Abstract: Systems, methods, and apparatuses enable a machine learning model to determine a risk probability of a URL. A query configurator receives a URL in a query and normalizes the URL. The normalized URL is segmented into a plurality of segments. The plurality of segments is serially provided to the machine learning model trained to provide an indication of risk associated with the URL. The indication of risk associated with the URL can be a probability value based on one or more risk probabilities determined for segment-segment transitions of the URL. A security service compares the probability value of the URL to a threshold value and performs a security action based on a result of comparing the probability value to the threshold value.

Abstract: Systems, methods, and apparatuses enable one or more security microservices to optimize a security configuration of a networked environment by applying security policies to resource groups passively to determine whether network sets, resource groups, or security policies should be modified, prior to active enforcement. When security policies are applied passively, security actions that are performed in response to a violation of security policy do not impact network traffic. The one or more security microservices evaluate the results of the passive application of security policies to determine whether there is at least one recommended modification to network sets, resource groups, or security policies. When there is at least one recommended modification, the modification is applied.

Abstract: Systems, methods, and apparatuses enable a machine learning model to determine a risk probability of a URL. A query configurator receives a URL in a query and normalizes the URL. The normalized URL is segmented into a plurality of segments. The plurality of segments is serially provided to the machine learning model trained to provide an indication of risk associated with the URL. The indication of risk associated with the URL can be a probability value based on one or more risk probabilities determined for segment-segment transitions of the URL. A security service compares the probability value of the URL to a threshold value and performs a security action based on a result of comparing the probability value to the threshold value.

Abstract: Systems, methods, and apparatuses enable a security orchestrator to detect a virtual machine deployed in a virtual environment. The virtual machine includes a tag storing information associated with the virtual machine. The security orchestrator determines that the tag contains one or more security elements, the security elements indicating information for determining security settings and policies to be applied to the virtual machine. The security orchestrator determines the security settings and policies associated with the one or more security elements. The security orchestrator then assigns or applies the security settings and policies for the virtual machine based on values of the one or more security elements.

Abstract: Systems, methods, and apparatuses enable one or more security microservices to optimize a security configuration of a networked environment by applying security policies to resource groups passively to determine whether network sets, resource groups, or security policies should be modified, prior to active enforcement. When security policies are applied passively, security actions that are performed in response to a violation of security policy do not impact network traffic. The one or more security microservices evaluate the results of the passive application of security policies to determine whether there is at least one recommended modification to network sets, resource groups, or security policies. When there is at least one recommended modification, the modification is applied.

Abstract: Systems, methods, and apparatuses enable deploying and executing a security policy on endpoints in a network. In an embodiment, a security orchestrator determines a set of endpoints in a network and determines transformed endpoints from the determined set of endpoints through an endpoint transformation process. The security orchestrator determines a connectivity vector for at least a first transformed endpoint and a second transformed endpoint, where the connectivity vector includes properties associated with the corresponding transformed endpoint. Using the properties from the connectivity vector of the first transformed endpoint, a security policy is generated and deployed to the first transformed endpoint. Based on a comparison of the connectivity vectors of the first and second transformed endpoints indicating a similarity between the first and second transformed endpoints, the security policy is further deployed to the second transformed endpoint.

Abstract: Systems, methods, and apparatuses enable a machine learning model to determine a risk probability of a URL. A query configurator receives a URL in a query and normalizes the URL. The normalized URL is segmented into a plurality of segments. The plurality of segments is serially provided to the machine learning model trained to provide an indication of risk associated with the URL. The indication of risk associated with the URL can be a probability value based on one or more risk probabilities determined for segment-segment transitions of the URL. A security service compares the probability value of the URL to a threshold value and performs a security action based on a result of comparing the probability value to the threshold value.

Abstract: Systems, methods, and apparatuses enable a security orchestrator to detect a virtual machine deployed in a virtual environment. The virtual machine includes a tag storing information associated with the virtual machine. The security orchestrator determines that the tag contains one or more security elements, the security elements indicating information for determining security settings and policies to be applied to the virtual machine. The security orchestrator determines the security settings and policies associated with the one or more security elements. The security orchestrator then assigns or applies the security settings and policies for the virtual machine based on values of the one or more security elements.

Abstract: Systems, methods, and apparatuses enable deploying and executing a security policy on endpoints in a network. In an embodiment, a security orchestrator determines a set of endpoints in a network and determines transformed endpoints from the determined set of endpoints through an endpoint transformation process. The security orchestrator determines a connectivity vector for at least a first transformed endpoint and a second transformed endpoint, where the connectivity vector includes properties associated with the corresponding transformed endpoint. Using the properties from the connectivity vector of the first transformed endpoint, a security policy is generated and deployed to the first transformed endpoint. Based on a comparison of the connectivity vectors of the first and second transformed endpoints indicating a similarity between the first and second transformed endpoints, the security policy is further deployed to the second transformed endpoint.

Abstract: In one embodiment, a method is provided and includes capturing a plurality of packet streams, recreating a plurality of flows from the packet streams, and analyzing the flows to identify one or more incidents. The incidents identify one or more pieces of data. The incidents are filtered and the incidents are rendered on a display for an end user that initiated the filtering operation. In other embodiments, the display allows the end user to view a selected one of a group of attributes for the incidents. The display allows the end user to open a captured object associated with a specific incident. In still other embodiments, the display allows a user to filter the incidents using a selected one of a group of group options such as content, destination IP, destination location, destination port, filename, host IP, etc.

Abstract: In one embodiment, a method is provided and includes capturing a plurality of packet streams, recreating a plurality of flows from the packet streams, and analyzing the flows to identify one or more incidents. The incidents indentify one or more pieces of data. The incidents are filtered and the incidents are rendered on a display for an end user that initiated the filtering operation. In other embodiments, the display allows the end user to view a selected one of a group of attributes for the incidents. The display allows the end user to open a captured object associated with a specific incident. In still other embodiments, the display allows a user to filter the incidents using a selected one of a group of group options such as content, destination IP, destination location, destination port, filename, host IP, etc.