Abstract: Message management and classification techniques are described. In one or more implementations, a message received from a sender for delivery via a user account is examined to extract one or more features of the message. A determination is then made as to whether the message corresponds to one or more categories based on the extracted features, the categories usable to enable features to be applied to the message in a user interface.

Abstract: Email tags are described. In embodiments, email messages are received for distribution to client devices that correspond to respective recipients of the email messages. Email routing decisions are applied to route an email message to an email folder for a recipient of the email message, where the email folder may include an email inbox, a junk folder, or a user-created folder. The email message is then tagged with an email tag to generate a tagged email message. The email tag includes a routing description that indicates why the email message was routed to the particular email folder.

Abstract: Email tags are described. In embodiments, email messages are received for distribution to client devices that correspond to respective recipients of the email messages. Email routing decisions are applied to route an email message to an email folder for a recipient of the email message, where the email folder may include an email inbox, a junk folder, or a user-created folder. The email message is then tagged with an email tag to generate a tagged email message. The email tag includes a routing description that indicates why the email message was routed to the particular email folder.

Abstract: Message management and classification techniques are described. In one or more implementations, a message received from a sender for delivery via a user account is examined to extract one or more features of the message. A determination is then made as to whether the message corresponds to one or more categories based on the extracted features, the categories usable to enable features to be applied to the message in a user interface.

Abstract: The subject invention provides for an advanced and robust system and method that facilitates detecting spam. The system and method include components as well as other operations which enhance or promote finding characteristics that are difficult for the spammer to avoid and finding characteristics in non-spam that are difficult for spammers to duplicate. Exemplary characteristics include analyzing character and/or number sequences, strings, and sub-strings, detecting various entropy levels of one or more character sequences, strings and/or sub-strings and analyzing message headers.

Abstract: Message management and classification techniques are described. In one or more implementations, a message received from a sender for delivery via a user account is examined to extract one or more features of the message. A determination is then made as to whether the message corresponds to one or more categories based on the extracted features, the categories usable to enable features to be applied to the message in a user interface.

Abstract: Geo-data spam filters are described. In one or more implementations, origin data and language data of a message are evaluated to establish a score for the message indicating a likelihood that the message is spam. The evaluation includes comparing the origin data and the language data to ranked lists indicating message origins and languages with which a respective message recipient interacts positively and ranked lists indicating message origins and languages with which the respective recipient interacts negatively. Interactions of the respective recipient with previously sent messages may be tracked to form these lists. Based on the score established by evaluating the origin data and the language data of the message, the message is filtered for delivery.

Abstract: The filtering of activities generated by nodes of a network while interacting with a device may be performed by evaluating the desirability of the activities (e.g., a spam or not-spam determination of email messages sent by the node) and assigning a trust rating to the node. However, nodes are often identified by network address, and an operator of a node sending undesirable activities may reassign the network address of the node in order to avoid heavy filtering. Instead, nodes may be identified as being controlled by a network entity (e.g., an autonomous system identified in a border gateway protocol routing table.) The network entity is assigned a network entity trust rating based on the trust ratings of the nodes controlled thereby, and an appropriate level of activity filtering based on the network entity trust rating may be selected for subsequent activities received from all nodes controlled by the network entity.

Abstract: Campaign detection techniques are described. In implementations, a signature is computed for each of a plurality of emails to be communicated by a service provider to respective intended recipients. A determination is made that two or more of the plurality of emails is similar based on the respective signatures. Responsive to a finding that a number of similar emails exceeds a threshold, an indication is output that the similar emails have a likelihood of being involved in a spam campaign.

Abstract: A computer implemented method for filtering unwanted bulk email in an email system and providing a positive user experience is provided. The method enables protection of email users from unsolicited bulk email using user-provided data on user interactions at both a user storage level and a global level with an email system. Metadata on user interactions with messages is collected. Messages are received by the system and evaluated using a global filter which assigns a score resulting in a message action. The action may be message delivery, message non-delivery or message routing, based on a score assigned by the global filter. When the message is delivered to user storage, the message may be examined relative to the metadata, and may alter the message action to an action different than the message action resulting from the score. Metadata for a plurality of users is returned to the global filter for use in making filtering future messages and modifies the global filter.

Abstract: A system and method of managing unsolicited email sent to an email system over a network. Email messages are received at an message at an inbound mail transfer agent. A determination is made as to whether the email message is suspected to be an unsolicited suspect message. One or more queries for additional information on one or more characteristics of the message is initiated. Determinations are made based on replies to the queries before issuing a message accepted for delivery indication to a sending server.

