Palo Alto Networks, Inc.

Farshad Rostamabadi

Shadi Rostami-Hesarsorkh

Sudarshan Vasudevan

William Redington Hewlett, Ii

Lin Xu

Zhi Xu

Seokkyung Chung

Lee Klarich

Bilal Malik

William Hewlett

Redington William Hewlett

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.

Automatically grouping malware based on artifacts

Techniques for categorizing mobile uniform resource locators (URLs) that are used by mobile applications are disclosed. A URL is extracted from a mobile application. A category for the URL is determined based on a categorization of the mobile application. The URL and its determined category are then generated as output.

Mobile URL categorization

Techniques for alerting and tagging using a malware analysis platform for threat intelligence made actionable are disclosed. In some embodiments, a system, process, and/or computer program product for alerting and tagging using a malware analysis platform for threat intelligence made actionable 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 artifacts associated with the log files; determining whether a tag matches any of the plurality of samples based on the artifacts; and performing an action based on whether the tag matches any of the plurality of samples.

Alerting and tagging using a malware analysis platform for threat intelligence made actionable

Techniques for automatically determining whether malware samples are similar are disclosed. In some embodiments, a system, process, and/or computer program product for automatically determining whether malware samples are similar includes receiving a plurality of samples for performing automated malware analysis to generate log files based on the automated malware analysis; comparing the log files based on the automated malware analysis; determining whether any of the plurality of samples are similar based on the comparison of the log files based on the automated malware analysis; and performing an action based on determining that at least two samples are similar.

Automatically determining whether malware samples are similar

Techniques for a malware analysis platform for threat intelligence made actionable are disclosed. In some embodiments, a system, process, and/or computer program product for a malware analysis platform for threat intelligence made actionable 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 determine artifacts associated with malware; and performing an action based on an artifact.

Malware analysis platform for threat intelligence made actionable

Categorizing mobile uniform resource locators (URLs) used by a mobile application is disclosed. A plurality of URLs is extracted from the mobile application. A category is assigned to at least one URL included in the plurality of URLs. The category is assigned to the URL based on a categorization of the mobile application.

A first unclassified uniform resource locator (URL) is received. An originally primary bloom filter is initialized. A second bloom filter is initialized. In response to receiving a 'no match' result from querying the primary bloom filter for the received first unclassified URL, insert operations are performed on both the originally primary bloom filter and the secondary bloom filter. At a time subsequent to inserting the first unclassified URL into both the originally primary and secondary bloom filters, a determination is made that a false positive rate associated with the originally primary bloom filter exceeds a threshold. In response to the determination, the secondary bloom filter is designated as a replacement primary.

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Los Gatos, CA, United States of America

Farshad Rostamabadi