Abstract: A method, apparatus, and computer program are disclosed. The method may be performed by one or more processors and may comprise receiving first data representing an infrastructure of a computer network, the first data comprising an indication of hosts which form at least part of the computer network and one or more software resources on respective hosts. The method may also comprise receiving second data from a vulnerability scanning software, the second data comprising an indication of one or more vulnerabilities detected in the one or more software resources provided on at least some of the hosts of the computer network. Using a combination of the first data and the second data, output data may be generated representing a risk profile of the computer network infrastructure, the output data indicating one or more subsets of hosts, determined as being at risk of being affected by the detected vulnerabilities by virtue of the software resources they provide for output on a user interface.

Abstract: A method, apparatus, and computer program are disclosed. The method may be performed by one or more processors and may comprise receiving first data representing an infrastructure of a computer network, the first data comprising an indication of hosts which form at least part of the computer network and one or more software resources on respective hosts. The method may also comprise receiving second data from a vulnerability scanning software, the second data comprising an indication of one or more vulnerabilities detected in the one or more software resources provided on at least some of the hosts of the computer network. Using a combination of the first data and the second data, output data may be generated representing a risk profile of the computer network infrastructure, the output data indicating one or more subsets of hosts, determined as being at risk of being affected by the detected vulnerabilities by virtue of the software resources they provide for output on a user interface.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may receive data comprising a plurality of raw data items from one or more data sources, such as a monitoring agent located in a monitored network. The received data may be scored using one or more scoring rules and/or algorithms, with raw data items satisfying a score threshold designated as “data item leads.” Raw data items associated with a data item lead may be searched and displayed to the user via an interactive user interface. The data analysis system may be used to execute searches and additional enrichments against the received raw data items. The data analysis system may group received raw data items based upon shared attribute values. The data analysis system may be used to categorize received data and construct timelines, histograms, and/or other visualizations based upon the various attributes of the raw data items.

Abstract: A method, apparatus, and computer program are disclosed. The method may be performed by one or more processors and may comprise receiving first data representing an infrastructure of a computer network, the first data comprising an indication of hosts which form at least part of the computer network and one or more software resources on respective hosts. The method may also comprise receiving second data from a vulnerability scanning software, the second data comprising an indication of one or more vulnerabilities detected in the one or more software resources provided on at least some of the hosts of the computer network. Using a combination of the first data and the second data, output data may be generated representing a risk profile of the computer network infrastructure, the output data indicating one or more subsets of hosts, determined as being at risk of being affected by the detected vulnerabilities by virtue of the software resources they provide for output on a user interface.

Abstract: A method, apparatus, and computer program are disclosed. The method may be performed by one or more processors and may comprise receiving first data representing an infrastructure of a computer network, the first data comprising an indication of hosts which form at least part of the computer network and one or more software resources on respective hosts. The method may also comprise receiving second data from a vulnerability scanning software, the second data comprising an indication of one or more vulnerabilities detected in the one or more software resources provided on at least some of the hosts of the computer network. Using a combination of the first data and the second data, output data may be generated representing a risk profile of the computer network infrastructure, the output data indicating one or more subsets of hosts, determined as being at risk of being affected by the detected vulnerabilities by virtue of the software resources they provide for output on a user interface.

Abstract: A method, apparatus, and computer program are disclosed. The method may be performed by one or more processors and may comprise receiving first data representing an infrastructure of a computer network, the first data comprising an indication of hosts which form at least part of the computer network and one or more software resources on respective hosts. The method may also comprise receiving second data from a vulnerability scanning software, the second data comprising an indication of one or more vulnerabilities detected in the one or more software resources provided on at least some of the hosts of the computer network. Using a combination of the first data and the second data, output data may be generated representing a risk profile of the computer network infrastructure, the output data indicating one or more subsets of hosts, determined as being at risk of being affected by the detected vulnerabilities by virtue of the software resources they provide for output on a user interface.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may receive data comprising a plurality of raw data items from one or more data sources, such as a monitoring agent located in a monitored network. The received data may be scored using one or more scoring rules and/or algorithms, with raw data items satisfying a score threshold designated as “data item leads.” Raw data items associated with a data item lead may be searched and displayed to the user via an interactive user interface. The data analysis system may be used to execute searches and additional enrichments against the received raw data items. The data analysis system may group received raw data items based upon shared attribute values. The data analysis system may be used to categorize received data and construct timelines, histograms, and/or other visualizations based upon the various attributes of the raw data items.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may receive data comprising a plurality of raw data items from one or more data sources, such as a monitoring agent located in a monitored network. The received data may be scored using one or more scoring rules and/or algorithms, with raw data items satisfying a score threshold designated as “data item leads.” Raw data items associated with a data item lead may be searched and displayed to the user via an interactive user interface. The data analysis system may be used to execute searches and additional enrichments against the received raw data items. The data analysis system may group received raw data items based upon shared attribute values. The data analysis system may be used to categorize received data and construct timelines, histograms, and/or other visualizations based upon the various attributes of the raw data items.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may receive data comprising a plurality of raw data items from one or more data sources, such as a monitoring agent located in a monitored network. The received data may be scored using one or more scoring rules and/or algorithms, with raw data items satisfying a score threshold designated as “data item leads.” Raw data items associated with a data item lead may be searched and displayed to the user via an interactive user interface. The data analysis system may be used to execute searches and additional enrichments against the received raw data items. The data analysis system may group received raw data items based upon shared attribute values. The data analysis system may be used to categorize received data and construct timelines, histograms, and/or other visualizations based upon the various attributes of the raw data items.