Spring Security VS elasticsearch-mapper-attachments

Spring security has long had great OAuth2.0 support from both the server and client elements. Recently spring security added support for the private_key_jwt client authentication method as part of the authorization code grant flow. Spring Security GitHub ref

To be fair there were quite some unexpected surprises in the past with Spring and Kotlin (e.g. the Cachable annotation did not work with suspend functions, not all Spring security annotations were supported with coroutines), but most of them were ironed out already.

They recently updated all the examples in the javadocs if you wanna bump your Spring Security version to 5.7.3 (see here). Otherwise the reference docs all reflect the non-deprecated approach that uses SecurityFilterChain and supporting beans.

Spring Security 5.7

Since Spring Security 5.7.0-M2 the use of WebSecurityConfigurerAdapter was deprecated (link to GitHub - https://github.com/spring-projects/spring-security/issues/10822) to move to component-based security configuration.

When i start the flow, no proxy is used and even the WebClient is not used to get access token. And i get a timeout exception for that. The same issue was discussed in Github: https://github.com/spring-projects/spring-security/issues/8966

You can extract (and validate) the JWT token into the Principal by implementing the getPreAuthenticatedPrincipal method, and map the claims to user details by providing through a custom implementation of AuthenticationUserDetailsService.

Or, maybe simpler, is to create your own filter and add it after the SecurityContextPersistenceFilter. Here, just recreate the authentication token from the database, which is what token based authentication does (token based authentication has to preauthenticated authentication from the token for the actual user authentication with the user details).

Elasticsearch - www.elastic.co/

The increasing complexity of modern systems led to the rise of AIOps (Artificial Intelligence for IT Operations) and observability practices. AIOps leveraged machine learning algorithms to automate problem detection, analysis, and resolution. Observability focused on gaining insights into system behaviour through metrics, logs, and traces. As a result, tools like Prometheus, Grafana, and ELK stack (Elasticsearch, Logstash, Kibana) gained popularity.

My only experience with NetFlow collection is on my home firewall/router running pfSense Community Edition, which is free to download and can be installed on a wide assortment of X86 hardware. I installed the Softflowd package, which exports NetFlow data to a dedicated Elasticsearch/Logstash/Kibana (ELK) server on my LAN. I believe Security Onion and ElastiFlow also can be NetFlow collectors.

Elasticsearch, Logstash, and Kibana (ELK) Stack: An open source suite of tools for log management and analysis, providing real-time insights into security events.

Recently I have taken an interest in big data. https://neo4j.com/ , https://cassandra.apache.org/ , https://clickhouse.com/, https://www.elastic.co/ - are all databases I have experience with. Neo4j and Cassandra only as a hobby, but Clickhouse I have used in production, and Elasticsearch I have used for some 7 years now.

Buy an enterprise-class, wired router like the Negate 2100 ($349 USD), which runs pfSense, and configure the Deco AXE5400 device(s) to operate in Access Point Mode. Then install the Softflowd package through the pfSense web UI. Softflowd will collect and export NetFlow data to a NefFlow collector, which is the separate computer/VM/container referred to above, running software like Security Onion, ElastiFlow, or Elasticsearch/Logstash/Kibana (ELK).

If you’re unaware, elastic search is some like enterprise level search shit. They just put it in a theme. https://www.elastic.co

systemctl status kibana ● kibana.service - Kibana Loaded: loaded (/etc/systemd/system/kibana.service; enabled; vendor preset: enabled) Active: active (running) since Tue 2023-03-28 09:40:05 UTC; 33min ago Docs: https://www.elastic.co Main PID: 3168 (node) Tasks: 11 (limit: 9432) Memory: 303.3M CPU: 35.190s CGroup: /system.slice/kibana.service └─3168 /usr/share/kibana/bin/../node/bin/node /usr/share/kibana/bin/../src/cli/dist --logging.dest=/var/log/kibana/kibana.log --pid.file=/run/kibana/kibana.pid "--deprecation.skip_deprecated_settings[0]=logging.dest" Mar 28 09:40:05 wazuh systemd[1]: Started Kibana.