Abstract: An endpoint security agent facilitates a security policy on an endpoint computing device. The endpoint agent comprises an engine and one or more plugins that each provide a particular security feature. The endpoint agent receives a policy from a cloud server specifying one or more plug-ins used by the policy and configuration of those plug-ins. The endpoint agent retrieves, installs, and configures the one or more plugins. The endpoint agent updates a communication table with command subscription information obtained from each installed plugin indicating command types subscribed to by each plug-in. When a command is received, a lookup of the command type is performed in the table, and the command is sent to the subscribing plugin.

Abstract: A scalable cloud-based endpoint security system facilitates a security policy on a plurality of endpoints. Configuration data or commands for implementing a security policy are entered via a web browser of an administrative client device and received at a cloud server. An API server generates a message to a queue of a publication/subscription server that publishes the messages from the queue to one or more subscribing communication servers. A communication server sends the message to an endpoint targeted by the message via a persistent connection that the communication server maintains with the endpoint. In response to the message, the endpoint establishes a connection to the API server. The API server then distributes the configuration data or commands to the endpoint.

Abstract: Client devices detect malware based on a ruleset received from a security server. To evaluate a current ruleset, an administrative client device initiates a ruleset evaluation of the malware detection ruleset. A security server partitions stored malware samples into a group of evaluation lists based on an evaluation policy. The security server then creates scanning nodes on an evaluation server according to the evaluation policy. The scanning nodes scan the malware samples of the evaluation lists using the rulesets and associate each malware sample with a rule of the ruleset based on the detections, if any. The security server analyzes the associations and optimizes the ruleset and stored malware samples. The security server sends the optimized ruleset to client devices such that they more efficiently detect malware samples.

Abstract: An endpoint security agent facilitates a security policy on an endpoint computing device. The endpoint agent comprises an engine and one or more plugins that each provide a particular security feature. The endpoint agent receives a policy from a cloud server specifying one or more plug-ins used by the policy and configuration of those plug-ins. The endpoint agent retrieves, installs, and configures the one or more plugins. The endpoint agent updates a communication table with command subscription information obtained from each installed plugin indicating command types subscribed to by each plug-in. When a command is received, a lookup of the command type is performed in the table, and the command is sent to the subscribing plugin.

Abstract: A security server tracks malicious objects detected by malware detection applications that scan for malicious objects on clients. The security server also receives client information from the clients indicating client states. The client state describes one or more protection applications executing on the client that seek to identify and prevent malicious objects from taking malicious actions based on real-time monitoring. Thus, the security server may identify when the protection application fails to detect a malicious object. In addition, the security server maps detection events of malicious objects with corresponding client states to generate aggregate detection information for a population of clients. Analytical data can be derived from the aggregate detection information to identify trends useful for evaluating different types of protection applications.

Abstract: A protection application detects and removes unwanted applications. The protection application scans a client device for suspected unwanted applications. A security server provides an application rating for detected applications to the client device. The application rating is generated based on application retention data received from client devices indicating whether users of the clients choose to remove or retain the application when given the option. The application retention data may be weighed based on a categorization of the clients providing the application retention data into to clients expected to have different reliability levels. The security server can also provide a definition specifying all known components associated with a suspected unwanted application. Responsive to a selection to remove a suspected unwanted application, the protection application uninstalls all components of the application.

Abstract: An anti-malware application detects and remediates ransomware. The anti-malware application monitors processes executing on a computing device and detects that a process is opening a file for editing. A portion of the original file is saved prior to being edited by the process. Once the edited file is saved, the anti-malware application compares a portion of the edited file to the portion of the original file to determine if the edited file is encrypted. The anti-malware application may determine the process is associated with ransomware based on whether the edited file is encrypted.

Abstract: An anti-malware application analyzes behavior of an executing process to identify ransomware. The anti-malware application detects an untrusted process requesting enumeration of a directory of user files and causes the untrusted process to initially operate on a decoy file that mimics the user files. If the behavior of the untrusted process with respect to the decoy file is indicative of ransomware, the process can be terminated without loss of the user files. The decoy file may be deployed in a way that is undetectable to the user.

Abstract: Client devices detect malware based on a ruleset received from a security server. To evaluate a current ruleset, an administrative client device initiates a ruleset evaluation of the malware detection ruleset. A security server partitions stored malware samples into a group of evaluation lists based on an evaluation policy. The security server then creates scanning nodes on an evaluation server according to the evaluation policy. The scanning nodes scan the malware samples of the evaluation lists using the rulesets and associate each malware sample with a rule of the ruleset based on the detections, if any. The security server analyzes the associations and optimizes the ruleset and stored malware samples. The security server sends the optimized ruleset to client devices such that they more efficiently detect malware samples.

Abstract: A protection application detects and remediates malicious files on a client. The protection application trains models using known samples of static clean files, and the models characterize features of the clean files. A model may be selected based on metadata obtained from a target file. By processing features of the clean files and features of the target file, the model may generate an anomaly score indicating a level of dissimilarity between the target file and the sample. The protection application compares the anomaly score to one or more threshold scores to classify the target file. Additionally, the target file may be provided to a security server to check against a whitelist or blacklist for classification. Responsive to a classification as malicious, the protection application remediates the target file on the client.

Abstract: An anti-malware application detects, stops, and quarantines ransomware. The anti-malware application monitors threads executing on a computing device and detects behaviors that conform to a predefined set of behaviors indicative of ransomware. Responsive to detecting these behaviors, indicators are stored to a log in a storage device. Each of the indicators in the log is associated with respective scores. A running score for each thread is generated by combining the respective scores of the indicators in the log. Responsive to determining that the running score exceeds a predefined threshold score, execution of the thread is terminated. The source ransomware file is then identified and quarantined.

Abstract: A scalable cloud-based endpoint security system facilitates a security policy on a plurality of endpoints. Configuration data or commands for implementing a security policy are entered via a web browser of an administrative client device and received at a cloud server. An API server generates a message to a queue of a publication/subscription server that publishes the messages from the queue to one or more subscribing communication servers. A communication server sends the message to an endpoint targeted by the message via a persistent connection that the communication server maintains with the endpoint. In response to the message, the endpoint establishes a connection to the API server. The API server then distributes the configuration data or commands to the endpoint.

Abstract: A protection application detects and removes unwanted applications. The protection application scans a client device for suspected unwanted applications. A security server provides an application rating for detected applications to the client device. The application rating is generated based on application retention data received from client devices indicating whether users of the clients choose to remove or retain the application when given the option. The application retention data may be weighed based on a categorization of the clients providing the application retention data into to clients expected to have different reliability levels. The security server can also provide a definition specifying all known components associated with a suspected unwanted application. Responsive to a selection to remove a suspected unwanted application, the protection application uninstalls all components of the application.

Abstract: An anti-malware application detects, stops, and quarantines ransomware. The anti-malware application monitors threads executing on a computing device and detects behaviors that conform to a predefined set of behaviors indicative of ransomware. Responsive to detecting these behaviors, indicators are stored to a log in a storage device. Each of the indicators in the log is associated with respective scores. A running score for each thread is generated by combining the respective scores of the indicators in the log. Responsive to determining that the running score exceeds a predefined threshold score, execution of the thread is terminated. The source ransomware file is then identified and quarantined.