Abstract: In communication with networked electronic devices, a method for providing a holistic view of a malware attack potentially being conducted on these networked electronic devices is described. The method includes requesting analytic data from each of the plurality of networked electronic devices. Thereafter, the analytic data from each of the networked electronic devices is analyzed to correlate analytic data from each of the plurality of networked electronic devices in order to provide the holistic view of a malware attack potentially being conducted. After correlation, display information is generated, where the display information includes the correlated analytic data.

Abstract: A computerized method for analyzing a subject URL to determine whether the subject URL is associated with a phishing attack is disclosed. The method includes steps of detecting keypoints within a screenshot of a webpage corresponding to the subject URL and determining a set of confidences based on an analysis of the detected keypoints with a model. Each confidence within the set of confidences is assigned to feature vector within a set of training feature vectors representing a training set of URLs used in generating the model. The method comprises performing an image comparison between the screenshot and a screenshot corresponding to a feature vector within the set of training feature vectors, the feature vector being assigned a highest confidence. Responsive to determining the image comparison result exceeds a predefined threshold, transmitting an alert indicating that the subject URL is associated with the phishing attack.

Abstract: According to one embodiment, a computerized method comprises detecting a malicious attack on an enterprise network, where the enterprise network comprises a plurality of network devices. Upon detection of a malicious attack, information (metadata) associated with the malicious attack is gathered. Examples of the information may include at least a geographic location associated with each of the plurality of network devices. Thereafter, an interactive display of a propagation of malware associated the malicious attack is generated. The interactive display includes a plurality of display items representative of the plurality of network devices, each of the plurality of display items is selectable to provide information as to at least one of (i) an origin of the malware, (ii) an entry point of the malware into an enterprise network, or (iii) a targeted destination of the malware.

Abstract: A computerized method for authenticating access to a subscription-based service to detect an attempted cyber-attack. The method features operations by the cloud broker that include receiving service policy level information and information based on operational metadata. The service policy level information includes at least subscription attributes to identify one or more performance criterion in analyses conducted on one or more objects submitted by a sensor for malware representing an attempted cyber-attack. The operational metadata includes metadata that pertains to an operating state of one or more clusters of a plurality of clusters of the subscription-based service. The cloud broker, using both the service policy level information and the information based on the operational metadata, selecting a cluster of the plurality of clusters to analyze the one or more objects submitted by the sensor and establishes a communication session between the sensor and the cluster via the cloud broker.

Abstract: A method performed by an enterprise search system to conduct an automated, computerized search for select operational attributes of a plurality of network devices is shown. The method comprises initiating the search via a user interface based on receipt of input information, which is used to form a query. The method then determines based on the query, one or more audits each specifying one or more tasks to be performed by at least a first network device to search for the select operational attributes. Subsequently, the method makes the one or more audits available to the first network device via a network, and receives, from the first network device, one or more responses to the query. The method may include generating one or more filter conditions to apply to results of executing the one or more tasks to yield the select operational attributes when included in the results.

Abstract: According to one embodiment, a malware detection system is integrated with at least a static analysis engine and a dynamic analysis engine. The static analysis engine is configured to automatically determine an object type of a received object. The dynamic analysis engine is configured to automatically launch the object after selecting an action profile based on the object type. The dynamic analysis engine is further configured to, provide simulated user interaction to the object based on the selected action profile either in response to detecting a request for human interaction or as a result of a lapse of time since a previous simulated human interaction was provided.

Abstract: A graphical user interface provides network security administrators a tool to quickly and easily create one or more courses of action for automatic response to a network threat. The courses of action are hardware and system agnostic, which allows a common response task to be implemented by an underlying response engine for any or multiple similar-function devices regardless of brand or version. The course of action builder allows the administrator to use a simple, graphic-based, business modeling concept to craft and design security response processes rather than having to hard code response routines specific to each piece of hardware on the network. The graphic interface model allows the user of the threat response software incorporating the course of action builder to easily understand the overall flow and paths the response may take, as well as understand the data requirements and dependencies that will be evaluated.

Abstract: A computerized method is described for authenticating access to a subscription-based service to detect an attempted cyber-attack. First, a request is received by a subscription review service to subscribe to the subscription-based service. The service is configured to analyze one or more objects for a potential presence of malware representing the attempted cyber-attack. Using service policy level information, the cloud broker selects a cluster from a plurality of clusters to analyze whether the one or more objects are associated with the attempted cyber-attack and establishes a communication session between the sensor and the cluster via the cloud broker. The service policy level information is associated with the customer and is used in accessing the subscription-based service. The service policy level information includes at least an identifier assigned to the customer.

Abstract: A scalable, malware detection system features at least one sensor and a cluster including at least one computing node. The computing node includes an analysis coordination system and an object analysis system. The analysis coordination system, when activated as a broker computing node, (i) receives metadata from a sensor, (ii) analyzes the metadata, and (iii) places at least a portion of the metadata into a data store for subsequent use in retrieval of the suspicious object by the object analysis system from the sensor. The object analysis system is configured to (i) retrieve the portion of the metadata, which includes at least a sensor identifier, from the data store, (ii) retrieve the suspicious object from the sensor using at least part of the portion of the metadata retrieved from the data store, and (iii) analyze the suspicious object for malware.