Abstract: Email tags are described. In embodiments, email messages are received for distribution to client devices that correspond to respective recipients of the email messages. Email routing decisions are applied to route an email message to an email folder for a recipient of the email message, where the email folder may include an email inbox, a junk folder, or a user-created folder. The email message is then tagged with an email tag to generate a tagged email message. The email tag includes a routing description that indicates why the email message was routed to the particular email folder.

Abstract: Email tags are described. In embodiments, email messages are received for distribution to client devices that correspond to respective recipients of the email messages. Email routing decisions are applied to route an email message to an email folder for a recipient of the email message, where the email folder may include an email inbox, a junk folder, or a user-created folder. The email message is then tagged with an email tag to generate a tagged email message. The email tag includes a routing description that indicates why the email message was routed to the particular email folder.

Abstract: A computer implemented system and method to enable protection of email users from unsolicited bulk email using a message delivery delay based on characteristics detected in selected messages. Messages are evaluated for characteristics resembling unsolicited bulk email. A determination is made whether a message passing through the email system exhibits such characteristics and whether to delay the message. Suspect messages may be delayed for a period of time, the delay period being dependent on the characteristics giving rise to a determination to delay. Following the period, additional information received during the delay period characterizing the message is used to determine whether to dispose or deliver the message. Messages evaluated can be inbound to the email system, outbound to other email systems, or moving within the email system.

Abstract: Trusted user accounts of an application provider are determined. Graphs, such as trees, are created with each node corresponding to a trusted account. Each of the nodes is associated with a vouching quota, or the nodes may share a vouching quota. Untrusted user accounts are determined. For each of these untrusted accounts, a trusted user account that has a social networking relationship is determined. If the node corresponding to the trusted user account has enough vouching quota to vouch for the untrusted user account, then the quota is debited, a node is added for the untrusted user account to the graph, and the untrusted user account is vouched for. If not, available vouching quota may be borrowed from other nodes in the graph.

Abstract: Geo-data spam filters are described. In one or more implementations, origin data and language data of a message are evaluated to establish a score for the message indicating a likelihood that the message is spam. The evaluation includes comparing the origin data and the language data to ranked lists indicating message origins and languages with which a respective message recipient interacts positively and ranked lists indicating message origins and languages with which the respective recipient interacts negatively. Interactions of the respective recipient with previously sent messages may be tracked to form these lists. Based on the score established by evaluating the origin data and the language data of the message, the message is filtered for delivery.

Abstract: Geo-data spam filters are described. In one or more implementations, origin data and language data of a message are evaluated to establish a score for the message indicating a likelihood that the message is spam. The evaluation includes comparing the origin data and the language data to ranked lists indicating message origins and languages with which a respective message recipient interacts positively and ranked lists indicating message origins and languages with which the respective recipient interacts negatively. Interactions of the respective recipient with previously sent messages may be tracked to form these lists. Based message, the message is filtered for delivery.

Abstract: In embodiments of an email trust service, an email message is received at an email distribution service for distribution to a client device that corresponds to a recipient of the email message. Authentication techniques can be applied to verify that the email message is received from an authorized domain as specified in a sender address field of the email message. Additionally, it can be determined whether an Extended Validation certificate is associated with the authorized domain. Responsive to determining that an Extended Validation certificate is associated with the authorized domain, a trust indicator is associated with the email message to generate a trusted email message. The trust indicator indicates that the trusted email message is from an authorized domain when the email message is displayed at the client device.

Abstract: The subject invention provides for an advanced and robust system and method that facilitates detecting spam. The system and method include components as well as other operations which enhance or promote finding characteristics that are difficult for the spammer to avoid and finding characteristics in non-spam that are difficult for spammers to duplicate. Exemplary characteristics include examining origination features in pairs, analyzing character and/or number sequences, strings, and sub-strings, detecting various entropy levels of one or more character sequences, strings and/or sub-strings as well as analyzing message and/or feature sizes.

Abstract: The subject invention provides for an advanced and robust system and method that facilitates detecting spam. The system and method include components as well as other operations which enhance or promote finding characteristics that are difficult or the spammer to avoid and finding characteristics in non-spam that are difficult for spammers to duplicate. Exemplary characteristics include examining origination features in pairs, analyzing character and/or number sequences, strings, and sub-strings, detecting various entropy levels of one or more character sequences, strings and/or sub-strings as well as analyzing message and/or feature sizes.