Abstract: Systems, computer readable media, apparatuses, and methods are disclosed for segregating executable files exhibiting network activity. An example apparatus includes at least one processor and memory including instructions which, when executed, cause the at least one processor to launch an executable file in a segmented portion of a computing system to load one or more dynamically linked libraries (DLLs) associated with the executable file into a process environment block (PEB) of the segmented portion, enumerate the PEB to generate an address list of the one or more DLLs, scan the one or more DLLs to determine whether the one or more DLLs are to perform network activity, and perform malware analysis on the executable file when at least one of the one or more DLLs are to perform network activity.

Abstract: Systems and methods for detection of domain generated algorithms (DGA) and their command and control (C&C) servers are disclosed. In one embodiment, such an approach includes examining DNS queries for DNS resolution failures, and monitoring certain set of parameters such as number of levels, length of domain name, lexical complexity, and the like for each failed domain. These parameters may then be compared against certain thresholds to determine if the domain name is likely to be part of a DGA malware. Domain names identified as being part of a DGA malware may then be grouped together. Once a DGA domain name has been identified, activity from that domain name can be monitored to detect successful resolutions from the same source to see if any of the successful domain resolutions match these parameters. If they match specific thresholds, then the domain is determined to be a C&C server of the DGA malware and may be identified as such.

Abstract: Systems and methods for detection of domain generated algorithms (DGA) and their command and control (C&C) servers are disclosed. In one embodiment, such an approach includes examining DNS queries for DNS resolution failures, and monitoring certain set of parameters such as number of levels, length of domain name, lexical complexity, and the like for each failed domain. These parameters may then be compared against certain thresholds to determine if the domain name is likely to be part of a DGA malware. Domain names identified as being part of a DGA malware may then be grouped together. Once a DGA domain name has been identified, activity from that domain name can be monitored to detect successful resolutions from the same source to see if any of the successful domain resolutions match these parameters. If they match specific thresholds, then the domain is determined to be a C&C server of the DGA malware and may be identified as such.

Abstract: Systems, computer readable media, apparatuses, and methods are disclosed for segregating executable files exhibiting network activity. An example apparatus includes at least one processor and memory including instructions which, when executed, cause the at least one processor to launch an executable file in a segmented portion of a computing system to load one or more dynamically linked libraries (DLLs) associated with the executable file into a process environment block (PEB) of the segmented portion, enumerate the PEB to generate an address list of the one or more DLLs, scan the one or more DLLs to determine whether the one or more DLLs are to perform network activity, and perform malware analysis on the executable file when at least one of the one or more DLLs are to perform network activity.

Abstract: An executable file is loaded into memory. The executable file is analyzed to determine whether one or more dynamically linked libraries are referenced in an import table of the file. It can then be determined whether one or more dynamically linked libraries is adapted to contact a network.

Abstract: An executable file is loaded into memory. The executable file is analyzed to determine whether one or more dynamically linked libraries are referenced in an import table of the file.

Abstract: Systems and methods for detection of domain generated algorithms (DGA) and their command and control (C&C) servers are disclosed. In one embodiment, such an approach includes examining DNS queries for DNS resolution failures, and monitoring certain set of parameters such as number of levels, length of domain name, lexical complexity, and the like for each failed domain. These parameters may then be compared against certain thresholds to determine if the domain name is likely to be part of a DGA malware. Domain names identified as being part of a DGA malware may then be grouped together. Once a DGA domain name has been identified, activity from that domain name can be monitored to detect successful resolutions from the same source to see if any of the successful domain resolutions match these parameters. If they match specific thresholds, then the domain is determined to be a C&C server of the DGA malware and may be identified as such.