Abstract: Disclosed are systems and methods for securing a network including one or more network nodes connecting a plurality of network connected devices of the network. A method may include: receiving and temporarily storing a plurality of data packets in a shared buffer of a network node; receiving requests from a first processing engine and a second processing engine to access a temporarily stored data packet; generating a first pointer and a second pointer to the temporarily stored data packet, the second pointer being different from the first pointer while pointing to the same temporarily stored data packet; and enabling the first processing engine to use the generated first pointer to access the temporarily stored data packet and the second processing engine to use the generated second pointer to access the temporarily stored data packet.

Abstract: Disclosed are systems and methods for securing a network using one or more controllers and one or more network nodes. A method may utilize a packet processing engine configured to process incoming network packets, a processing analysis engine configured to perform relatively more complex processing and analysis, and one or more controllers configured to coordinate one or more packet processing engines and one or more processing analysis engines across a network to perform endpoint threat detection and mitigation.

Abstract: Disclosed are systems and methods for securing a network using one or more controllers and one or more network nodes. A method may utilize a packet processing engine configured to process incoming network packets, a processing analysis engine configured to perform relatively more complex processing and analysis, and one or more controllers configured to coordinate one or more packet processing engines and one or more processing analysis engines across a network to perform endpoint threat detection and mitigation.

Abstract: Disclosed are systems and methods for securing a network. A method may include obtaining, by a detection engine, an encapsulated image defining an action for a predetermined data packet of interest; determining, by the detection engine, that the action defined by the encapsulated image should be applied to one or more data packets accessed by the detection engine; generating and deploying, by the detection engine, an action state including one or more attributes associated with the accessed data packet and the encapsulated image; determining, at a first execution engine executing parallel with the detection engine, that the one or more data packets comprises attributes matching the one or more attributes included in the deployed action state; and executing, by the first execution engine, the action included in the deployed action state on a received data packet to generate a processed data packet.

Abstract: Disclosed are systems and methods for securing a network including one or more network nodes connecting a plurality of network connected devices of the network. A method may include: receiving and temporarily storing a plurality of data packets in a shared buffer of a network node; receiving requests from a first processing engine and a second processing engine to access a temporarily stored data packet; generating a first pointer and a second pointer to the temporarily stored data packet, the second pointer being different from the first pointer while pointing to the same temporarily stored data packet; and enabling the first processing engine to use the generated first pointer to access the temporarily stored data packet and the second processing engine to use the generated second pointer to access the temporarily stored data packet.

Abstract: Disclosed are systems and methods for securing a network using one or more controllers and one or more network nodes. A method may utilize a packet processing engine configured to process incoming network packets, a processing analysis engine configured to perform relatively more complex processing and analysis, and one or more controllers configured to coordinate one or more packet processing engines and one or more processing analysis engines across a network to perform endpoint threat detection and mitigation.

Abstract: Apparatus and methods described herein relate to a processor that can convert intelligence data into a data structure, and that can store the data structure in a data store. The processor can calculate an identity value for the data structure. The data structure can be immutable such that data represented in the data structure is not modified. A query engine implemented by the processor can receive a request for intelligence status data, and can query an index data store for a set of identity values correlated with data included in the request. The query engine can retrieve, from the data store, intelligence status data correlated with each identity value in the set of identity values. The query engine can also return a snapshot data structure representing at least a portion of the intelligence status data correlated with each identity value in the set of identity values, in response to the request.

Abstract: In some embodiments, an apparatus includes a memory, storing processor-executable instructions, blacklist terms, and credential dump records, and a processor. The processor receives repository data from targeted remote repositories and stores the repository data as a potential credential dump in the memory when the repository data includes a credential dump attribute. The processor stores the potential credential dump as a probable credential dump when the potential credential dump does not include a blacklist term, in which case the processor also detects a format and delimiter of the probable credential dump. Based on the format and delimiter, pairs of usernames and associated passwords are identified and hashed. If a percentage of the hashes not associated with the credential dump records exceeds a predetermined threshold, the probable credential dump is deemed authentic.

Abstract: The cyber threat intelligence confidence rating visualization and editing user interface technology (hereinafter “TIC”) provides a user interface that allows a user (e.g., a cyber threat analyst, etc.) to submit ratings for various characteristics associated with a cyber threat indicator. In one embodiment, the TIC may instantiate a user interactive risk evaluation component having a user interface input element for a user to submit calculation weights for one or more characteristics of a cyber threat; generate a graphical representation of a cyber threat confidence score for user interface display via the user interactive risk evaluation component; and dynamically adjust the graphical representation of the threat confidence score using at least one of the one or more characteristics weighted by the user configured weight.

Abstract: Apparatus and methods described herein relate to a global workspace management compute device that can generate a workspace hierarchy tree representing a hierarchy of a set of workspaces in a network. A local workspace management compute device operatively coupled to the global workspace management compute device can, when operative, calculate workspace cyber-threat data for a local workspace in the set of workspaces based on data from a global workspace, and can provide the calculated workspace cyber-threat data to a local workspace interface so that the local workspace interface displays a representation of the set of workspaces in the network. After receiving modifications of portions of the local workspace cyber-threat data, the local workspace management compute device can define a child node of the local workspace based on the modifications. The local workspace interface can modify the representation of the set of workspaces in the network based on the child node.

