Run-time configurable cybersecurity system
A system for conducting cyberthreat analytics on a submitted object to determine whether the object is malicious is described. The system features a cybersecurity system operating with a cloud platform, which is configured to host resources including cloud processing resources and cloud storage resources. The cybersecurity system is configured to analyze one or more received objects included as part of a submission received from a subscriber after authentication of the subscriber and verification that the subscriber is authorized to perform one or more tasks associated with the submission. The cybersecurity system is configured to operate as a multi-tenant Security-as-a-Service (SaaS) that relies upon the cloud processing resources and the cloud storage resources provided by the cloud platform in performing the cybersecurity operations.
1. A system for conducting cyberthreat analytics on a submitted object to determine whether the object is malicious, comprising:
a cloud platform configured to host resources including cloud processing resources and cloud storage resources; and
a cybersecurity system to analyze one or more received objects included as part of a submission received from a subscriber after authentication of the subscriber and verification that the subscriber is authorized to perform one or more tasks associated with the submission, wherein the cybersecurity system comprises
an interface to receive the submission including the one or more objects for analysis,
administrative control logic including (i) a credential management module being configured to generate a first credential assigned to the subscriber associated with the submission, and (ii) an auto-scaling module to generate analytic engines based on computing instances hosted by the cloud platform, and
an object evaluation logic configured to receive a data sample from the administrative control logic, the data sample being a portion of the submission that comprises the one or more received objects and context information associated with the one or more received objects, the object evaluation logic includes a cyberthreat analytic module that comprises the analytic engines each directed to a different analysis approach in analyzing the one or more received objects for malware,
wherein the analytic engines comprise a combination of two or more of any of (1) a static analytic engine to conduct an analysis on content of an object of the one or more received objects and generate results including observed features represented by characteristics of the object and the context information associated with the object; (2) a dynamic analytic engine to execute the object and generate results including features represented by observed behaviors of the dynamic analytic engine along with context information accompanying the observed features; (3) a machine learning analytic engine to submit the object as input into a trained machine-learning model and generates results including features represented by insights derived from the machine-learning model and accompanying context information; and (4) an emulation analytic engine to conduct reproduction of operations representing an execution of the object and generate results including features represented by behaviors captured during emulation and accompanying context information.
2. The system of claim 1 , wherein the cloud platform is operating as an Infrastructure-as-a-Service.
3. The system of claim 2 , wherein the cloud processing resources includes one or more computing instances.
4. The system of claim 1 , wherein the cybersecurity system further includes logic to monitor a number of submissions received from the subscriber for computation of costs associated with usage of the cybersecurity system while the cloud platform to monitor (i) an amount of processing time used by the cloud processing resources for execution of logic associated with the cybersecurity system and (ii) an amount of storage used by the cybersecurity system in maintaining the logic associated with the cybersecurity system.
5. The system of claim 1 , wherein the cybersecurity system further includes the object evaluation logic configured to conduct cyberthreat analytics on the one or more received objects independent of object type.
6. The system of claim 1 , wherein the cybersecurity system further includes a credential management module that is configured to generate one or more keys for use in authentication of the subscriber or verify that the subscriber is authorized to perform the one or more tasks associated with the submission.
7. The system of claim 5 , wherein the auto-scaling module of the administrative control logic is configured to generate one or more of the analytic engines in response to detection of at least a particular level of usage of queue elements maintaining the one or more received objects that are awaiting cyberthreat analytics being conducted on the one or more received objects.
8. The system of claim 5 , wherein the cybersecurity system includes system health monitor logic being communicatively coupled to the analytic engines generates based on computing instances associated with the cloud processing resources.
9. The system of claim 1 , wherein the cybersecurity system further includes a consumption quota monitoring module configured to enable the subscriber to obtain metrics associated with the current state of a subscription, the metrics include at least a total number of submissions conducted during a subscription period or a number of submissions remaining for the subscription period.
