Systems and methods to detect malicious software include an application software repository including a stored header file associated with a driver, an executable, or both, and are operable to (i) receive a memory dump file upon an operating system crash including a driver copy, an executable copy, or both, (ii) verify the memory dump file is new for analysis, (iii) compress the verified memory dump file to generate a memory snapshot of the verified memory dump file, (iv) scan the memory snapshot for a memory dump header file associated with the driver copy, the executable copy, or both, and (v) identify and extract malicious software when the memory dump header file from the memory snapshot fails to match at least one stored header file in the application software repository.

A protection module operates to analyze threats, at the protocol level (e.g., at the HTML level), by intercepting all requests that a browser engine resident in a computing device sends and receives, and the protection agent completes the requests without the help of the browser engine. And then the protection module analyzes and/or modifies the completed data before the browser engine has access to it, to, for example, display it. After performing all of its processing, removing, and/or adding any code as needed, the protection module provides the HTML content to the browser engine, and the browser engine receives responses from the protection agent as if it was speaking to an actual web server, when in fact, browser engine is speaking to an analysis engine of the protection module.

Implementations are provided herein for systems, methods, and a non-transitory computer product configured to use predictive analysis of quantifiable parameters associated with individual files stored on a distributed file storage system. In some embodiments, parameters are analyzed by machine learning so that scheduled antivirus scanning can be intelligently conducted. We teach creating a sequential order for scheduled antivirus scanning such that the files most likely to be accessed or needed by users in the future will be scanned for viruses before those files less likely to be accessed. Our teachings encompass the use of heuristic data compiled and analyzed on a per-file basis. We enable system administrators to determine which parameters to prioritize and to set thresholds for antivirus scanning such as time limits.

Implementations are provided herein for systems, methods, and a non-transitory computer product configured to use predictive analysis of quantifiable parameters associated with individual files stored on a distributed file storage system. In some embodiments, parameters are analyzed by machine learning so that scheduled antivirus scanning can be intelligently conducted. We teach creating a sequential order for scheduled antivirus scanning such that the files most likely to be accessed or needed by users in the future will be scanned for viruses before those files less likely to be accessed. Our teachings encompass the use of heuristic data compiled and analyzed on a per-file basis. We enable system administrators to determine which parameters to prioritize and to set thresholds for antivirus scanning such as time limits.

Methods and systems for detecting undesirable computer files based on scanning and analysis of information contained within an associated digital certificate chain are provided. According to one embodiment, a file having associated therewith a certificate chain is received. A type and structure of the file are identified. A location of the certificate chain is determined based on the identified type and structure. A signature of the file is formed by extracting a targeted subset of information from the certificate chain. The file is evaluated by comparing the signature with a set signatures having a known desirable or undesirable status. The file is classified based on a result of the evaluating into a category of multiple categories, including one indicative of an associated file being an undesired file or a file suspected of being undesired. The file is handled in accordance with a policy associated with the category.

A storage device comprising a memory, a controller, and a host interface operative to connect with a host. The memory containing data locations access to which are controllable by a protection application which is executable on a host. When the host interface operatively coupled to a host data locations in the memory are accessible to an operating system of the host only under permission from the protection application. The controller communicates with the protection application running on the host for allowing the protection application access to data locations in the memory. Upon a host request for access to a data location, the controller determines if permission to access the requested data location is acquired from the protection application. The permission is based on determination of the protection application that the data location does not contain malicious data harmful to the host operating system, to any application and/or to any data on the host.

A storage device comprising a memory, a controller, and a host interface operative to connect with a host. The memory containing data locations access to which are controllable by a protection application which is executable on a host. When the host interface operatively coupled to a host data locations in the memory are accessible to an operating system of the host only under permission from the protection application. The controller communicates with the protection application running on the host for allowing the protection application access to data locations in the memory. Upon a host request for access to a data location, the controller determines if permission to access the requested data location is acquired from the protection application. The permission is based on determination of the protection application that the data location does not contain malicious data harmful to the host operating system, to any application and/or to any data on the host.

Circuits and methods are provided for detecting, identifying and/or removing undesired content. According to one embodiment, a method for performing content scanning of content objects is provided. A content object that is to be scanned is stored by a general purpose processor to a system memory of the general purpose processor. Content scanning parameters associated with the content object are set up by the general purpose processor. Instructions from a signature memory of a co-processor that is coupled to the general purpose processor are read by the co-processor based on the content scanning parameters. The instructions contain op-codes of a first instruction type and op-codes of a second instruction type. Those of the instructions containing op-codes of the first instruction type are assigned by the co-processor to a first instruction pipe of multiple instruction pipes of the co-processor for execution. An instruction of the assigned instructions containing op-codes of the first instruction type is executed by the first instruction pipe including accessing a portion of the content object from the system memory.

Circuits and methods are provided for detecting, identifying and/or removing undesired content. According to one embodiment, a method for performing content scanning of content objects is provided. A content object that is to be scanned is stored by a general purpose processor to a system memory of the general purpose processor. Content scanning parameters associated with the content object are set up by the general purpose processor. Instructions from a signature memory of a co-processor that is coupled to the general purpose processor are read by the co-processor based on the content scanning parameters. The instructions contain op-codes of a first instruction type and op-codes of a second instruction type. Those of the instructions containing op-codes of the first instruction type are assigned by the co-processor to a first instruction pipe of multiple instruction pipes of the co-processor for execution. An instruction of the assigned instructions containing op-codes of the first instruction type is executed by the first instruction pipe including accessing a portion of the content object from the system memory.

An engine architecture for processing finite automata includes a hyper non-deterministic automata (HNA) processor specialized for non-deterministic finite automata (NFA) processing. The HNA processor includes a plurality of super-clusters and an HNA scheduler. Each super-cluster includes a plurality of clusters. Each cluster of the plurality of clusters includes a plurality of HNA processing units (HPUs). A corresponding plurality of HPUs of a corresponding plurality of clusters of at least one selected super-cluster is available as a resource pool of HPUs to the HNA scheduler for assignment of at least one HNA instruction to enable acceleration of a match of at least one regular expression pattern in an input stream received from a network.