Manufacturing facilities have become the primary target for cybercriminals in 2025, accounting for 26% of all global cyberattacks (Source: Industrial Cyber). For OT and IT security teams, the challenge is no longer just about securing the perimeter; it is about protecting a converged environment where a single compromised video camera can provide a pathway to vital programmable logic controllers (PLCs) and production systems. Ransomware attacks against the manufacturing sector surged 61% in 2025, often exploiting vulnerabilities in connected IoT devices and outdated infrastructure (Source: Industrial Cyber).

The conventional approach of "air-gapping" or relying on perimeter firewalls is failing. As manufacturers adopt Industry 4.0 technologies, the need for remote access, data-informed maintenance planning, and real-time video analytics has dissolved the physical boundaries that once protected operations. This shift demands a zero-trust architecture—a security model that assumes no user or device is trustworthy by default, regardless of their location on the network.

Implementing zero-trust is not just about risk mitigation; it can lower breach-related costs. Organizations with mature zero-trust frameworks save an average of $1.76 million per breach compared to those without such protections (Source: Varonis). For network specialists and security leaders responsible for maintaining production continuity while securing expanded attack surfaces, adopting a zero-trust mindset for video platforms is a pragmatic path forward.

The reality of manufacturing cyber threats in 2025

The convergence of Information Technology (IT) and Operational Technology (OT) has expanded the attack surface far beyond established factory boundaries. While this convergence enables operational efficiency and data-informed maintenance planning, it also introduces new vulnerabilities.

• Ransomware targeting production: Attackers now employ sophisticated tactics, including remote access trojans engineered to communicate with industrial protocols like Modbus to manipulate control logic. The average manufacturing ransomware attack results in 23 days of downtime (Source: Total Assure).

• IoT and video vulnerabilities: Manufacturing accounted for the highest volume of IoT device-related attacks in 2025 (Source: Cybersecurity Dive). Video cameras frequently connect to networks with default credentials or unpatched firmware, serving as entry points for lateral movement toward high-value assets.

• Extended detection timelines: Manufacturing organizations require an average of 265 days to identify security breaches, compared to the global average of 241 days (Source: Total Assure). This dwell time allows attackers to conduct reconnaissance and prepare for coordinated disruption.

Key terms to know

Why traditional security fails OT environments

OT and IT security teams often face a "balancing act" frustration: every security measure must be weighed against potential production impact. Standard security tools designed for enterprise IT often disrupt sensitive OT environments.

• Incompatibility with legacy systems: Many manufacturing facilities rely on aging OT systems running outdated operating systems like Windows XP that cannot be patched without disrupting production. Traditional endpoint protection agents may cause latency that triggers safety system failures.

• The remote access risk: To maintain uptime, facilities require remote access for vendors and integrators. However, conventional VPNs often grant broad network access once authenticated. A compromised vendor credential can allow ransomware to spread from a third-party session to engineering workstations.

• Network blindness: Older video systems often operate in isolation from Manufacturing Execution Systems (MES) and SCADA platforms. This creates security blind spots where operational and security data cannot be correlated, making it difficult to detect unauthorized access to sensitive assets.

Core principles of zero-trust for video platforms

To secure video data and the broader manufacturing network, security teams must apply zero-trust principles specifically to their video infrastructure. This approach mitigates the risks associated with third-party access and IoT vulnerabilities.

• Continuous verification: Every access request to the video platform—whether from a security guard, a plant manager, or an API integration—must be authenticated based on multiple factors, not just a password. This includes verifying user identity, device health, and geolocation.

• Least-privileged access: Users should only have access to the specific video feeds and data required for their role. A production line operator needs visibility into their specific workstation, not the entire facility’s server room or loading dock cameras.

• Network segmentation: Video systems should reside in isolated network zones. Even if a camera is compromised, segmentation prevents attackers from moving laterally to the production control network.

• Assume breach: Security architectures should be designed with the assumption that attackers are already present. This necessitates continuous monitoring and anomaly detection to identify suspicious behavior, such as a camera attempting to communicate with an external server.

Solving the OT security dilemma with Spot AI

OT/IT Security and Network Specialists face specific challenges when securing manufacturing environments. Spot AI addresses these core frustrations through a cloud-native, zero-trust approach that respects the unique constraints of production environments.

By addressing these specific pain points, organizations can shift from reacting to issues to proactively managing risk. Book a consultation to discuss your specific network architecture needs.

Compliance drivers: IEC 62443 and NIS2

Regulatory pressure is a major driver for adopting zero-trust architectures in manufacturing. Non-compliance can result in substantial fines and increased insurance premiums.

