Abstract: A system configured to detect malware is described. The system configured to detect malware including a data collector configured to detect at least a first hypertext transfer object in a chain of a plurality of hypertext transfer objects. The data collector further configured to analyze at least the first hypertext transfer object for one or more events. And, the data collector configured to generate a list of events based on the analysis of at least the first hypertext transfer object.

Abstract: Systems and methods for monitoring malware events in a computer networking environment are described. The systems and methods including the steps of identifying suspect objects; transmitting the suspect objects to an inspection service, wherein the inspection service inspects the suspect objects using a plurality of inspection methods to create digital information about the nature of the potential threat posed by the suspect objects; transmitting said digital information to an analytical service operating, wherein the analytical service performs a plurality of analytical algorithms to categorize the suspect objects with one or more scores for each suspect object based on their security threat; transmitting said one or more scores to a correlation facility which aggregates a plurality of scores; and generating an infection verification pack comprising routines which, when run on an end-point machine within the computer networking environment, will mitigate a suspected security threat.

Abstract: A system configured to generate a risk score for a threat activity including a digital device. The digital device configured to extract one or more threat events on a network based on metadata for one or more targeted digital devices on the network. Further, the digital device is configured to detect one or more incidents based on a correlation between at least a first threat event of the one or more threat events and a second threat event of the one or more threat events. And, the digital device is configured to generate a risk score for each of said one or more incidents.

Abstract: A system configured to detect a threat activity on a network. The system including a digital device configured to detect a first order indicator of compromise on a network, detect a second order indicator of compromise on the network, generate a risk score based on correlating said first order indicator of compromise on the network with the second order indicator of compromise on said network, and generate at least one incident alert based on comparing the risk score to a threshold.

Abstract: A system configured to detect malware is described. The system including an infection verification pack configured to perform behavior detonation; identify a malware object based on machine-learning; and select one or more persistent artifacts of the malware on the target system based on one or more algorithms applied to behavior traces of the malware object to select one or more persistent artifacts of the malware on the target system.

Abstract: A system configured to detect malware is described. The system configured to detect malware including a data collector configured to detect at least a first hypertext transfer object in a chain of a plurality of hypertext transfer objects. The data collector further configured to analyze at least the first hypertext transfer object for one or more events. And, the data collector configured to generate a list of events based on the analysis of at least the first hypertext transfer object.

Abstract: Systems and methods for monitoring malware events in a computer networking environment are described.

Abstract: Methods and apparatuses are described for inspecting data packets in a computer network. One or more data packets through the network have associated header data and content. One method includes receiving a data packet, examining the data packet to classify the data packet including classifying the data packet using information included in the header and content, determining flow instructions for processing the packet based on both the header information and the content and processing of the packet using the flow instructions.

Abstract: A system and method are disclosed for network-based file analysis for malware detection. Network content is received from a network tap. A binary packet is identified in the network content. A binary file, including the binary packet, is extracted from the network content. It is determined whether the extracted binary file is detected to be malware.

Abstract: A system and method are disclosed for network-based file analysis for malware detection. Network content is received from a network tap. A binary packet is identified in the network content. A binary file, including the binary packet, is extracted from the network content. It is determined whether the extracted binary file is detected to be malware.

Abstract: Methods and apparatuses are described for inspecting data packets in a computer network. One or more data packets through the network have associated header data and content. One method includes receiving a data packet, examining the data packet to classify the data packet including classifying the data packet using information included in the header and content, determining flow instructions for processing the packet based on both the header information and the content and processing of the packet using the flow instructions.

Abstract: Methods and apparatuses are described for inspecting data packets in a computer network. One or more data packets through the network have associated header data and content. One method includes receiving a data packet, examining the data packet to classify the data packet including classifying the data packet using information included in the header and content, determining flow instructions for processing the packet based on both the header information and the content and processing of the packet using the flow instructions.

Abstract: A system and method are disclosed for network-based file analysis for malware detection. Network content is received from a network tap. A binary packet is identified in the network content. A binary file, including the binary packet, is extracted from the network content. It is determined whether the extracted binary file is detected to be malware.

Abstract: Methods and apparatuses are described for inspecting data packets in a computer network. One or more data packets through the network have associated header data and content. One method includes receiving a data packet, examining the data packet to classify the data packet including classifying the data packet using information included in the header and content, determining flow instructions for processing the packet based on both the header information and the content and processing of the packet using the flow instructions.

Abstract: The invention is a method and apparatus for detecting shellcode such that a set of computer instructions is scanned for the presence of a null operation instruction. The computer instructions are also examined for the presence of a system call instruction, and reviewed for the presence of a decoder instruction set. A null operation weight value is then determined corresponding to the null operation instruction. Also assessed is a system call weight value corresponding to the system call instruction. In addition, a decoder weight value is calculated corresponding to the decoder instruction set. The null operation weight value, the system call weight value, and the decoder weight value are then analyzed to identify a shellcode.

Abstract: Methods and apparatuses are described for inspecting data packets in a computer network. One or more data packets through the network have associated header data and content. One method includes receiving a data packet, examining the data packet to classify the data packet including classifying the data packet using information included in the header and content, determining flow instructions for processing the packet based on both the header information and the content and processing of the packet using the flow instructions.

Abstract: A system and method are disclosed for network-based file analysis for malware detection. Network content is received from a network tap. A binary packet is identified in the network content. A binary file, including the binary packet, is extracted from the network content. It is determined whether the extracted binary file is detected to be malware.

Abstract: The invention is a method and apparatus for detecting shellcode such that a set of computer instructions is scanned for the presence of a null operation instruction. The computer instructions are also examined for the presence of a system call instruction, and reviewed for the presence of a decoder instruction set. A null operation weight value is then determined corresponding to the null operation instruction. Also assessed is a system call weight value corresponding to the system call instruction. In addition, a decoder weight value is calculated corresponding to the decoder instruction set. The null operation weight value, the system call weight value, and the decoder weight value are then analyzed to identify a shellcode.

Abstract: A method of detecting intrusions on a computer includes the step of identifying an internet protocol field range describing fields within internet protocol packets received by a computer. A connectivity range is also established which describes a distribution of network traffic received by the computer. An internet protocol field threshold and a connectivity threshold are then determined from the internet protocol field range and connectivity range, respectively. During the operation of the computer, values are calculated for the internet protocol field range and connectivity range. These values are compared to the internet protocol metric threshold and connectivity metric threshold so as to identify an intrusion on the computer.

Abstract: A method of identifying a distributed denial of service attack is described in which a rate profile is determined, where the rate profile corresponds to information transfer rates at which information is received from a network. A burst magnitude threshold based on this rate profile is then established. A burst duration profile characterizing periods of time during which the information transfer rate exceeds this burst magnitude threshold is also calculated, and a burst duration threshold is then defined based upon this burst duration profile. A distributed denial of service attack is identified when the information transfer rate exceeds the burst magnitude threshold for a period of time exceeding the burst duration threshold.