Automatically grouping malware based on artifacts
First Claim
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1. A computer-implemented method, comprising:
- clustering a plurality of samples based on a plurality of features associated with malware, wherein each of the features corresponds to a line or a sub-line in one or more log files determined to be an artifact associated with malware based on an automated malware analysis, wherein clustering the plurality of samples based on the plurality of features further comprises;
selecting one or more of the plurality of features and assigning values to each indicator, wherein selecting one or more of the plurality of features includes performing a pre-filtering operation to select the plurality of features for clustering based on a threshold association between the line or the sub-line in the one or more of the log files and known malware;
collecting the assigned values in an array for each of the plurality of samples;
comparing the assigned values of the array between two of the plurality of samples; and
calculating a distance between the two samples, wherein the samples within a defined threshold of distance are clustered; and
performing an action based on an output of clustering the plurality of samples based on the plurality of features, wherein the action based on the output of clustering the plurality of samples based on the plurality of features further comprises validate the output of clustering the plurality of samples based on the plurality of features based on tags to identify previously identified malware groups.
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Abstract
Techniques for automatically grouping malware based on artifacts are disclosed. In some embodiments, a system, process, and/or computer program product for automatically grouping malware based on artifacts includes receiving a plurality of samples for performing automated malware analysis to generate log files based on the automated malware analysis; processing the log files to extract features associated with malware; clustering the plurality of samples based on the extracted features; and performing an action based on the clustering output.
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Citations
24 Claims
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1. A computer-implemented method, comprising:
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clustering a plurality of samples based on a plurality of features associated with malware, wherein each of the features corresponds to a line or a sub-line in one or more log files determined to be an artifact associated with malware based on an automated malware analysis, wherein clustering the plurality of samples based on the plurality of features further comprises; selecting one or more of the plurality of features and assigning values to each indicator, wherein selecting one or more of the plurality of features includes performing a pre-filtering operation to select the plurality of features for clustering based on a threshold association between the line or the sub-line in the one or more of the log files and known malware; collecting the assigned values in an array for each of the plurality of samples; comparing the assigned values of the array between two of the plurality of samples; and calculating a distance between the two samples, wherein the samples within a defined threshold of distance are clustered; and performing an action based on an output of clustering the plurality of samples based on the plurality of features, wherein the action based on the output of clustering the plurality of samples based on the plurality of features further comprises validate the output of clustering the plurality of samples based on the plurality of features based on tags to identify previously identified malware groups. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A system, comprising:
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a processor configured to; cluster a plurality of samples based on a plurality of features associated with malware, wherein each of the features corresponds to a line or a sub-line in one or more log files determined to be an artifact associated with malware based on an automated malware analysis, wherein clustering the plurality of samples based on the plurality of features further comprises; select one or more of the plurality of features and assigning values to each indicator, wherein selecting one or more of the plurality of features includes performing a pre-filtering operation to select the plurality of features for clustering based on a threshold association between the line or the sub-line in the one or more of the log files and known malware; collect the assigned values in an array for each of the plurality of samples; compare the assigned values of the array between two of the plurality of samples; and calculate a distance between the two samples, wherein the samples within a defined threshold of distance are clustered; and perform an action based on an output of clustering the plurality of samples based on the plurality of features, wherein the action based on the output of clustering the plurality of samples based on the plurality of features further comprises validate the output of clustering the plurality of samples based on the plurality of features based on tags to identify previously identified malware groups; and a memory coupled to the processor and configured to provide the processor with instructions. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A computer program product, the computer program product being embodied in a non-transitory tangible computer readable storage medium and comprising computer instructions for:
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clustering a plurality of samples based on a plurality of features associated with malware, wherein each of the features corresponds to a line or a sub-line in one or more log files determined to be an artifact associated with malware based on an automated malware analysis, wherein clustering the plurality of samples based on the plurality of features further comprises; selecting one or more of the plurality of features and assigning values to each indicator, wherein selecting one or more of the plurality of features includes performing a pre-filtering operation to select the plurality of features for clustering based on a threshold association between the line or the sub-line in the one or more of the log files and known malware; collecting the assigned values in an array for each of the plurality of samples; comparing the assigned values of the array between two of the plurality of samples; and calculating a distance between the two samples, wherein the samples within a defined threshold of distance are clustered; and performing an action based on an output of clustering the plurality of samples based on the plurality of features, wherein the action based on the output of clustering the plurality of samples based on the plurality of features further comprises validate the output of clustering the plurality of samples based on the plurality of features based on tags to identify previously identified malware groups. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24)
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Specification