• IEC 62443: This international standard for industrial automation security mandates network segmentation and the definition of security zones. Zero-trust aligns with IEC 62443 by requiring strict access controls and boundaries between IT and OT systems.

• NIS2 Directive: For manufacturers serving EU markets, NIS2 requires organizations to identify and assess supply chain risks and implement rigorous incident reporting. NIS2 explicitly encourages proactive risk identification, which zero-trust controls can help enable within a video platform.

• NIST Cybersecurity Framework: NIST SP 800-207 provides the roadmap for zero-trust, emphasizing identity governance and data protection. Following these standards helps manufacturers demonstrate due diligence to auditors and cyber insurance providers.

Integrating AI without introducing risk

Integrating AI into manufacturing environments often raises concerns about introducing new vulnerabilities. However, when deployed within a zero-trust framework, Video AI can be a useful tool for security and operational efficiency.

• Passive analysis: Spot AI’s Video AI Agents process video streams passively. They do not send control commands to machinery, eliminating the risk of accidental production stoppages that active control systems might cause.

• Edge processing: By processing data locally on the Intelligent Video Recorder (IVR) before sending metadata to the cloud, organizations minimize bandwidth usage and keep sensitive raw footage within the local network unless specific events are flagged.

• Automated threat detection: AI-powered anomaly detection can identify suspicious behavior patterns, such as unauthorized personnel entering a restricted hazardous zone or a vehicle moving in a "no-go" area. This shortens the Mean Time to Detect (MTTD) for security threats, an important metric for OT security teams.

• Privacy compliance: Automated redaction features allow organizations to blur faces and PII in video footage, supporting compliance with GDPR and employee privacy standards while still allowing for safety and operational analysis.

Comparison of video security approaches

When evaluating video platforms for manufacturing, it is essential to consider how different architectures impact security, deployment speed, and total cost of ownership.

Spot AI’s architecture is designed to sit securely at the edge, making outbound-only connections that do not require opening inbound firewall ports—a vital feature for maintaining the integrity of the manufacturing network perimeter.

The business case for zero-trust video security

The surge in ransomware attacks and the increasing cost of data breaches confirm that legacy security models are no longer sufficient for modern manufacturing. A zero-trust architecture is essential for protecting the converged IT/OT environment, ensuring that video platforms serve as intelligent assets rather than security liabilities.

By implementing a system that enforces continuous verification, least-privileged access, and network segmentation, manufacturers can secure their video data while unlocking the operational value of Video AI. This approach directly addresses the "balancing act" of maintaining production continuity while hardening security posture. With the average cost of a data breach reaching $10.22 million in 2025 (Source: Varonis), the investment in a secure, zero-trust video platform can yield a faster payback by mitigating risk and supporting compliance.

Ready to secure your facility with a platform built for the demands of modern manufacturing? Book a consultation with our security experts today.

Frequently asked questions

What are the key principles of zero-trust security in manufacturing?

The key principles include "never trust, always verify," least-privileged access, network segmentation, and continuous monitoring. In manufacturing, this means verifying every user and device attempting to access the network, limiting access to only what is necessary for a specific role, and isolating critical OT systems from the corporate IT network.

How can zero-trust architecture be implemented without replacing existing cameras?

Zero-trust can be implemented by using an intelligent bridge or gateway device that sits between existing cameras and the network. This device handles encryption, authentication, and secure data transmission, effectively wrapping insecure older hardware in a zero-trust layer without requiring a "rip-and-replace" of existing cameras.

What challenges do manufacturers face in securing video data?

Manufacturers face challenges such as securing remote access for third-party vendors, managing the convergence of IT and OT networks, patching older systems that cannot be taken offline, and ensuring that video data containing PII is handled in compliance with regulations like GDPR.

How does zero-trust enhance cybersecurity for connected devices?

Zero-trust enhances security by assuming that connected devices (IoT) are potentially compromised. It enforces strict traffic controls, ensuring devices can only communicate with authorized endpoints. It also employs continuous monitoring to detect and isolate devices that exhibit anomalous behavior, mitigating lateral movement.

What is the ROI of implementing zero-trust for video platforms?

The ROI includes quantifiable risk mitigation, such as the average $1.76 million savings per breach for organizations with mature zero-trust frameworks (Source: Varonis). Additionally, operational ROI is realized through faster incident response times (MTTR) and reduced downtime, which can result in significant costs for manufacturers.

About the author

Joshua Foster is an IT Systems Engineer at Spot AI, where he focuses on designing and securing scalable enterprise networks, managing cloud-integrated infrastructure, and automating system workflows to enhance operational efficiency. He is passionate about cross-functional collaboration and takes pride in delivering robust technical solutions that empower both the Spot AI team and its customers.