Abstract: Examples of the present disclosure describe systems and methods for a behavioral threat detection virtual machine. In examples, the virtual machine executes a rule comprising rule instructions. A rule may comprise one or more wait rule instructions that causes the virtual machine to pause execution. As events are added to an event queue for the rule virtual machine, the behavioral threat detection virtual machine evaluates such events in order to identify a positive or, in some instances, a negative match. When a matching event is identified, rule execution resumes. Eventually, a determination is made as a result of processing events and wait packets, thereby indicating the presence or absence of a malicious or potentially malicious behavior, among other examples. Thus, among other things, the behavioral threat detection virtual machine maintains a state associated with rule execution and processes events to identify behaviors accordingly.

Abstract: Examples of the present disclosure describe systems and methods for behavioral threat detection definition. In an example, a behavior rule comprising a set of rule instructions is used to define one or more events indicative of a behavior. For example, a set of events from which one event must be matched may be defined or a set of events from which all events must be matched may be defined. In some examples, events are matched based on an event name or type, or may be matched based on one or more parameters. Exact and/or inexact matching may be used. The set of rule instructions ultimately specifies one or more halt instructions, thereby indicating that a determination as to the presence of the behavior has been made. Example determinations include, but are not limited to, a match determination, a non-match determination, or an indication that additional monitoring should be performed.

Abstract: Examples of the present disclosure describe systems and methods for a behavioral threat detection engine. In examples, the behavioral threat detection engine manages execution of one or more virtual machines, wherein each virtual machine processes a rule in relation to a context. The behavioral threat detection engine uses any of a variety of techniques to identify when events occur. Accordingly, the behavioral threat detection engine provides event indications, in the form of event packets, to one or more virtual machines, such that corresponding rules are able to process the events accordingly. Eventually, a rule may make a determination as to the presence or absence of a behavior. As a result, execution of the associated virtual machine may be halted, thereby indicating to the behavioral threat detection engine that a determination has been made. Thus a behavioral threat detection engine employs a behavior-based approach to detecting malicious or potentially malicious behaviors.

Abstract: The present disclosure describes systems and methods for remote management of appliances. The appliance may be configured to periodically check in a predetermined online location for the presence of a trigger file identifying one or more appliances directed to contact a management server for maintenance. If the file is present at the predetermined location and the file includes the identifier of the appliance, the appliance may initiate a connection to the management server. If the file is not found, then the appliance may reset a call timer and attempt to retrieve the file at a later time. To avoid having to configure addresses on the appliance, link local IPv6 addresses may be configured for use over a virtual private network, allowing administration, regardless of the network configuration or local IP address of the appliance.

Abstract: Examples of the present disclosure describe systems and methods of automatic inline detection based on static data. In aspects, a file being received by a recipient device may be analyzed using an inline parser. The inline parser may identify sections of the file and feature vectors may be created for the identified sections. The feature vectors may be used to calculate a score corresponding to the malicious status of the file as the information is being analyzed. If a score is determined to exceed a predetermined threshold, the file download process may be terminated. In aspects, the received files, file fragments, feature vectors and/or additional data may be collected and analyzed to build a probabilistic model used to identify potentially malicious files.

Abstract: Examples of the present disclosure describe systems and methods for detecting and mitigating stack pivoting exploits. In aspects, various “checkpoints” may be identified in software code. At each checkpoint, the current stack pointer, stack base, and stack limit for each mode of execution may be obtained. The current stack pointer for each mode of execution may be evaluated to determine whether the stack pointer falls within a stack range between the stack base and the stack limit of the respective mode of execution. When the stack pointer is determined to be outside of the expected stack range, a stack pivot exploit is detected and one or more remedial actions may be automatically performed.

Abstract: Examples of the present disclosure describe systems and methods for detecting and mitigating stack pivoting using stack artifact verification. In aspects, function hooks may be added to one or more functions. When a hooked function executes, artifacts relating to the hooked function may be left on the stack memory (“stack”). The location of the artifacts on the stack may be stored in a local storage area. Each time a hook in a hooked function is subsequently executed, protection may be executed to determine whether an artifact remains in the location stored in the local storage area. If the artifact is no longer in the same location, a stack pivot may be detected and one or more remedial actions may be automatically performed.

Abstract: Examples of the present disclosure describe systems and methods for sharing memory using a multi-ring shared, traversable and dynamic database. In aspects, the database may be synchronized and shared between multiple processes and/or operation mode protection rings of a system. The database may also be persisted to enable the management of information between hardware reboots and application sessions. The information stored in the database may be view independent, traversable, and resizable from various component views of the database. In some aspects, an event processor is additionally described. The event processor may use the database to allocate memory chunks of a shared heap to components/processes in one or more protection modes of the operating system.

Abstract: The present disclosure relates to systems and methods for identifying highly sensitive modules and taking a remediation or preventative action if such modules are accessed by malicious software. For example, the likelihood that a module is used for an exploit, and is thus sensitive, is categorized as high, medium, or low. The likelihood that a module can be used for an exploit can dictate whether, and to what degree, an application accessing the module is “suspicious.” However, in some instances, a sensitive module may have legitimate reasons to load when used in certain non-malicious ways. The system may also consider a trust level when determining what actions to take, such that an application and/or user having a higher trust level may be less suspicious when accessing a sensitive module as compared to an application or user having a lower trust level.

Abstract: The present disclosure describes systems and methods for aggregation and management of cloud storage among a plurality of providers via file fragmenting to provide increased reliability and security. In one implementation, fragments or blocks may be distributed among a plurality of cloud storage providers, such that no provider retains a complete copy of a file. Accordingly, even if an individual service is compromised, a malicious actor cannot access the data. In another implementation, fragments may be duplicated and distributed to multiple providers, such that loss of communications to any one provider does not result in inability to access the data. This implementation may be combined with error correction techniques to allow recovery, even with loss of multiple providers. File synchronization may also be faster in these implementations by dividing reading and writing operations among multiple providers.

