I watched one of David Bombal’s interviews from CISCO live linked below and thought why not…. It’s Pi vs Pi day. In this post, I would like to explore a solution for process monitoring, mapping, and alerting by integrating AI with an Extended Detection and Response (XDR) framework. The objective is to provide enhanced visibility into process behaviors, including the identification of application chains and child processes, in order to identify access patterns and proactively detect potential zero day threats. By employing Coral.ai’s capabilities, I will enable real-time analysis and monitoring of processes from their start times, facilitating a more robust security posture.
In today’s rapidly evolving digital landscape, ensuring robust cybersecurity measures has become more critical than ever. The proliferation of sophisticated cyber threats necessitates proactive strategies to safeguard sensitive data and protect network infrastructure. One such approach involves leveraging the power of an AI platform for monitoring and mapping, system process and detect access patterns. In this post, I will delve into the implementation of Coral.ai on a Raspberry Pi with an XDR (Extended Detection and Response) framework to monitor, map, and follow processes. By closely examining the application chains opened by these monitored processes, I will gain valuable insights into access patterns that individuality may not be detected and take precautionary measures to mitigate potential security risks.
Zero-day vulnerabilities pose significant challenges to conventional security mechanisms. Traditional signature-based detection systems often fail to identify these emerging threats due to their lack of prior recognition. Techniques like Obfuscation, Encryption, Signature evasion, and Polymorphic malware are often used to hide from detection. Therefore, a proactive approach is necessary to detect and respond to these threats before they can cause substantial damage. By combining the power of AI, which provides real-time visibility into process behaviors, with an XDR framework, we can bolster our security posture and improve our incident response capabilities.
Coral.ai can provide real-time visibility into process behaviors, capturing and analyzing data as processes execute. By watching process behavior to identify anomalies we pull into frame a string of events that look suspicious. If we are able to put the pieces together my following a chain such as an open email leads to a website, then a shell is executed and a port is opened its clear that this string of events looks suspicious. This ability to detect and respond promptly to any anomalies or suspicious activities can proved improved response and alerting times.
Child Process Tracking enables the tracking of child processes spawned by monitored processes and by monitoring the behavior of these child processes, we gain an understanding of the full process hierarchy and can identify any malicious activities or unusual patterns. AI employs advanced algorithms to analyze access patterns exhibited by these processes and this analysis helps identify normal and abnormal behavior, facilitating the detection of potential threats and enabling proactive response.
AI offers flexible integration possibilities with various security tools and frameworks, providing the ability to leverage an Extended Detection and Response (XDR) framework that enables seamless collaboration between the AI process monitoring capabilities and the broader security ecosystem. Security Information and Event Management (SIEM) solutions enables the consolidation of process monitoring data into a central management system which facilitates correlation with other security events, enabling comprehensive threat detection and analysis.
By harnessing the power of AI’s advanced capabilities, we gain unparalleled visibility into process behaviors, map application chains, track child processes, and analyze access patterns. This enables early detection of potential threats, drives proactive alerts, and strengthen overall security postures.
Access pattern analysis is an ongoing process that requires continuous monitoring and adaptation. Using AI provides real-time visibility into process behaviors, allowing us to stay vigilant and adapt baseline access patterns as environments evolve. Continuous monitoring ensures that emerging threats or changes in process behaviors are promptly detected and addressed.
There are several open-source options available for SIEM (Security Information and Event Management) and XDR (Extended Detection and Response) frameworks. Here are a few popular choices:
SIEM Options:
- ELK Stack (Elasticsearch, Logstash, Kibana): ELK Stack is a widely used open-source solution that combines Elasticsearch for log storage and indexing, Logstash for log collection and parsing, and Kibana for log visualization and analysis.
- Graylog: Graylog is an open-source log management and SIEM platform that provides centralized log collection, processing, and analysis capabilities. It offers features like alerting, dashboards, and threat intelligence integration.
- OSSIM (Open Source Security Information Management): OSSIM is a comprehensive SIEM solution that integrates various open-source security tools, including Suricata, Snort, OpenVAS, and others. It provides log management, event correlation, and threat intelligence capabilities.
- Apache Metron: Apache Metron is a scalable open-source SIEM platform that combines real-time streaming analytics, machine learning, and threat intelligence for detecting and responding to security events.
XDR Options:
- TheHive: TheHive is an open-source XDR platform that combines incident response, case management, and threat intelligence capabilities. It enables security teams to collaborate and investigate security incidents effectively.
- MISP (Malware Information Sharing Platform): MISP is an open-source threat intelligence platform that allows for the sharing, storing, and correlation of threat indicators. It can be integrated with other security tools to enhance detection and response capabilities.
- Wazuh: Wazuh is an open-source XDR platform that combines host-based intrusion detection, log analysis, vulnerability assessment, and security monitoring capabilities. It provides real-time threat detection and response for on-premises and cloud environments.
- OpenCTI: OpenCTI is an open-source platform for managing and sharing cyber threat intelligence. It offers features such as threat modeling, campaign analysis, and incident management.
These are just a few examples of open-source SIEM and XDR options available. Each solution has its own features, capabilities, and community support. It’s important to evaluate and choose the one that best fits your specific requirements and integrates well with the other components of your security infrastructure.
Pi vs Pi – Are you ready to rumble?
Using Kali linux on Raspberry Pi as the Red Team (Attacker):
- Install Kali Linux on one Raspberry Pi and configure it as the Red team’s attack platform.
- Use Kali’s tools, such as Metasploit, Nmap, and Wireshark, to simulate various attack scenarios and exploit vulnerabilities within the virtual lab.
Setting up the Blue Team (Defender):
- Install an operating system (e.g., Raspberry Pi OS) on another Raspberry Pi and configure it as the Blue team’s monitoring platform.
- Install and configure Coral.ai on the Blue team Raspberry Pi to enable process monitoring, application chain mapping, and access pattern analysis.
Process Monitoring and Application Chain Mapping:
- Utilize Coral.ai’s process monitoring capabilities to capture and analyze the behavior of processes running on the Blue team Raspberry Pi.
- Map the application chains initiated by the processes, tracking the flow of interactions between various components within the network.
Access Pattern Analysis and Anomaly Detection:
- Establish baseline access patterns by monitoring the normal behavior of processes and their interactions within the network.
- Utilize Coral.ai’s access pattern analysis to identify deviations from the established baselines, which may indicate unauthorized activities or Red team attacks.
- Implement anomaly detection algorithms or machine learning techniques to identify suspicious patterns and generate alerts for potential security breaches.
Zero-Day Alerting and Response:
- Configure Coral.ai to generate zero-day alerts when it detects abnormal behavior or potential Red team attacks based on the access pattern analysis.
- Integrate Coral.ai with open-source security tools, such as a SIEM system or an XDR framework, to automate incident response actions.
- The Blue team can leverage the alerts provided by Coral.ai to initiate countermeasures, such as isolating the Red team Raspberry Pi, blocking malicious IP addresses, or capturing network traffic for further analysis.
By deploying this Red team vs. Blue team setup with Coral.ai, you can actively detect and respond to simulated attacks launched by the Red team. The process monitoring, application chain mapping, access pattern analysis, and zero-day alerting capabilities of Coral.ai enable the Blue team to enhance threat detection and incident response capabilities reducing the effectiveness of the Red team exploits.
It’s important to note that this setup should be used in a controlled testing environment, and proper permissions and legal considerations should be followed when conducting such activities. Have fun and let the Battles begin…..
