Abstract: In one embodiment, a device in a network receives an attack mitigation request regarding traffic in the network. The device causes an assessment of the traffic, in response to the attack mitigation request. The device determines that an attack detector associated with the attack mitigation request incorrectly assessed the traffic, based on the assessment of the traffic. The device causes an update to an attack detection model of the attack detector, in response to determining that the attack detector incorrectly assessed the traffic.

Abstract: Techniques and mechanisms for identifying unmanaged cloud resources with endpoint and network logs and attributing the identified cloud resources to an entity of an enterprise that owns the cloud resources. The process collects data from sources, e.g., endpoint and network logs, with respect to traffic in a computer network and based at least in part on the data, extracts relationships related to the traffic. The process applies rules to the relationships to extract destinations in the computer network that provide cloud resources in a cloud environment, wherein the cloud resources are owned by an enterprise. One or more users or business entities of the enterprise are identified as accessing the cloud resources.

Abstract: In one embodiment, a device obtains one or more packets of a traffic session in a network. The device determines, for a particular packet of the one or more packets that match a filter, a fingerprint for the particular packet. The device identifies a plurality of traffic sessions whose packets match the fingerprint, wherein each of the plurality of traffic sessions is associated with at least one process. The device updates a process with the traffic session by applying a classifier to the plurality of traffic sessions.

Abstract: In one embodiment, a service that monitors a network obtains file characteristic data of a file stored on a first endpoint in the network. The service infers characteristics of encrypted content within encrypted traffic in the network between the first endpoint and a second endpoint, by applying a machine learning-based classifier to traffic data regarding the encrypted traffic session. The service compares the file characteristic data of the file to the inferred content characteristics of the encrypted content within the encrypted traffic, to detect the file within the encrypted traffic. The service enforces a network policy in the network, based on the detection of the file within the encrypted traffic.

Abstract: In one embodiment, a device in a network receives certificate data for an encrypted traffic flow associated with a client node in the network. The device determines one or more data features from the certificate data. The device determines one or more flow characteristics of the encrypted traffic flow. The device performs a classification of an application executed by the client node and associated with the encrypted traffic flow by using a machine learning-based classifier to assess the one or more data features from the certificate data and the one or more flow characteristics of the traffic flow. The device causes performance of a network action based on a result of the classification of the application.

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 traffic inspection service executed by an intermediary device obtains, from a monitoring agent executed by an endpoint device, keying information for an encrypted traffic session between the endpoint device and a remote entity. The traffic inspection service provides a notification to the monitoring agent that acknowledges receipt of the keying information. The traffic inspection service uses the keying information to decrypt encrypted traffic from the encrypted traffic session. The traffic inspection service applies a policy to the encrypted traffic session between the endpoint device and the remote entity, based on the decrypted traffic from the session.

Abstract: Techniques and mechanisms for identifying unmanaged cloud resources with endpoint and network logs and attributing the identified cloud resources to an entity of an enterprise that owns the cloud resources. The process collects data from sources, e.g., endpoint and network logs, with respect to traffic in a computer network and based at least in part on the data, extracts relationships related to the traffic. The process applies rules to the relationships to extract destinations in the computer network that provide cloud resources in a cloud environment, wherein the cloud resources are owned by an enterprise. One or more users or business entities of the enterprise are identified as accessing the cloud resources.

Abstract: In one embodiment, a device in a network receives an attack mitigation request regarding traffic in the network. The device causes an assessment of the traffic, in response to the attack mitigation request. The device determines that an attack detector associated with the attack mitigation request incorrectly assessed the traffic, based on the assessment of the traffic. The device causes an update to an attack detection model of the attack detector, in response to determining that the attack detector incorrectly assessed the traffic.

Abstract: This disclosure describes techniques and mechanisms for detecting and alerting on domain fronting within a network using network location context. Popular services are often hosted by multiple CDNs to increase resiliency and decrease latency. The techniques described herein utilize this insight to identify anomalous encrypted sessions by first creating a baseline of domain name resolutions for a given customer site. The techniques may then look for encrypted sessions destined to an IP address that is anomalous for the given domain name and is known to support domain fronting.