Abstract: Examples of the present disclosure describe systems and methods for malicious software detection based on API trust. In an example, a set of software instructions executed by a computing device may call an API. A hook may be generated on the API, such that a threat processor may receive an indication when the API is called. Accordingly, the threat processor may generate a trust metric based on the execution of the set of software instructions, which may be used to determine whether the set of software instructions poses a potential threat. For example, one or more call stack frames may be evaluated to determine whether a return address is preceded by a call instruction, whether the return address is associated with a set of software instructions or memory associated with a set of software instructions, and/or whether the set of software instructions satisfies a variety of security criteria.

Abstract: The present disclosure describes systems and methods for detection and mitigation of malicious encryption. A security agent on an infected computing device may monitor data writes to disk, memory, or network transmission buffers for strings that may represent encryption keys or moduli. The security agent may apply one or more techniques to decode and parse the string to either identify or extract the keys, or rule out the string as containing an encryption key or modulus. If a key is identified, or its presence cannot be excluded, then the security agent may generate an alert and take mitigation actions.

Abstract: Examples of the present disclosure describe systems and methods for selective export address table filtering. In aspects, the relative virtual address (RVA) of exported function names may be modified to point to a protected memory location. An exception handler may be registered to process exceptions relating to access violations of the protected memory location. If an exception is detected that indicates an attempt to access the protected memory location, the instruction pointer of the exception may be compared to an allowed range of memory addresses. If the instruction pointer address is outside the boundaries, remedial action may occur.

Abstract: Examples of the present disclosure describe systems and methods for restricting access to application programming interfaces (APIs). For example, when a process calls an API, the API call may be intercepted by a security system for evaluation of its trustfulness before the API is allowed to run. Upon intercepting an API call, the process calling the API may be evaluated to determine if the process is known to the security system, such that known processes that are untrusted may be blocked from calling the API. Further, when the security system cannot identify the process calling the API, the security service may evaluate a call stack associated with the call operation to determine if attributes of the call operation are known to the security system. If the call operation is known to the security system as untrusted, the call operation may be blocked from calling the API.

Abstract: Examples of the present disclosure describe systems and methods of determining online identity reputation. In aspects, an online identity of an entity may engage in online interactions. The content provided by the online identity may be accessed and analyzed to determine interaction characteristics and reputation metrics for the online identity. Based on the reputation metrics, the online identity and/or entity (and content therefrom) may be filtered from further online interactions. In some aspects, interaction data may be stored in a data store. An interaction mapping component having access to the data store may analyze the data store data to determine mappings between online identities, entities and interactions. In at least one aspect, an opt-in certificate system may also be provided. The opt-in system may provide an online identity or entity a certificate to securely validate identity.

Abstract: Examples of the present disclosure describe systems and methods for discrete processor feature behavior collection and analysis. In aspects, a monitoring utility may initialize a set of debugging and/or performance monitoring feature sets for a microprocessor. When the microprocessor receives from software content a set of instructions that involves the loading of a set of modules or code segments, the set of modules or code segments may be evaluated by the monitoring utility. The monitoring utility may generate a process trace of the loaded set of modules or code segments. Based on the process trace output, various execution paths may be reconstructed in real-time. The system and/or API calls made by the microprocessor may then be compared to the process trace output to quickly observe the interaction between the software content and the operating system of the microprocessor.

Abstract: Embodiments disclosed herein relate to systems and methods for providing a smart cache. In embodiments, a variable time to live (TTL) may be calculated and associated with data as it is stored in a cache. The variable TTL may be calculated based upon reputation and/or category information related to the source of the data. The reputation and/or category information may include TTL modifiers for adjusting the TTL for data from a particular data source that is stored in the cache. In further embodiments, a feedback method may be employed to update reputation and/or category information for a particular data source.

Abstract: Aspects of the present disclosure are operable to protect against malicious objects, such as JavaScript code, which may be encountered, downloaded, or otherwise accessed from a content source by a computing system. In an example, antivirus software implementing aspects disclosed herein may be capable of detecting malicious objects in real-time. Aspects of the present disclosure aim to reduce the amount of time used to detect malicious code while maintaining detection accuracy, as detection delays and/or a high false positive rate may result in a negative user experience. Among other benefits, the systems and methods disclosed herein are operable to identify malicious objects encountered by a computing system while maintaining a high detection rate, a low false positive rate, and a high scanning speed.

Abstract: Examples of the present disclosure describe systems and methods of providing real-time scanning of IP addresses. In aspects, input may be received by a real-time IP scanning system. The system may generate one or more work orders based on the input. A scanner associated with the system may access a work order and attempt to communicate with one or more devices identified by the work order. If the attempted communication with a device is successful, a protocol analyzer may be used to provide a predefined payload to the device. If the response from the device matches an expected string, the device may be determined to be a safe and/or legitimate device. If the response from the device does not match an expected string, the device may be determined to be a malicious device.

Abstract: Examples of the present disclosure describe systems and methods for exploit detection via induced exceptions. One embodiment of a method can include generating an inspection point, the inspection point causing an exception when a set of software instructions encounters the inspection point during an execution of the set of software instructions by a processor, registering an exception handler to handle the exception associated with by the inspection point; receiving, in response to the set of software instructions encountering the inspection point, an indication of an exception, accessing a context record associated with the execution of the set of software instructions, evaluating the context record to determine if an exploit is present using the first reputation information, and based on a determination that an exploit is present, performing a corrective action for the exploit.