computing assets with the open port information being open.
6. The computer-implemented method of claim 1 , wherein
the vulnerability scanner detects the one or more anomalous computing assets in the computing environment based on the open port model indicating that a port associated with a computing asset of the one or more of the plurality of computing assets with the open port information should not be open compared to other computing assets in a same cluster of the one or more clusters generated by the type similarity model as the computing asset.
7. A non-transitory computer readable storage medium comprising program instructions executable to:
receive security data associated with a plurality of computing assets executing in a computing environment from an agent executing on each of the plurality of computing assets;
extract open port information associated with each of one or more of the plurality of computing assets from the security data;
provide the open port information and a list of the one or more of the plurality of computing assets associated with the open port information to a processor executing instructions stored on a memory to generate: (1) a type similarity model and (2) an open port model;
receive from the type similarity model, one or more clusters of computing assets of the plurality of computing assets, and from the open port model, information indicating whether each port associated with the one or more of the plurality of computing assets with the open port information should be open in the computing environment; and
detect one or more anomalous computing assets in the computing environment.
8. The non-transitory computer readable storage medium of claim 7 , further comprising:
in response to the vulnerability scanner detecting the one or more anomalous computing assets, transmitting to the agent executing on each of the one or more anomalous computing assets, instructions to close their respective open ports.
9. The non-transitory computer readable storage medium of claim 7 , wherein
the one or more clusters of computing assets are generated by the type similarity model by clustering the plurality of computing assets using k-means clustering based on a type similarity characteristic of each of the plurality of computing assets, and
the type similarity characteristic comprises a role type, a use case type, a job type, a team type, a group type, or a department type.
10. The non-transitory computer readable storage medium of claim 7 , wherein
extracting the open port information from the security data is based on parsing the security data based on port type.
11. The non-transitory computer readable storage medium of claim 7 , wherein
the information indicating whether each port associated with the one or more of the plurality of computing assets with the open port information should be open is generated by the open port model based on a historical frequency of each port of each of the one or more of the plurality of computing assets with the open port information being open.
12. The non-transitory computer readable storage medium of claim 7 , wherein
the vulnerability scanner detects the one or more anomalous computing assets in the computing environment based on the open port model indicating that a port associated with a computing asset of the one or more of the plurality of computing assets with the open port information should not be open compared to other computing assets in a same cluster of the one or more clusters generated by the type similarity model as the computing asset.
13. A system comprising:
one or more processors; and
a memory coupled to the one or more processors, wherein the memory stores program instructions executable by the one or more processors to:
receive security data associated with a plurality of computing assets executing in a computing environment from an agent executing on each of the plurality of computing assets;
extract open port information associated with each of one or more of the plurality of computing assets from the security data;
provide the open port information and a list of the one or more of the plurality of computing assets associated with the open port information to a processor executing instructions stored on a memory to generate: (1) a type similarity model and (2) an open port model;
receive from the type similarity model, one or more clusters of computing assets of the plurality of computing assets, and from the open port model, information indicating whether each port associated with the one or more of the plurality of computing assets with the open port information should be open in the computing environment; and
detect one or more anomalous computing assets in the computing environment.
14. The system of claim 13 , further comprising:
in response to the vulnerability scanner detecting the one or more anomalous computing assets, transmitting to the agent executing on each of the one or more anomalous computing assets, instructions to close their respective open ports.
15. The system of claim 13 , wherein
the one or more clusters of computing assets are generated by the type similarity model by clustering the plurality of computing assets using k-means clustering based on a type similarity characteristic of each of the plurality of computing assets, and
the type similarity characteristic comprises a role type, a use case type, a job type, a team type, a group type, or a department type.
16. The system of claim 13 , wherein
extracting the open port information from the security data is based on parsing the security data based on port type.
17. The system of claim 13 , wherein
the information indicating whether each port associated with the one or more of the plurality of computing assets with the open port information should be open is generated by the open port model based on a historical frequency of each port of each of the one or more of the plurality of computing assets with the open port information being open.
18. The system of claim 13 , wherein
the vulnerability scanner detects the one or more anomalous computing assets in the computing environment based on the open port model indicating that a port associated with a computing asset of the one or more of the plurality of computing assets with the open port information should not be open compared to other computing assets in a same cluster of the one or more clusters generated by the type similarity model as the computing asset.