Abstract: According to one embodiment, a computerized method is directed to neutralizing callback malware. This method involves intercepting a message directed to an endpoint device, where the message is in response to a callback message sent from callback malware operating on the endpoint device. Thereafter, a first portion of information within the message is substituted with a second portion of information. The second portion of information includes code that is configured to overwrite at least a portion of the callback malware and cause the callback malware to become inoperable or mitigate its operability.

Abstract: An electronic message is analyzed for malware contained in the message. Text of an electronic message may be analyzed to detect and process malware content in the electronic message itself. The present technology may analyze an electronic message and attachments to electronic messages to detect a uniform resource location (URL), identify whether the URL is suspicious, and analyze all suspicious URLs to determine if they are malware. The analysis may include re-playing the suspicious URL in a virtual environment which simulates the intended computing device to receive the electronic message. If the re-played URL is determined to be malicious, the malicious URL is added to a black list which is updated throughout the computer system.

Abstract: The disclosure is directed towards systems and methods for improving security in a computer network. The system can include a planner and a plurality of controllers. The controllers can be deployed within each zone of the production network. Each controller can be configured to assume the role of an attacker or a target for malicious network traffic. Simulations of malicious behavior can be performed by the controllers within the production network, and can therefore account for the complexities of the production network, such as stateful connections through switches, routers, and other intermediary devices. In some implementations, the planner can analyze data received from the controllers to provide a holistic analysis of the overall security posture of the production network.

Abstract: A computerized method that assists in preventing malware from evading detection through analysis of the virtual hardware components operating within a malware detection system is described. First, a virtual machine (VM) is provisioned in accordance with a guest image, which includes a guest operating system and one or more virtual hardware component. The virtual hardware component including an identifier, and the guest operating system includes a software driver that controls access to the virtual hardware component and features the identifier of the virtual hardware component. Responsive to processing an object within the VM and issuance of a request for an identifier of a hardware component, the identifier of the first virtualized hardware component (virtualization of the hardware component) is received. The first identifier of the first virtual hardware component being an identifier substituted for a prior identifier of the first virtual hardware component before creation of the guest image.

Abstract: An architecture deployed to facilitate real-time security analysis, including exploit detection and threat intelligence, of operating system (OS) processes executed by a central processing unit (CPU). The architecture features memory configured to store a process, an OS kernel, a VMM and a virtualization module. The virtualization module is configured to communicate with the VMM and execute, at a privilege level of the CPU, to control access permissions to kernel resources accessible by the process. The VMM is configured to execute at a first privilege level of the virtualization module to expose the kernel resources to the OS kernel. The OS kernel is configured to execute at a second privilege level lower than the first privilege level of the virtualization module. The VMM is further configured to instantiate a virtual machine containing the OS kernel, where access to the kernel resources is controlled by the VMM and the virtual machine.

Abstract: A computerized method is described that is adapted to compare extracted features of a received object under analysis with one or more features associated with each known malicious object of a plurality of known malicious objects accessible to the one or more servers. Responsive to determining that the extracted features satisfy a prescribed level of correlation with the one or more features of a first known malicious object of the plurality of known malicious objects, identifying the received object as a malicious object. Also, responsive to determining that the extracted features fail to satisfy the prescribed level of correlation, conducting a second analysis that includes a comparison of the extracted features to the one or more features associated with each of the plurality of known malicious objects being of a type of malware other than malware targeting a specific entity.

Abstract: Disclosed is a cyber-security system that is configured to aggregate and unify data from multiple components and platforms on a network. The system allows security administrators can to design and implement a workflow of device-actions taken by security individuals in response to a security incident. Based on the nature of a particular threat, the cyber-security system may initiate an action plan that is tailored to the security operations center and their operating procedures to protect potentially impacted components and network resources.

Abstract: A computing device features one or more hardware processors and a memory that is coupled to the one or more processors. The memory comprises software that is implemented with a security mechanism to protect the availability of a software component operating within a virtual machine, which is controlled by a guest operating system (OS) kernel. The software comprises a virtualization layer operating in a host mode, where the virtualization layer, when executed by the one or more hardware processors, is configured to send one or more virtual interrupts to the guest OS kernel of the virtual machine. A virtual interrupt causes an interrupt service routine within the guest OS kernel to perform a particular service that prevents a protected process (or protected software data structures) from being effected by malware.

Abstract: An analytics-based security monitoring system adapted to detect a plurality of behavioral characteristics from behavioral data, each representing an action conducted in a computing environment. Furthermore, the system determines, in accordance with a correlation profile, one or more behavioral fragments, each comprising a plurality of the behavioral characteristics. In accordance with the correlation profile, the one or more determined behavioral fragments are correlated against an attack profile comprising a plurality of sets of behavioral fragments where each set of behavioral fragments forms a malicious behavior pattern of a known attack. Thereafter, an attack based on the correlated one or more determined behavioral fragments may be identified, and the correlation profile is updated after an analysis of the identified attack.

Abstract: To prevent un-authorized accesses to data and resources available in workloads on an organization's or enterprise's computer network, various improvements to automated computer network security processes to enable them to enforce network security policies using native network security mechanisms to control communications to and/or from workload units of applications running on different nodes within hybrid computer network infrastructures having both traditional hardware resources and virtual resources provided by private and public cloud infrastructure services.

Abstract: A system and method operable to identify malicious software by extracting one or more features disassembled from software suspected to be malicious software and employing one or more of those features in a machine-learning algorithm to classify such software.