Abstract: Detection of user accounts associated with spammer attacks may be performed by constructing a social graph of email users. Biggest connected components (BCC) of the social graph may be used to identify legitimate user accounts, as the majority of the users in the biggest connected components are legitimate users. BCC users may be used to identify more legitimate users. Using degree-based detection techniques and PageRank based detection techniques, the hijacked user accounts and spammer user accounts may be identified. The users' email sending and receiving behaviors may also be examined, and the subgraph structure may be used to detect stealthy attackers. From the social graph analysis, legitimate user accounts, malicious user accounts, and compromised user accounts can be identified.

Abstract: In embodiments of trusted email sender indicators, email messages are received for distribution, and validation techniques can be applied to determine whether a sender of an email message is trusted. If the sender of the email message is determined to be trusted, a trusted sender indicator can be associated with the email message for display with the email message. The trusted sender indicator indicates that the email message is from a trusted sender, such as when the trusted sender indicator is displayed along with the email message at a recipient client device.

Abstract: User account behavior techniques are described. In implementations, a determination is made as to whether interaction with a service provider via a user account deviates from a model. The model is based on behavior that was previously observed as corresponding to the user account. Responsive to a determination that the interaction deviates from the model, the user account is flagged as being potentially compromised by a malicious party.

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: 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: Techniques for managing multiple versions of relational database schema data are described. Schema data associated with multiple versions of a relational database are maintained according to a database schema version management structure. Laws of set theory are applied to the structured database schema data to identify data definition language (DDL) and data manipulation language (DML) scripts that are associated with a particular version of the relational database. The identified scripts are then copied into an installation file that can be executed to create a full install of the particular version of the relational database. Similarly, laws of set theory are applied to the structured database schema data to identify DDL scripts, DML scripts, and drop scripts that are to be applied to upgrade from one version of the relational database to a newer version of the relational database.

Abstract: Automatically determining the conformance of database server schema. Maintaining conformance of database schema helps manage and sustain database driven services and applications. Schema for a pair of randomly selected databases are generated and compared. A diffgram is generated from the difference of the database schema. An alarm message can then be sent to an alarm server with the differences of the comparable databases. A master schema dump can be compared to selected database servers within the database system concurrently with the comparable database pair schema processing. A diffgram is generated in response to the comparison between the selected database schema and the master schema.

Abstract: Techniques for managing multiple versions of relational database schema data are described. Schema data associated with multiple versions of a relational database are maintained according to a database schema version management structure. Laws of set theory are applied to the structured database schema data to identify data definition language (DDL) and data manipulation language (DML) scripts that are associated with a particular version of the relational database. The identified scripts are then copied into an installation file that can be executed to create a full install of the particular version of the relational database. Similarly, laws of set theory are applied to the structured database schema data to identify DDL scripts, DML scripts, and drop scripts that are to be applied to upgrade from one version of the relational database to a newer version of the relational database.