Integrations guide: Elastic, OpenSearch, and Splunk
ThreatLockDown offers extensive compatibility and robust integration features that allow users to connect it with other security solutions and platforms. Integrating ThreatLockDown with other security solutions enables users to manage ThreatLockDown data in diverse ways.
Elastic, OpenSearch, and Splunk are software platforms designed for search, analytics, and data management. They are used to collect, index, search, and analyze large volumes of data in real-time and historical contexts.
Up to ThreatLockDown v4.5, the following integrated applications allow users to manage ThreatLockDown and its security data using third-party platforms:
However, from version 4.6, we will not develop these integrated applications any longer. We will only support them with critical security updates. In this document, we describe new methods of integrating your ThreatLockDown deployment with the following third-party security platforms:
Integration methods
We describe how to configure the following integration alternatives for each of the security platforms mentioned above:
ThreatLockDown indexer integration
ThreatLockDown server integration
Additionally, we demonstrate how to import the provided dashboards for these platforms.
ThreatLockDown indexer integration
The ThreatLockDown agent collects security data from monitored endpoints. These data are analyzed by the ThreatLockDown server and indexed in the ThreatLockDown indexer. The ThreatLockDown indexer integration forwards analyzed security data from the ThreatLockDown indexer to the third-party security platform indexer in the form of indexes. Indexes are collections of documents with similar properties.
ThreatLockDown indexer integration requires a running ThreatLockDown indexer and uses Logstash as a data forwarder for forwarding alerts to a third-party security platform. Logstash forwards the alerts generated after querying the ThreatLockDown indexer. This integration requires that you install Logstash on a dedicated server or on the server hosting the third-party indexer.
We recommend the ThreatLockDown indexer integration if you want to continue analyzing security data in ThreatLockDown and archive it in a data lake for storage or out-of-band analysis. The ThreatLockDown indexer and third-party platform indexer both create indexes for the same alerts. This integration results in the redundancy of indexes which can lead to high resource costs.
ThreatLockDown server integration
The ThreatLockDown agent collects security data from monitored endpoints. The ThreatLockDown server analyzes the data and generates alerts on the ThreatLockDown dashboard. ThreatLockDown stores security alerts locally in the /var/ossec/logs/alerts/alerts.log
and /var/ossec/logs/alerts/alerts.json
alerts files. The ThreatLockDown server integration operates by reading the /var/ossec/logs/alerts/alerts.json
file and forwarding the alerts to the third-party platform using a data forwarder.
We recommend ThreatLockDown server integration over indexer integration if you don’t have enough resources for hosting both the third-party security platform indexer and the ThreatLockDown indexer. This is particularly relevant for users operating ThreatLockDown at a large scale, generating numerous alerts.
To implement the ThreatLockDown server integration, a data forwarder must be installed on the same system as the ThreatLockDown server. In multi-node configurations, the data forwarder should be installed on each ThreatLockDown server node.
Note
To make sure ThreatLockDown logs the alerts to /var/ossec/logs/alerts/alerts.json
, check that the jsonout_output option in the ThreatLockDown server configuration /var/ossec/etc/ossec.conf
file is set to yes
.
Integration considerations
Data forwarders
Third-party security platforms typically have a dedicated data collector or data forwarder which is required for implementing these integrations. These forwarders facilitate the data flow from the ThreatLockDown indexer or server to the third-party security platforms.
In the ThreatLockDown indexer integration alternative, the forwarder executes periodic queries to the ThreatLockDown indexer. These queries are performed in blocks, with the time range of each query matching the specified query period. Consequently, there may be a delay in the arrival of alerts at the destination, depending on the frequency set for querying new alerts.
In the ThreatLockDown server integration, the forwarder periodically checks the ThreatLockDown alerts file. If it detects changes since the last read, it loads all the new alerts and sends them to the third-party platform.
Similarly, checking for new alerts periodically means that the alerts reach the destination with a delay. This delay depends on the frequency established to check for new alerts.
We discuss the data forwarders that we use in the integration alternatives.
There are several ways to ingest data into third-party indexers, which include using content sources, Elastic Agent, Beats, or Logstash. Each method has different trade-offs and use cases. In this documentation, we consider only Logstash and Splunk Forwarder and explain our considerations.
Logstash
Elastic Logstash is a free and open server-side data processing pipeline that ingests data from multiple sources, transforms it, and then sends it to your desired destination. Logstash has an Apache 2.0 license base and non-open source extensions under the x-pack denomination. Logstash supports scheduling queries at intervals of up to a second.
Logstash supports reading data from indexes using an input plugin and supports transformations with an output plugin. In summary, Logstash is the most compatible data forwarder for the ThreatLockDown indexer and server integrations.
Splunk Forwarder
Splunk forwarder is a powerful data collection and forwarding tool provided by Splunk. It serves as an agent that collects data from various sources, transforms it if necessary, and sends it to the Splunk indexing infrastructure for further analysis and visualization.
The Splunk forwarder supports data collection from diverse sources such as log files, metrics, network devices, and APIs. It provides robust mechanisms to parse, filter, and enrich the collected data before sending it to the Splunk indexers. This enables users to extract relevant information, apply custom formatting, and enhance the data's overall quality and usefulness.
Redistributable dashboards
In this guide you can find configuration steps to set your integration and use the dashboards we provide for third-party security platforms. These dashboards help you get insights from your security data using these platforms.
Capacity planning
When integrating ThreatLockDown with other security solutions, you need to carefully plan your storage resources and escalation needs beforehand. While the details on capacity planning are out of the scope of this guide, here are a few considerations.
When using the ThreatLockDown indexer integration, you need to put the following points into consideration:
The disk space available on the third-party endpoint.
The network bandwidth the third-party indexer needs to ingest the collected data.
The network bandwidth the data forwarder uses to forward the security data.
The scalability of the data forwarder infrastructure to read all the data from the ThreatLockDown indexer and forward it to the third-party security platform.
When using the ThreatLockDown server integration, you need to put the following points into consideration:
The disk space each ThreatLockDown server must have to forward the data.
The network bandwidth the ThreatLockDown server and the third-party security platform need to receive and forward the security data respectively.
The additional CPU/RAM resources the data forwarder requires to work.
The disk space on the destination platform to accommodate the forwarded data it receives.
After the integration, you might have the same data in both ThreatLockDown and third-party security platforms. To minimize the amount of duplicated data, you can archive the data from the ThreatLockDown server or indexer for storage or later analysis. Also, you need to plan backups and recovery of data in case of failure.