Protecting modern manufacturing systems from socially engineered cyber fraud

Manufacturing has always been an industry built on resilience. Production lines are engineered for uptime. Supply chains are designed for continuity and redundancy is standard practice. But today, the biggest threats to that resilience are not mechanical, they are digital and often invisible.

The bottleneck holding back manufacturing’s next era of reliability isn’t on the factory floor. It’s in the systems of trust that connect finance, operations, and supplier networks.

See also: New report sees big increases in cybersecurity risks for ICS/OT devices

According to LevelBlue’s 2025 Spotlight Report, 37% of manufacturing executives reported a higher volume of cyberattacks this year, and more than one in four experienced a breach—many of which targeted financial and vendor systems that keep production running.

These types of attacks aren’t ones that bring down machines. They use social engineering which includes manipulation, impersonation, and deception, to build false trust inside the organization.

And when trust itself becomes the target, even the most advanced factory can grind to a halt. The real bottleneck isn’t mechanical. It’s human and systemic, the fragile systems of trust that keep finance, operations, and supplier networks connected.

The hidden bottleneck of trust

In manufacturing, every process is designed to eliminate weak links. Yet many organizations still rely on fragmented financial systems, aging IT stacks, and manual controls inherited from decades of mergers and modernization projects.

These disconnected workflows create visibility gaps between finance, procurement, and cybersecurity—precisely where bad actors strike.

Fraudsters no longer rely on crude phishing emails. They use AI to mimic supplier communication styles, craft invoices that match historical records, and time their requests to align with real business events.

A “routine” supplier payment request could be a sophisticated impersonation that slips through traditional validation checks. In this new environment, trust between business units, vendors, and systems has become a vulnerability.

And the consequences go well beyond the finance department. Imagine a scenario where a fraudulent payment diverts funds meant for a key parts supplier.

The supplier, unaware of the deception, pauses shipments due to nonpayment. Within days, assembly lines stall due to a lack of components. Orders pile up. Customers grow frustrated.

What began as a few manipulated emails becomes a full-blown operational disruption that can be just as damaging as a downed machine on the production floor.

Where fragmentation creates risk

Manufacturers often separate financial workflows from cybersecurity oversight. Finance teams focus on accuracy, procurement on delivery, and cybersecurity on network protection. But the attack surface has blurred.

According to the Trustmi’s 2025 Socially Engineered Fraud & Risk Report, based on a survey of 525 mid- to senior-level finance and cybersecurity leaders at large U.S. enterprises across financial services, technology, health care, manufacturing, and retail, 70% of social engineering attacks cross multiple systems, including finance, vendor onboarding, and payment tools. This means that no single team has complete visibility.

See also: With MFT use growing among manufacturers, new findings see critical cybersecurity gaps

In addition, nearly one-third of organizations also said their existing security tools missed the attack entirely, while one in five said even their standard validations failed to catch it.

This finding is not because these teams aren’t diligent. It’s because fraud has evolved faster than the organizational structures designed to stop it.

When finance and security don’t share intelligence, a suspicious email domain flagged by IT might still pass as an approved vendor payment in accounting. When procurement is pressured to onboard new suppliers quickly, security reviews get skipped. Each gap becomes an opening for attackers to exploit.

Resilience 2.0: Securing the systems of trust

The manufacturing sector understands operational resilience better than most. Now it’s time to extend that same mindset beyond machinery and to the digital systems and human processes that underpin every transaction.

Here are three ways to do that:

Redefine resilience beyond the factory floor: Operational resilience can no longer stop at production. It must extend into finance, procurement, and supply chain relationships.

See also: ‘Legacy’ cyber risk: How to prepare OT for system updates

Manufacturers should treat payment workflows and vendor communications as mission-critical systems because they are. Regular validation of supplier data, stress-testing financial workflows, and simulation of fraud scenarios should become part of standard resilience planning.

Build fusion between finance and cybersecurity: To close the “trust gap,” manufacturers should establish cross-functional governance—fusion teams that unite finance, cybersecurity, and procurement under shared risk accountability.

This structure promotes joint dashboards, shared alerting, and integrated response plans. It’s the same principle used in integrated production control: visibility and coordination reduce downtime and risk.

Embed AI-resilient verification: Attackers now use AI to personalize and scale deception. Manufacturers should meet this with equally intelligent validation.

See also: OT cybersecurity case study: Flaws found and fixed in widely used industrial network devices

AI-driven systems can detect anomalies in payment behavior, flag subtle deviations in vendor details, and correlate activity across systems that humans can’t easily connect. The key is pairing automation with human oversight to ensure AI enhances, not replaces, judgment.

Trust as a measurable asset

In a world of connected operations, trust isn’t intangible, it’s measurable and when it fails, production halts, supply chains stall, and brand credibility suffers.

Yet, most manufacturers don’t monitor trust like they monitor uptime. They track equipment health in real time but validate supplier relationships and payment controls only periodically.

That’s a dangerous mismatch in a landscape where an AI-generated email can trigger a multimillion-dollar loss in minutes.

AI’s dual role: Tool and threat

AI represents both the problem and the solution. Attackers use generative AI to mimic identities and fabricate authenticity. But the same technology can help manufacturers analyze vendor risk, automate anomaly detection, and strengthen decision-making.

See also: Zero-trust cybersecurity for increasingly interconnected OT

The lesson is not to fear AI but to apply it responsibly by aligning it with governance frameworks that blend automation, accountability, and human verification.

Engineering trust for the future

Manufacturing success has always depended on precision. Every process, every part, every person plays a role in ensuring quality and continuity.

Securing digital trust requires that same discipline. It must be engineered into the systems that move money, data, and relationships as carefully as those that move materials.

E-handbook: Cybersecurity

The next evolution of resilience won’t be measured only in uptime or throughput. It will be measured in the ability to maintain a level of trust. Manufacturers must have the ability to protect the flow of information and value across an increasingly digital ecosystem.

We know that when trust breaks, production follows. And in modern manufacturing, securing the systems of trust is the new frontier of resilience.