Abstract: In one embodiment, a service receives administration traffic data in a network associated with a remote administration session in which a control device remotely administers a client device. The service analyzes the administration traffic data to determine whether any portion of the administration traffic data is resulting from an administration session involving a trusted administrator. The service flags a first portion of the administration traffic data as authorized when the first portion of the administration traffic data is determined to result from an administration session involving a trusted administrator, and a second portion of the administration traffic data is non-flagged. The service assesses the second portion of the administration traffic data using a machine learning-based traffic classifier to determine whether the second portion of the administration traffic data is malicious.

Abstract: In one embodiment, a service receives administration traffic data in a network associated with a remote administration session in which a control device remotely administers a client device. The service analyzes the administration traffic data to determine whether any portion of the administration traffic data is resulting from an administration session involving a trusted administrator. The service flags a first portion of the administration traffic data as authorized when the first portion of the administration traffic data is determined to result from an administration session involving a trusted administrator, and a second portion of the administration traffic data is non-flagged. The service assesses the second portion of the administration traffic data using a machine learning-based traffic classifier to determine whether the second portion of the administration traffic data is malicious.

Abstract: In one embodiment, a service receives administration traffic data in a network associated with a remote administration session in which a control device remotely administers a client device. The service analyzes the administration traffic data to determine whether any portion of the administration traffic data is resulting from an administration session involving a trusted administrator. The service flags a first portion of the administration traffic data as authorized when the first portion of the administration traffic data is determined to result from an administration session involving a trusted administrator, and a second portion of the administration traffic data is non-flagged. The service assesses the second portion of the administration traffic data using a machine learning-based traffic classifier to determine whether the second portion of the administration traffic data is malicious.

Abstract: In one embodiment, a service receives administration traffic data in a network associated with a remote administration session in which a control device remotely administers a client device. The service analyzes the administration traffic data to determine whether any portion of the administration traffic data is resulting from an administration session involving a trusted administrator. The service flags a first portion of the administration traffic data as authorized when the first portion of the administration traffic data is determined to result from an administration session involving a trusted administrator, and a second portion of the administration traffic data is non-flagged. The service assesses the second portion of the administration traffic data using a machine learning-based traffic classifier to determine whether the second portion of the administration traffic data is malicious.

Abstract: In one embodiment, a service receives captured traffic flow data regarding a traffic flow sent via a network between a first device assigned to a first network zone and a second device assigned to a second network zone. The service identifies, from the captured traffic flow data, one or more cryptographic parameters of the traffic flow. The service determines whether the one or more cryptographic parameters of the traffic flow satisfy an inter-zone policy associated with the first and second network zones. The service causes performance of a mitigation action in the network when the one or more cryptographic parameters of the traffic flow do not satisfy the inter-zone policy associated with the first and second network zones.

Abstract: In one embodiment, a service receives administration traffic data in a network associated with a remote administration session in which a control device remotely administers a client device. The service analyzes the administration traffic data to determine whether any portion of the administration traffic data is resulting from an administration session involving a trusted administrator. The service flags a first portion of the administration traffic data as authorized when the first portion of the administration traffic data is determined to result from an administration session involving a trusted administrator, and a second portion of the administration traffic data is non-flagged. The service assesses the second portion of the administration traffic data using a machine learning-based traffic classifier to determine whether the second portion of the administration traffic data is malicious.

Abstract: In one embodiment, a service receives administration traffic data in a network associated with a remote administration session in which a control device remotely administers a client device. The service analyzes the administration traffic data to determine whether any portion of the administration traffic data is resulting from an administration session involving a trusted administrator. The service flags a first portion of the administration traffic data as authorized when the first portion of the administration traffic data is determined to result from an administration session involving a trusted administrator, and a second portion of the administration traffic data is non-flagged. The service assesses the second portion of the administration traffic data using a machine learning-based traffic classifier to determine whether the second portion of the administration traffic data is malicious.

Abstract: In one embodiment, a service receives administration traffic data in a network associated with a remote administration session in which a control device remotely administers a client device. The service analyzes the administration traffic data to determine whether any portion of the administration traffic data is resulting from an administration session involving a trusted administrator. The service flags a first portion of the administration traffic data as authorized when the first portion of the administration traffic data is determined to result from an administration session involving a trusted administrator, and a second portion of the administration traffic data is non-flagged. The service assesses the second portion of the administration traffic data using a machine learning-based traffic classifier to determine whether the second portion of the administration traffic data is malicious.

Abstract: In one embodiment, a service receives data regarding administration traffic in a network associated with a remote administration session in which a control device remotely administers a client device. The service analyzes the received data to determine whether the administration traffic is authorized. The service flags the received data as authorized, based on the analysis of the received data. The service uses the data flagged as authorized to distinguish between benign traffic and malicious traffic in the network.

Abstract: In one embodiment, a service receives captured traffic flow data regarding a traffic flow sent via a network between a first device assigned to a first network zone and a second device assigned to a second network zone. The service identifies, from the captured traffic flow data, one or more cryptographic parameters of the traffic flow. The service determines whether the one or more cryptographic parameters of the traffic flow satisfy an inter-zone policy associated with the first and second network zones. The service causes performance of a mitigation action in the network when the one or more cryptographic parameters of the traffic flow do not satisfy the inter-zone policy associated with the first and second network zones.

Abstract: In one embodiment, a service receives captured traffic flow data regarding a traffic flow sent via a network between a first device assigned to a first network zone and a second device assigned to a second network zone. The service identifies, from the captured traffic flow data, one or more cryptographic parameters of the traffic flow. The service determines whether the one or more cryptographic parameters of the traffic flow satisfy an inter-zone policy associated with the first and second network zones. The service causes performance of a mitigation action in the network when the one or more cryptographic parameters of the traffic flow do not satisfy the inter-zone policy associated with the first and second network zones.

Abstract: In one example embodiment, a server obtains network flow metadata of a network flow of a host in a network. The server identifies one or more attributes of the network flow metadata. For each host group of a plurality of host groups, the server determines whether the one or more attributes of the network flow metadata satisfy one or more criteria for the host group. For each host group for which it is determined that the one or more attributes of the network flow metadata satisfy the one or more criteria, the server classifies the host as belonging to the host group.

Abstract: In one embodiment, a service receives captured traffic flow data regarding a traffic flow sent via a network between a first device assigned to a first network zone and a second device assigned to a second network zone. The service identifies, from the captured traffic flow data, one or more cryptographic parameters of the traffic flow. The service determines whether the one or more cryptographic parameters of the traffic flow satisfy an inter-zone policy associated with the first and second network zones. The service causes performance of a mitigation action in the network when the one or more cryptographic parameters of the traffic flow do not satisfy the inter-zone policy associated with the first and second network zones.

Abstract: In one embodiment, a service receives data regarding administration traffic in a network associated with a remote administration session in which a control device remotely administers a client device. The service analyzes the received data to determine whether the administration traffic is authorized. The service flags the received data as authorized, based on the analysis of the received data. The service uses the data flagged as authorized to distinguish between benign traffic and malicious traffic in the network.