10. A cybersecurity system deployed as a cloud-based, multi-tenant Security-as-a-Service (SaaS) leveraging resources hosted by a cloud platform operating as an Infrastructure-as-a-Service (IaaS), the cybersecurity system comprising:
an interface to receive a submission including one or more objects for analysis and a virtual key provided to a subscriber for attachment to the submission;
administrative control logic including (i) a credential management module being configured to generate a first credential assigned to the subscriber associated with the submission, and (ii) an auto-scaling module to generate analytic engines based on computing instances hosted by the cloud platform in response to detection of at least a particular level of usage of queue elements maintaining objects that are awaiting cyberthreat analytics being conducted on the maintained objects; and
an object evaluation logic configured to receive a data sample from the administrative control logic, the data sample being a portion of the submission that comprises content associated with the submission including one or more objects and context information associated with the one or more objects, the object evaluation logic includes a cyberthreat analytic module that comprises one or more analytic engines each directed to a different analysis approach in analyzing the one or more objects for malware,
wherein the one or more analytic engines comprises a combination of two or more of any of (1) a static analytic engine to conduct an analysis on content of an object of the one or more objects and generate results including observed features represented by characteristics of the object and the context information associated with the object; (2) a dynamic analytic engine to execute the object and generate results including features represented by observed behaviors of the dynamic analytic engine along with context information accompanying the observed features; (3) a machine learning analytic engine to submit the object as input into a trained machine-learning model and generates results including features represented by insights derived from the machine-learning model and accompanying context information; and (4) an emulation analytic engine to conduct reproduction of operations representing an execution of the object and generate results including features represented by behaviors captured during emulation and accompanying context information.
11. The cybersecurity system of claim 10 , wherein at least one analytic engine of the analytic engines to perform cyberthreat analytics on the one or more objects to determine whether any of the one or more objects include malware.
12. The cybersecurity system of claim 10 , wherein the credential management module and the auto-scaling module form a portion of administrative control logic of the cybersecurity system.
13. The cybersecurity system of claim 12 further comprising an object evaluation logic configured to receive a data sample from the administrative control logic, the data sample being a portion of the submission that comprises content associated with the submission including one or more objects and context information associated with the one or more objects, the object evaluation logic to conduct cyberthreat analyses on at least the one or more objects included as part of the data sample.
14. The cybersecurity system of claim 13 , wherein the object evaluation logic comprises a plurality of evaluation stages with each evaluation stage of the plurality of evaluation stages being provided access a queue including a plurality of queue elements each storing the content.
15. The cybersecurity system of claim 14 , wherein an evaluation stage of the plurality of evaluation stages includes a cyberthreat analytic module that comprises the one or more analytic engines each directed to a different analysis approach in analyzing the one or more objects for malware.
16. The cybersecurity system of claim 10 , wherein each of the context information associated with the features provides additional information associated with the features.
17. The cybersecurity system of claim 10 , wherein a second evaluation stage of the plurality of evaluation stages includes an analytic engine selection module configured to determine the one or more analytic engines to conduct cyberthreat analytics of the object based on at least a portion of the context information accompanying the object being part of the data sample.
18. The cybersecurity system of claim 17 , wherein a third evaluation stage of the plurality of evaluation stages includes a correlation module to analyze features associated with the object to determine whether the object includes malware.
19. The cybersecurity system of claim 10 , wherein interface includes an Application Programming Interface (API) provided to the subscriber upon completion of an onboarding subscription process provided as part of the cybersecurity system.
20. A cybersecurity system deployed as a cloud-based, multi-tenant Security-as-a-Service (SaaS) leveraging resources hosted by a cloud platform operating as an Infrastructure-as-a-Service (IaaS), the cybersecurity system comprising:
an interface to receive (ii) a submission that comprises a data sample including one or more objects and (ii) a virtual key attached to the submission to identify a subscriber that provided the submission, the data sample to be provided for cyberthreat analytics;
administrative control logic to validate the submission, authenticate the subscriber submitting the submission, verify that the submission including the data sample is in compliance with parameters associated with a subscription held by the subscriber to provide the submission to the cybersecurity system, and output at least the data sample;
object evaluation logic to receive the data sample provided from the administrative control logic and conduct cyberthreat analytics on the one or more objects included in the data sample, where the object evaluation logic includes a cyberthreat analytic module that comprises one or more analytic engines each directed to a different cyberthreat analytic approach in analyzing the one or more objects for malware, and the one or more analytic engines comprises a combination of two or more of any of (1) a static analytic engine to conduct an analysis on content of an object of the one or more objects and generate results including observed features represented by characteristics of the object and the context information associated with the object; (2) a dynamic analytic engine to execute the object and generate results including features represented by observed behaviors of the dynamic analytic engine along with context information accompanying the observed features; (3) a machine learning analytic engine to submit the object as input into a trained machine-learning model and generates results including features represented by insights derived from the machine-learning model and accompanying context information; and (4) an emulation analytic engine to conduct reproduction of operations representing an execution of the object and generate results including features represented by behaviors captured during emulation and accompanying context information; and
reporting logic to receive meta-information associated with results of the cyberthreat analytics conducted by the object evaluation logic on the one or more objects and generate a displayable report including the results.