AI’s Role in Identifying Cyber Threats in the Supply Chain

Artificial intelligence is widely recognized today as a crucial tool for maintaining manufacturing efficiency and profitability. With 93% of manufacturing companies believing that AI will be “a pivotal technology” to drive growth and innovation, it’s no surprise that its projected annual growth in manufacturing is over 40% — expected to surpass $2 billion in 2025.

Most of the current use of AI in manufacturing is in smart production, enabling factory automation, order management, and automated scheduling. But that’s just the beginning: AI’s value for manufacturing is rapidly expanding beyond production optimization –—to security. 

Physical Security Threats

Amid escalating trade wars and tumultuous geopolitical conflicts around the world, supply chains have become vulnerable targets for malicious actors. This increasing volatility is reflected in the Geopolitical Risk with Trade (GPRT) index, which surged by a frightening 30% between 2020 and 2024 compared with the two decades prior. Among the most pressing threats are physical security and product integrity. Ninety-one percent of IT and security decision-makers believe that nation-state actors are likely to launch a new era of cyberattacks by embedding malware or malicious components into hardware and firmware that will make their way into electronics such as computers and electric vehicles. An additional 63% anticipate that the next major nation-state attack will involve malware introduced through hardware supply chains. The ramifications of such an attack would extend well beyond operational disruptions, potentially compromising consumer safety and even national security.

A staggering number of U.S. businesses have already been impacted by nation-state threat actors’ use of malicious hardware, while tech giants such as Apple and Amazon.com have had their supply chains compromised by tiny microchips. And those are just the instances we’re aware of —the true number is likely to be much higher.

This risk is exacerbated by the overwhelming lack of thorough electronic component traceability — the process of identifying country of origin, date and lot code, and other crucial information — allowing malicious and unauthorized components to easily sneak into hardware without detection. Indeed, it’s practically impossible for equipment manufacturers to know if the components placed on their printed circuit board assemblies have been tampered with using current industry practices.

One way to mitigate this risk is by using visual AI to inspect pieces of electronics, from large processors to tiny, passive components, for probe marks, which indicate attempts at tampering. These can potentially be evidence that a component has been “injected” with firmware, and while probe marks are not a guarantee of malicious activity, they indicate tampering of some kind that requires further inspection. Probe inspection is a simple process in theory, but no small task in practice, considering that some components are as small as 1 mm in diameter and can be placed on PCBs at speeds of up to 1,000 per minute. To maintain quality assurance and ensure supply chain security without slowing down production, component monitoring practices must improve — and are, thanks to AI.

A Future-Forward Approach

With supply chains under strict scrutiny, regulations are constantly expanding. AI tools support compliance with the ability to verify every single component assembled into a product. These tools can inspect new components in real time for three key security risks — country of origin, source authenticity, and signs of probing and tampering — and approve or discredit any compromised components before they’re shipped to market.

By identifying the manufacturer and the country of origin of each component, manufacturers can better ensure that they’re using only parts from vendors on authorized vendor lists — first line of defense against component tampering and physical security attacks. Powered by computer vision, visual AI is uniquely able to assess the microscopic differences that signify vendor authenticity on any given component, significantly reducing the chances that compromised, substandard or counterfeit components make their way into final products.

The ability to identify these security risks is critical to fortifying supply chain resilience and upholding product integrity. By utilizing AI to inspect every com…