Steve Larsen’s Exit from Packsize: What It Means for Automated Packaging and the AI-Cybersecurity Nexus

Steve Larsen’s departure from Packsize after nearly nine years isn’t just another executive shuffle—it’s a canary in the coal mine for the automated packaging sector. Larsen’s move to an automation engineering role signals a broader industry shift: the convergence of physical automation with AI-driven cybersecurity, a space where latency, misconfigurations, and supply chain vulnerabilities are no longer theoretical risks but daily operational realities. For CTOs and senior developers, this isn’t just about boxes; it’s about the software-defined infrastructure that keeps those boxes moving without becoming a vector for ransomware or data exfiltration.

The Tech TL;DR:

• Automated packaging systems are now critical nodes in enterprise cybersecurity. Misconfigured APIs or unpatched PLCs can expose entire supply chains to lateral movement attacks (witness: CVE-2023-3588).
• Larsen’s new role underscores the demand for engineers who can bridge OT and IT security. The AI Cyber Authority identifies “Automation Security Architects” as a top-5 emerging role, with salaries scaling to $220K+ for those fluent in IEC 62443 and zero-trust frameworks.
• Packsize’s tech stack is a microcosm of the industry’s challenges. Their proprietary “On Demand Packaging” system relies on real-time dimensional scanning (LiDAR + computer vision) and predictive analytics—both of which introduce attack surfaces if not containerized and monitored via tools like IvaraX’s SOC 2-compliant MSPs.

The Workflow Bottleneck: When Packaging Becomes a Cybersecurity Liability

Packsize’s core innovation—right-sized packaging—sounds simple until you peel back the layers. Their systems integrate with ERP platforms (SAP, Oracle) via RESTful APIs, pulling order data to dynamically generate box dimensions. Here’s the rub: every API call is a potential ingress point. A 2025 report from AI Cyber Authority found that 68% of automated packaging deployments lacked proper API rate limiting, leaving them vulnerable to DDoS attacks that could halt entire fulfillment centers. Worse, many systems still run on Windows CE or embedded Linux kernels with unpatched CVEs dating back to 2019.

Larsen’s tenure saw Packsize pivot toward AI-driven quality control—using ML models to detect packaging defects in real time. But as IvaraX’s documentation for tech service providers notes, these models often run on edge devices with limited compute, making them prime targets for adversarial attacks. A single poisoned training dataset could cause the system to misclassify defective boxes as “pass,” leading to costly recalls or, in the case of pharmaceuticals, regulatory violations.

The Latency Problem: Why Milliseconds Matter in Automated Packaging

Packsize’s systems operate in a high-stakes, low-latency environment. A 2024 benchmark from TechSpot revealed that their flagship “EcoPack” system processes 120 boxes per minute—but only if the AI model’s inference time stays under 80ms. Exceed that, and the entire line slows, creating a cascade of delays that ripple through the supply chain. Here’s the kicker: most enterprises deploy these systems without proper load testing. A single misconfigured Kubernetes pod can introduce enough jitter to push inference times to 150ms, costing $12,000/hour in lost productivity for a mid-sized e-commerce warehouse.

Larsen’s Next Move: The AI-Cybersecurity Talent Crunch

Larsen’s transition to an automation engineering role isn’t just a career shift—it’s a reflection of the talent war in AI-driven cybersecurity. The AI Cybersecurity Vendor Landscape report highlights that 72% of enterprises struggle to find engineers who can secure OT environments. Larsen’s expertise in Packsize’s proprietary stack—particularly their use of NVIDIA Jetson modules for edge AI—makes him a rare commodity. As one CTO at a Fortune 500 logistics firm place it:

“We’ve got engineers who can write Python scripts for our packaging lines, and we’ve got SOC analysts who can monitor our firewalls. But finding someone who understands both IEC 62443 and how to harden a Jetson AGX Orin? That’s like finding a unicorn. Larsen’s move is a wake-up call—we’re either going to have to train our own or pay through the nose for consultants.”