Abstract: The cyber threat monitor and control apparatuses, methods and systems (hereinafter “CTMC”) determines risk across a global Internet network graph model for various virtual or physical network elements. In one embodiment, the CTMC defines a factor mechanism representing interactions among the set of network elements, the factor mechanism including a factor indicative of a correlation between a pair of network elements from the set of network elements, and dynamically calculate the probabilistic network security measure for each network element in the global Internet graph model based at least in part on the factor mechanism and any observed threat indicators related to the global Internet graph model.

Abstract: The real-time cyber threat indicator verification mechanism technology (hereinafter “TIVM”) instantiates one or more virtual client emulators to access a source of a threat, in response to a received threat indicator, so as to evaluate validity and/or severity of the potential threat. In one embodiment, the TIVM may receive a cyber threat indicator having identifying information of a cyber threat source; instantiate, in response to the cyber threat indicator, a virtual client emulator; send a control message to cause the virtual client emulator to interact with the cyber threat source based on the identifying information; obtain a confidence indicator relating to the cyber threat indicator based on interaction between the virtual client emulator and the cyber threat source; and generate a cyber threat indicator confirmation report including the confidence indicator.

Abstract: Apparatus and methods described herein relate to a global workspace manager that can dynamically update historical cyber-threat data for a network. The global workspace manager can receive cyber-threat event data including a time of a cyber-threat event. The global workspace manager can identify a workspace node in a workspace graph associated with the cyber-threat event data, and can identify a threat score interval including a set of times that includes the time of the cyber-threat event. The global workspace manager can retrieve, from the workspace node, a threat score calculation function associated with the threat score interval, and can calculate a threat score for the workspace node during the threat score interval using the threat score calculation function and the cyber-threat event data.

Abstract: In some embodiments, an apparatus includes a memory, storing processor-executable instructions, blacklist terms, and credential dump records, and a processor. The processor receives repository data from targeted remote repositories and stores the repository data as a potential credential dump in the memory when the repository data includes a credential dump attribute. The processor stores the potential credential dump as a probable credential dump when the potential credential dump does not include a blacklist term, in which case the processor also detects a format and delimiter of the probable credential dump. Based on the format and delimiter, pairs of usernames and associated passwords are identified and hashed. If a percentage of the hashes not associated with the credential dump records exceeds a predetermined threshold, the probable credential dump is deemed authentic.

Abstract: In some embodiments, an apparatus includes a memory, storing processor-executable instructions, blacklist terms, and credential dump records, and a processor. The processor receives repository data from targeted remote repositories and stores the repository data as a potential credential dump in the memory when the repository data includes a credential dump attribute. The processor stores the potential credential dump as a probable credential dump when the potential credential dump does not include a blacklist term, in which case the processor also detects a format and delimiter of the probable credential dump. Based on the format and delimiter, pairs of usernames and associated passwords are identified and hashed. If a percentage of the hashes not associated with the credential dump records exceeds a predetermined threshold, the probable credential dump is deemed authentic.

Abstract: The cyber threat monitor and control apparatuses, methods and systems (hereinafter “CTMC”) determines risk across a global Internet network graph model for various virtual or physical network elements. In one embodiment, the CTMC defines a factor mechanism representing interactions among the set of network elements, the factor mechanism including a factor indicative of a correlation between a pair of network elements from the set of network elements, and dynamically calculate the probabilistic network security measure for each network element in the global Internet graph model based at least in part on the factor mechanism and any observed threat indicators related to the global Internet graph model.

Abstract: Current approaches to managing security intelligence data often address both threat and malicious behavior at the individual computer level, tracked by the Internet Protocol (IP) address. For example, important facts, observed behavior, and other indications that are tracked by security organizations are only tracked with respect to individual IP addresses. Bilateral network inheritance generally refers to inheriting a variety of attributes from parents to children and from children to parents in a computer network hierarchy. The computer network hierarchy may comprise various entities such as, for example, top level entities, autonomous systems, address ranges, and individual IP addresses.

Abstract: The cyber threat monitor and control apparatuses, methods and systems (hereinafter “CTMC”) determines risk across a global Internet network graph model for various virtual or physical network elements. In one embodiment, the CTMC defines a factor mechanism representing interactions among the set of network elements, the factor mechanism including a factor indicative of a correlation between a pair of network elements from the set of network elements, and dynamically calculate the probabilistic network security measure for each network element in the global Internet graph model based at least in part on the factor mechanism and any observed threat indicators related to the global Internet graph model.

Abstract: Apparatus and methods described herein relate to a global workspace management compute device that can generate a workspace hierarchy tree representing a hierarchy of a set of workspaces in a network. A local workspace management compute device operatively coupled to the global workspace management compute device can, when operative, calculate workspace cyber-threat data for a local workspace in the set of workspaces based on data from a global workspace, and can provide the calculated workspace cyber-threat data to a local workspace interface so that the local workspace interface displays a representation of the set of workspaces in the network. After receiving modifications of portions of the local workspace cyber-threat data, the local workspace management compute device can define a child node of the local workspace based on the modifications. The local workspace interface can modify the representation of the set of workspaces in the network based on the child node.

Abstract: The cyber threat intelligence confidence rating visualization and editing user interface technology (hereinafter “TIC”) provides a user interface that allows a user (e.g., a cyber threat analyst, etc.) to submit ratings for various characteristics associated with a cyber threat indicator. In one embodiment, the TIC may instantiate a user interactive risk evaluation component having a user interface input element for a user to submit calculation weights for one or more characteristics of a cyber threat; generate a graphical representation of a cyber threat confidence score for user interface display via the user interactive risk evaluation component; and dynamically adjust the graphical representation of the threat confidence score using at least one of the one or more characteristics weighted by the user configured weight.