{"id":21828,"date":"2026-06-30T10:11:20","date_gmt":"2026-06-30T10:11:20","guid":{"rendered":"https:\/\/any.run\/cybersecurity-blog\/?p=21828"},"modified":"2026-06-30T13:23:17","modified_gmt":"2026-06-30T13:23:17","slug":"us-manufacturer-security-risk","status":"publish","type":"post","link":"https:\/\/any.run\/cybersecurity-blog\/us-manufacturer-security-risk\/","title":{"rendered":"Closing the Supplier Security Gap: How a US Manufacturer Cut Third-Party Risk and Doubled SOC Triage Speed"},"content":{"rendered":"\n

For a US automotive manufacturer working with more than 200 active vendors, supplier file intake had become a growing security and cost challenge. That pressure is especially high in manufacturing, where SOC teams carry an average workload 18% higher<\/strong> than teams in other industries.<\/p>\n\n\n\n

By introducing behavioral sandboxing<\/a> and threat intelligence<\/a>, the company made triage 2x faster<\/strong>, achieved an MTTD of 20 seconds<\/strong>, improved MTTR<\/strong> and detection, and analyzed hundreds of supplier files every week without adding headcount.<\/p>\n\n\n\n

A US Automotive Manufacturer Built Around a Large Supplier Ecosystem <\/h2>\n\n\n\n

The company is a US-based automotive manufacturer operating within a highly interconnected supply chain. Its daily operations depend on continuous collaboration with more than 200 active vendors and third-party contractors. <\/p>\n\n\n\n

These external partners regularly exchange files with the organization to support ongoing manufacturing, technical, and business processes. This makes supplier communication essential to keeping operations moving, but it also creates a large and constantly changing entry point for risk. <\/p>\n\n\n\n

The SOC is responsible for protecting the company\u2019s environment while ensuring legitimate supplier activity is not delayed. As the volume of incoming files grew, the team needed a way to analyzesubmissions consistently, improve detection and response speed, and reduce third-party exposure without increasing staffing costs. <\/p>\n\n\n\n

The Challenge: Supplier Files Were Entering Without a Consistent Analysis Process <\/h2>\n\n\n\n

Before ANY.RUN, the company had no systematic process for analyzing files received from vendors and third-party contractors. <\/p>\n\n\n

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US Manufacturer\u2019s security challenges <\/em><\/figcaption><\/figure>\n<\/div>\n\n\n

Existing security controls could flag a submission as suspicious, but they did not always show what the file would actually do after execution. Without behavioral evidence, analysts were left with incomplete indicators and uncertain verdicts.<\/p>\n\n\n\n

\u201cThe volume itself was not the only challenge. The bigger issue was that analysts did not have enough context to quickly decide which supplier files were safe and which required further action.\u201d <\/p>Head of SOC, US automotive manufacturer<\/em><\/strong> <\/cite><\/blockquote><\/figure>\n\n\n\n

This created several problems for the SOC:<\/p>\n\n\n\n

A Security Gap in Supplier File Intake <\/h3>\n\n\n\n

Files could enter the environment without passing through a dedicated behavioral analysis layer.<\/p>\n\n\n\n

This limited the company\u2019s ability to identify threats that appeared harmless during static inspection but revealed malicious activity only after execution.<\/p>\n\n\n\n

The risk was especially significant in a large supplier ecosystem. A compromised vendor account or mailbox could turn a trusted communication channel into an indirect route into the organization. With more than 47%<\/strong> of attacks on manufacturing companies originating from email, supplier messages and attachments represented a critical part of the company\u2019s third-party attack surface.<\/p>\n\n\n\n

High Escalation Rates <\/h3>\n\n\n\n

Tier 1 analysts often lacked enough context to confidently close suspicious submissions. <\/p>\n\n\n\n

As a result, the majority of these files were escalated to more experienced analysts. Senior team members had to spend time reviewing cases that could have been resolved earlier with clearer evidence. <\/p>\n\n\n\n

Rising Investigation Costs <\/h3>\n\n\n\n

The supplier network continued to generate a high volume of files. Handling that growth through manual investigation would have required more analyst hours and, eventually, additional headcount. <\/p>\n\n\n\n

Without a more scalable process, the company risked paying more just to maintain the same level of protection.<\/p>\n\n\n\n

This pressure is especially high in manufacturing, where SOC teams carry an average workload 18% higher<\/strong> than security teams in other industries. For companies managing large supplier ecosystems, that makes manual investigation increasingly difficult to sustain.<\/p>\n\n\n\n

Longer Exposure to Potential Threats <\/h3>\n\n\n\n

Every delay in validating a suspicious file extended the period during which the organization could not confidently allow, block, or contain it. <\/p>\n\n\n\n

In a manufacturing environment, a missed threat can affect more than an individual endpoint. It can disrupt operations, expose sensitive data, and weaken trust across the supplier network. <\/p>\n\n\n\n

Building a Scalable Supplier File Triage and Analysis Process with ANY.RUN <\/h2>\n\n\n\n

The manufacturer introduced a consistent process for analyzing files received from vendors and third-party contractors. <\/p>\n\n\n\n

By combining behavioral analysis with threat intelligence, the SOC gained both the evidence needed to understand what a file does and the context required to assess the wider threat behind it. <\/p>\n\n\n\n

\u201cWe have over 200 active vendors sending files into the environment. ANY.RUN gave us a scalable way to analyze that volume and make triage much faster without adding headcount\u201d<\/p>Head of SOC, automotive manufacturer<\/cite><\/blockquote><\/figure>\n\n\n\n

Instead of relying on isolated alerts or incomplete indicators, analysts could detect malicious submissions more accurately, reach verdicts faster, resolve more cases at Tier 1, and reduce the amount of senior analyst time spent on routine reviews. <\/p>\n\n\n\n

This improved detection quality while contributing to lower MTTD and MTTR across supplier-related investigations. <\/p>\n\n\n\n

Reaching Faster Verdicts with Behavioral Evidence <\/h3>\n\n\n\n

The SOC reduced triage time by giving analysts direct visibility into what suspicious supplier files did after execution. <\/p>\n\n\n\n

Files were safely analyzed in ANY.RUN\u2019s cloud-based Interactive Sandbox<\/a>, where the team could review process activity, network connections, system changes, commands, and other behavior without exposing the production environment. <\/p>\n\n\n

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Full chain of a complicated EvilTokens attack on US companies analyzed in just 1 minute<\/em><\/figcaption><\/figure>\n<\/div>\n\n\n

This replaced incomplete indicators with clear evidence of whether a submission was malicious and how it could affect the business. <\/p>\n\n\n\n

\u201cWe no longer have to spend time piecing together what a supplier file might do. The behavior is visible in one place, which makes decisions faster and easier to defend.\u201d<\/em> <\/p>Head of SOC, US automotive manufacturer<\/em><\/strong> <\/cite><\/blockquote><\/figure>\n\n\n\n

Structured and visual results also helped Tier 1 analysts move from alert to verdict with fewer manual checks. Instead of reconstructing file behavior across disconnected tools, they could validatesuspicious submissions faster and make more confident decisions. <\/p>\n\n\n\n

The faster path from alert to confirmed verdict contributed to improved MTTD, while clearer evidence and fewer repeated checks helped reduce MTTR. <\/p>\n\n\n\n\n

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\nCut investigation time<\/span> with clear behavioral evidence
Help analysts reach faster decisions. <\/span>\n<\/p>\n\n\nAccelerate triage now  \n<\/a>\n<\/div>\n\n\n\n