Abstract: This disclosure describes techniques and mechanisms for improving blocking and alerting with domain fronting intelligence. The techniques may identify Internet infrastructure that supports domain fronting through passive data collection and active scanning of the data. The results of the active scanning are then used to generate enhanced threat intelligence feeds that associate indicators of compromise with their support of domain fronting. The new feeds are then used to perform more aggressive blocking, raise weak alerts that can be correlated to other alerts, and to create a more secure DNS system by de-prioritizing infrastructure that supports domain fronting for DNS responses.

Abstract: In one embodiment, a traffic inspection service executed by an intermediary device obtains, from a monitoring agent executed by an endpoint device, keying information for an encrypted traffic session between the endpoint device and a remote entity. The traffic inspection service provides a notification to the monitoring agent that acknowledges receipt of the keying information. The traffic inspection service uses the keying information to decrypt encrypted traffic from the encrypted traffic session. The traffic inspection service applies a policy to the encrypted traffic session between the endpoint device and the remote entity, based on the decrypted traffic from the session.

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 device in a network detects an encrypted traffic flow associated with a client in the network. The device captures contextual traffic data regarding the encrypted traffic flow from one or more unencrypted packets associated with the client. The device performs a classification of the encrypted traffic flow by using the contextual traffic data as input to a machine learning-based classifier. The device generates an alert based on the classification of the encrypted traffic flow.

Abstract: In one embodiment, a traffic inspection service executed by an intermediary device obtains, from a monitoring agent executed by an endpoint device, keying information for an encrypted traffic session between the endpoint device and a remote entity. The traffic inspection service provides a notification to the monitoring agent that acknowledges receipt of the keying information. The traffic inspection service uses the keying information to decrypt encrypted traffic from the encrypted traffic session. The traffic inspection service applies a policy to the encrypted traffic session between the endpoint device and the remote entity, based on the decrypted traffic from the session.

Abstract: In one embodiment, a telemetry exporter in a network establishes a tunnel between the telemetry exporter and a traffic analysis service. The telemetry exporter obtains packet copies of a plurality of packets sent between devices via the network. The telemetry exporter forms a set of traffic telemetry data by discarding at least a portion of one or more of the packet copies, based on a filter policy. The telemetry exporter applies compression to the formed set of traffic telemetry data. The telemetry exporter sends, via the tunnel, the compressed set of traffic telemetry data to the traffic analysis service for analysis.

Abstract: Techniques and mechanisms for using passively collected network data to automatically generate a fingerprint prevalence database without the need for endpoint ground truth. The process first clusters all observations with the same fingerprint string and similar source and destination context. The process then annotates each cluster with descriptive information and uses a rule-based system to derive an informative name from that descriptive information, e.g., “winnt amp client” or “cross-platform browser”. Optionally, the learned database may be augmented by a user to clarify custom process labels. Additionally, the generated database may be used to report the inferred processes in the same way as databases generated with endpoint ground truth.

Abstract: In one embodiment, a device in a network detects an encrypted traffic flow associated with a client in the network. The device captures contextual traffic data regarding the encrypted traffic flow from one or more unencrypted packets associated with the client. The device performs a classification of the encrypted traffic flow by using the contextual traffic data as input to a machine learning-based classifier. The device generates an alert based on the classification of the encrypted traffic flow.

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 traffic inspection service executed by an intermediary device obtains, from a monitoring agent executed by an endpoint device, keying information for an encrypted traffic session between the endpoint device and a remote entity. The traffic inspection service provides a notification to the monitoring agent that acknowledges receipt of the keying information. The traffic inspection service uses the keying information to decrypt encrypted traffic from the encrypted traffic session. The traffic inspection service applies a policy to the encrypted traffic session between the endpoint device and the remote entity, based on the decrypted traffic from the session.