Agro: Ransomware Threats

Background

As edge computing continues to gain momentum in agriculture, it has become a target for cybercriminals. The client is a prominent farming co-op organization that focuses on corn and soy products for chickens, hogs, and cattle.

The challenge

Over the years, the client has grown quickly, resulting in a disjointed network with a mix of aging and newer farm equipment. Given the rising sophistication of harmful cyber attacks such as ransomware that are capable of disrupting ongoing operations within their farming operations.

Like any farming environment, their operations include control systems and specialized assets such as chemical mixing machines, refrigeration units, or smart irrigation systems that don’t particularly work well with traditional security solutions. Their system and assets are critical to monitoring temperature, water quality, humidity, and other environmental conditions that affect the quality of their operations.

In late 2021, they were targeted by hackers with a ransomware attack that endangered its food supply chains and feeding schedules for millions of cattle. The attack was the result of a vulnerability in an unidentified device.

The solution

After weeks of trying to contain the breach and develop a workaround to continue their operations, the losses were significant and the damage was done. Amidst their recovery, the organization decided to take preventative measures and proactive steps to safeguard their operations.

Concerned about solving their device security and network visibility gaps, it was important to protect their device-generated data in its growing environment and mitigate the risks of not being able to see what devices were connected to its IT and OT networks.

As a result, our client reached out to us to employ AI EdgeLabs as part of their revamped strategy towards achieving a safer environment. AI EdgeLabs helps reduce their cyber attack surface with advanced network visibility, threat intelligence software for early threat detection, and automated incident and remediation protocols in real-time.

After careful evaluation, our client favored our solution, AI EdgeLabs as a much-needed extra layer of security for its entire corporate estate. AI EdgeLabs gives the IT team information about network activity that they didn't have before with the security tools they were using.

AI EdgeLabs: Accuracy and real-time insights as the client’s top choice

With the help of our threat intelligence software for early threat detection and real time monitoring, our client soon realized where their system and network vulnerabilities were. Before using our solution, they estimated having 50 network-connected devices in one of their smaller facilities and soon realized there were more than 295 unidentified connected devices in that network.

“We rolled out the AI EdgeLabs solution in all of our farming operations facilities, which enabled us to respond immediately to ongoing attacks and protect Edge/IoT critical infrastructure from malware, ransomware,” said the company’s Head of Security Operations.

By detecting the early signs of ransomware, such as the creation of new accounts with high privileges, the installation of unauthorized software, port scans from inside the network, or spike in device activity, AI EdgeLabs provides them with real-time protection, incident response, and interruption of any threat before they result in downtime or operational disruption.

Benefits of AI EdgeLabs in Agriculture

With the implementation of AI EdgeLabs’ automation for network and device security, we:

• Identify suspicious devices and disabled them automatically and immediately.
• Collect monitoring and reporting data from suspicious devices for deeper analysis.
• Halt account access for all suspicious devices.
• Kill infected device connections by updating access control lists with smart firewalling.
• Discontinue irregular or blacklisted processes on critical devices with automated incident response protocols.
• Improve security posture, network threat detection, and malware detection.
• Address the new and emerging concerns of their rapidly growing asset infrastructure.
• Stop device attacks before they even had the chance of causing harm.
• Alert the network and security teams with real-time information about threats and attacks.
• Set up a distributed defense infrastructure that was easy to scale.