The purpose of this blog post is to provide multiple methods on how to install/setup Hashicorp Boundary. This blog post generated an Ansible playbook, Docker-compose for Swarm, and manual instructions for installing Boundary on Ubuntu 20.04. In addition, this blog post will demonstrate how to setup Auth0 OIDC authentication for single-sing on. Lastly, I will end this blog post with connecting to a remote machine in my homelab via SSH using the Boundary Desktop and CLI client.
Do you know if your Filebeat client is connecting to a rogue Logstash server? Do you know if your Logstash server is accepting random logs from random devices? If you have answered “I don’t know” to either of these questions then this blog post is for you. The purpose of this blog post is to provide instructions on how to setup Logstash and Filebeat with mutual TLS (mTLS). The step-by-step instructions in this post, will demonstrate how to create the certificate chain of trust using Vault. Lastly, I will cover the Python script I created to automate constructing this logging certificate chain of trust.
While working on my TOR relay project I was trying to compile Suricata with pf_ring but couldn’t find any documentation for the latest releases. This blog post will provide instructions to compile the latest stable version of Suricata and pf_ring. In addition, this blog post contains instructions for the infrastructure-as-code written in Ansible to automate the installation and step-by-step instructions for a manual installation.
In incident response, time is precious and something you can never get back. Typically, when I receive a security alert about an endpoint, it requires manual lookups on multiple data sources for critical pieces of information. These manual lookups can be time-consuming, create fatigue, and don’t use the power of technology to your advantage. This blog post will demonstrate a proof-of-concept (POC) by using the power of a network community ID hash by Corelight to fuse endpoint and network-based data sources.
KSQL by Confluent provides the ability to enrich independent data sources by correlating common attributes. In this POC, we are going to use Sysmon or Osquery to monitor the endpoint and Zeek to monitor the network. Not only will this blog post serve as a POC but it will discuss the architecture, design decisions, working infrastructure-as-code, and the knowledge I accumulated from this project. The hope is that this POC will serve as a framework for the infosec community to use to perform log enrichment. Lastly, I will demonstrate the power of this POC by detecting a Powershell Empire agent that has been injected into explorer.exe.
In incident response, there is a disconnect between a security alert being generated and a user’s confirmation of the security alert. For example, generating an alert every time a user runs “curl” on a production system would generate a bunch of false positives that can lead to what is called “alert fatigue”. But if we extend our incident response capabilities to include the user as part of the triage process we could reduce the number of alerts. This blog post is going to demonstrate AskJeevesSecBot which is an open-source proof of concept (POC) of how to integrate Slack and user responses into your security pipeline, specifically during the triage phase of the incident response process. In addition to a PoC, this blog post will also provide a deep dive into the architecture of this project, design decisions, and lessons learned as an evolving threat detection engineer.
Here we go again! This blog post is tangential to my previous blog post on creating an Osquery extension with Python but this time we are using golang. Osquery is my favorite open-source security tool and golang is becoming a popular programming language so fusing them together allows us to engineer tools to detect threats. This blog post will build an Osquery-go extension to calculate the CommunityID of a network connection utilizing the Osquery-polylogyx extension pack to monitor network connections. In blog posts to follow, we will correlate network-based events monitored by Zeek and host-based events generated by Osquery using the CommunityID. So follow me again as your adventure guide on this development journey to make an Osquery extension with osquery-go.
Osquery is my favorite open-source security tool and Python is my favorite programming language so fusing them together allows us to engineer tools to detect threats. This blog post will build an Osquery-python extension to calculate the CommunityID of a network connection utilizing the Osquery-polylogyx extension pack to monitor network connections. In blog posts to follow, we will correlate network-based events generated by Zeek and host-based events generated by Osquery using the CommunityID. So follow me as your adventure guide on this development journey to make an Osquery extension with osquery-python.
This proof-of-concept (PoC) will demonstrate how to use Osquery to monitor the browser activity of users. Not only will this PoC collect browser activity, but it will also use VirusTotal to rank each URL to detect malicious activity. In addition to VirusTotal, this PoC will utilize Rsyslog, Osquery, Kafka, Splunk, Virustotal, Python3, and Docker as a logging pipeline. Once this pipeline has been implemented, your security team will have the ability to protect your user’s from today’s most serious threats on the web.
In this blog post, we will explore how Zeek detects SSH brute forcing. We will explore the SSH handshake to understand how it works. Next, I will demonstrate several test cases of Zeek detecting SSH brute forcing. Finally, this post will lay down the foundation to implement active defense controls with Zeek in future posts.
Monitoring your home network can be challenging without enterprise-grade equipment. Although monitoring your home network can prove to be difficult, Proxmox and Zeek provide the perfect solution to monitor your home network. This blog post will cover how to setup Zeek+PF_Ring to monitor network traffic on Proxmox.
One of the biggest challenges for blue teams is using logs to hunt for malicious activity. Tools like BRO provide fantastic logging of the events that transpired on a network but don’t provide a mechanism to ask those logs a question. Threat hunting is the process of generating a series of hypotheses about malicious activity that might be occurring on your network. EQL provides a tool that can ingest logs and provide the threat hunter a mechanism to ask questions to prove or disprove their hypotheses. Furthermore, I have extended the EQL platform to support Zeek/BRO logs for network-based threat hunting.
In this blog post series, I will be covering how to setup a Tor exit node for security research. The educational goals of this series is to learn more about network security monitoring, logging, and enrichment to create a threat intelligence pipeline. My exit node will collect data that will be ingested and returned to the community as intelligence.