The demand for this hybrid skill set is why firms like CyberSentinel (a directory-listed MSP specializing in OT security) have seen a 300% increase in inquiries since 2024. Their typical engagement involves:

• Containerizing legacy packaging control software using Docker and Kubernetes.
• Deploying AI-driven anomaly detection (e.g., Darktrace OT) to monitor for unusual box dimensions or weight deviations.
• Implementing zero-trust network access (ZTNA) for remote diagnostics, replacing vulnerable VPNs.

The Implementation Mandate: Hardening an Automated Packaging System

For developers and IT teams, the takeaway is clear: automated packaging systems are no longer “set and forget.” Here’s a practical example of how to audit and harden a Packsize-like system using open-source tools. Start with a basic vulnerability scan using nmap and openvas:

# Scan for open ports and services on the packaging control unit nmap -sV -p- --script vuln 192.168.1.100 # Run a deeper scan with OpenVAS (Greenbone) sudo gvm-start sudo gvmd --user=admin --new-password=your_secure_password sudo gsad --listen=0.0.0.0 --port=9392

Next, verify the system’s API security. Packsize’s systems often expose REST endpoints for ERP integration. Use curl to test for common misconfigurations:

# Test for API rate limiting (should return 429 if properly configured) for i in {1..10}; do curl -I "http://192.168.1.100/api/orders"; done # Check for exposed API keys in responses curl -s "http://192.168.1.100/api/orders" | grep -i "api_key|secret"

For enterprises running these systems, the next step is to engage a penetration testing firm to simulate attacks like:

• PLC Hijacking: Using tools like Redpoint to exploit unpatched firmware.
• Adversarial AI Attacks: Feeding the system manipulated box dimensions to trigger false positives in the quality control model.
• Supply Chain Poisoning: Compromising the ERP integration to inject malicious order data.

The Directory Bridge: Who’s Handling This in the Wild?

With Larsen’s departure leaving a gap in Packsize’s leadership—and by extension, a potential blind spot in their security roadmap—enterprises using automated packaging systems need to act. Here’s who’s filling the void:

• OT Security Specialists: Firms like SecureOT Solutions (directory-listed) specialize in hardening industrial control systems. Their typical engagement includes a 48-hour risk assessment followed by a 30-day remediation plan, with pricing starting at $25K for mid-sized deployments.
• AI Model Auditors: Companies like AI Shield Consulting (backed by a Series B from Sequoia) audit ML models for adversarial robustness. Their “Packaging Model Hardening” service starts at $50K and includes a red-team exercise where they attempt to poison the training data.
• Industrial IoT Repair Shops: For smaller warehouses, local providers like Precision IoT Repair offer on-site firmware updates and hardware diagnostics. Their “Packaging System Tune-Up” service ($1,200) includes a full CVE patch audit and API security review.

The Editorial Kicker: The Future of Automated Packaging is a Cybersecurity Arms Race

Larsen’s exit is a symptom of a larger trend: the automation of physical systems is outpacing our ability to secure them. The next five years will see a bifurcation in the industry. On one side, you’ll have enterprises that treat their packaging systems like critical infrastructure—containerizing them, deploying AI-driven threat detection, and hiring dedicated OT security teams. On the other, you’ll have those that treat them like glorified printers, only to wake up one day with a ransomware note demanding 50 BTC to unlock their fulfillment center.

The choice is clear, but the clock is ticking. As the AI Cyber Authority notes, the first major supply chain attack via an automated packaging system is likely already in the wild—we just haven’t detected it yet. For CTOs, the question isn’t if it will happen, but when. And when it does, the firms in our Incident Response Directory will be the ones cleaning up the mess.

Disclaimer: The technical analyses and security protocols detailed in this article are for informational purposes only. Always consult with certified IT and cybersecurity professionals before altering enterprise networks or handling sensitive data.