![]() When we re-run GraphKer for example after 1 month, these number will probably be different even though, these CVEs have been published in 2020. In every record in our data, there will be several modifications by the numbering authorities. Which are the most appearing CWEs during the first six months with covid-19?Īs you can see, there are 1772 vulnerabilities not related to any known weakness yet. ![]() GraphKer - Examples on Neo4j Browser - YouTube GraphKer Repository: amberzovitis/GraphKer: Open Source Tool - Cybersecurity Graph Database in Neo4j () Now you are ready to explore your data in Neo4j graphs!Ĭheck out a DBMS Dump File with 2021 CVEs and relevant CPEs, and all CWEs and CAPECs: amberzovitis/GraphKer-DBMS-Dump () Then go to your Linux or Windows terminal and run GraphKer! Depends on your hardware you will have the most recent data feeds of CVEs, CWEs, CAPECs, CPEs in about 6 to 15 minutes. Install and use applications created for Neo4j such as Neo4j Bloom, Graphlytic, Neo4j Database Analyzer etc.Install Python requirements for GraphKer. ![]() To run GraphKer you need to do 3 + 1 things. GraphKer makes good use of Neo4j as a native graph database platform and APOC Library Procedures to maintain an efficient way on data storage and retrieval. Using Neo4j, we can search these graphs, in a fast and super user-friendly way, and discuss them with users that don’t have any idea about cybersecurity and graph databases. GraphKer uses a new ontology approach for data feeds, to reinforce the knowledge extraction ways that graph databases provide. With Neo4j and GraphKer Tool, we demonstrate an example on how we can manage big cybersecurity data, and more specifically every public record of CVE, CWE, CAPEC and CPE provided by MITRE and NIST to find new connections between them and their attributes, and extract knowledge from connected graphs. to update our cybersecurity level, and operational readiness? How can we think out of the box? How can we search connections between cyber security incidents, threat actors, hardware, software, skills required, attack paths, etc. we can maintain a -relatively- safe environment both virtual and physical. As long as we stay up to date into cybersecurity techniques, procedures, policies, regulations etc. We need to educate our colleagues and clients (and users in general) into cybersecurity policies and procedures, and possible ways that a dangerous user could exploit to break in our data or organization. However, we can admit that is not enough, it’s not even close to stop the advanced threats unleashed by malicious users. In 2021 we have plenty of great software, hardware, and techniques to enrich our cyber defense. Every try for a successful analysis of this vast amount of data that we deal with, every day, contributes to cyber defense and protection of our colleagues, clients, data, and organizations. ![]() We work in a constantly changing environment and must be ahead of unwanted surprises as much as possible. The common use of these concepts has a very important impact on our lives even though we don’t notice it. Connectivity and knowledge extraction from data are two highly connected concepts and not just a methodology for scientists. Nowadays, when everything is translated into data and is being used for knowledge extraction, every scientist, researcher, industry worker etc., tries to find connectivity between these huge amounts of data. GraphKer is a free and open-source tool, providing a detailed and updated cybersecurity graph database using Neo4j. Let’s talk about GraphKer a combination of the words Graph and Hacker. GraphKer represents every public record of CVE, CWE, CAPEC and CPE provided by MITRE and NIST in a connected graph using Neo4j. ![]()
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