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Osquery kills ec25/2/2023 libs: Update librdkafka to version 1.8.0 ( #7330).libs: Update libmagic to version 5.40 ( #7330).libs: Update libcap to version 1.2.59 ( #7330).libs: Update libarchive to version 3.5.2 ( #7330).libs: Update googletest to version 1.11.0 ( #7330).libs: Update glog to version 0.5.0 ( #7330).libs: Update boost to version 1.77 ( #7330).libs: Update augeas to version 1.12.0 ( #7330).libs: Update OpenSSL to verion 1.1.1l ( #7330).Add osquery version to macOS app bundle ist ( #7452).Fix submodule cache for macOS CI runner ( #7456).Removing unnecessary macOS version check ( #7451).Add BOOST_USE_ASAN define when enabling Asan ( #7469).Prevent running discovery queries when fuzzing ( #7418).Fix how we disable tables in the fuzzer init method ( #7419).Fix linking of thirdparty_sleuthkit ( #7425).Fix typos in documentation ( #7443, #7412).Fix a crash introduced by 5.2.0 when Yara uses its own strutils.Update the ATC table path column check to be case.Add windows_firewall_rules table for windows ( #7403).Hide the deprecated antispyware column in.Update time table to always reflect UTC values ( #7276, #7460, #7437).The lldp_neighbors table has been deprecated, and is.The smart_drive_info table has been deprecated, and is.This release represents commits from 24 contributors! Thank you To support this work, the developer docs haveīeen updated, as have several parts of the build system It also represents a comprehensive review and update of our Osquery 5.2.2 brings native Apple Silicon (M1) support to the macOS libs: Update OpenSSL from version 1.1.1l to 1.1.1n #7506.Remove the libelfin library and elf parsing tables #7510.Remove the ssdeep library and remove its support in the.Third-party libraries which contained CVEs that could affect osquery.Īdditionally some other third-party libraries and tables have beenĭropped, since they were not maintained or considered safe anymore. Osquery 5.2.3 is a security update that focuses on updating some See also the latest Fossies "Diffs" side-by-side code changes report for "CHANGELOG.md": 5.2.3_vs_5.3.0.Ī hint: This file contains one or more very long lines, so maybe it is better readable using the pure text view mode that shows the contents as wrapped lines within the browser window. Advanced users can build visualizations the suit their own investigative or operational requirements, optionally contributing those back to the primary code repository.As a special service "Fossies" has tried to format the requested source page into HTML format (assuming markdown format).Īlternatively you can here view or download the uninterpreted source code file.Ī member file download can also be achieved by clicking within a package contents listing on the according byte size field. Instead, they can simply download the pre-built and ready-to-use SOF-ELK® virtual appliance that consumes various source data types (numerous log types as well as NetFlow), parsing out the most critical data and visualizing it on several stock dashboards. With a significant amount of customization and ongoing development, SOF-ELK® users can avoid the typically long and involved setup process the Elastic stack requires. The platform is a customized build of the open source Elastic stack, consisting of the Elasticsearch storage and search engine, Logstash ingest and enrichment system, Kibana dashboard frontend, and Elastic Beats log shipper (specifically filebeat). SOF-ELK® is a “big data analytics” platform focused on the typical needs of computer forensic investigators/analysts and information security operations personnel. Read more in our Introduction to Deep File Inspection, dig deeper in our Walkthrough of a Common Malware Carrier, read more about InQuest, about DFI or contact us directly for a formal capabilities briefing. In the future, we will expose lite versions of our Adobe PDF, Oracle Java, and Adobe Flash DFI shims. The current public release is limited to Microsoft and Open Office documents, spreadsheets, and presentations up to 15MB in size. Drag and drop one or more files to queue them for analysis. Additionally, artifacts such as URLs, domains, IPs, e-mail addresses, file names, and XMP IDs are extracted and searchable. While not in full parity with our production engine, this InQuest Labs tool can identify and extract embedded logic, semantic context (including that embedded within images through OCR), and metadata. We aim to automate and scale the reverse engineering skill-set of a typical SOC analyst. Capable of recursively decompressing, decoding, deobfuscating, decompiling, deciphering, and more. A core facet to the InQuest solution is our Deep File Inspection (DFI) engine.
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