Why Proprietary Software, Hardware & Protocols Face AI Security Risks
Why Proprietary Software, Hardware & Protocols Face AI Security Risks
https://www.infosecurity-magazine.com/blogs/why-software-faces-ai-driven/
Publish Date: 2026-05-06 04:30:00
Source Domain: www.infosecurity-magazine.com
When Anthropic launched Project Glasswing in April 2026 – a consortium of eleven major companies deploying its Claude Mythos Preview model to find vulnerabilities in critical open-source software − the cybersecurity industry applauded. And rightfully so: Mythos discovered bugs that had hidden in heavily-audited codebases for decades.
But Glasswing’s focus on open source, while valuable, addresses the most visible part of the problem. Open-source software has always benefited from community review, etc. The software that nobody has been looking at – proprietary binaries, embedded firmware, legacy protocols, even chip microcode – carries a far larger and more dangerous accumulation of undiscovered vulnerabilities. And the same AI capabilities that make Glasswing possible are about to expose all of it.
Code that nobody looks at accumulates hidden bugs. Proprietary software operates under a fundamentally different model. Its security posture has historically relied on a simple premise: if attackers can’t read the source code, they’ll have a harder time finding bugs. This isn’t better security – it’s security by obscurity.
The Binary Barrier Is Falling
The traditional answer was it doesn’t matter because attackers can’t read proprietary source code. They only get compiled binaries – stripped of variable names, comments, and structure. That answer is becoming obsolete.
What wasn’t solved was the human bottleneck. A typical security audit covers only a fraction of a codebase – auditors triage by intuition, focus on high-risk surfaces, and leave vast swaths of code untouched. LLMs eliminate this bottleneck. Claude Mythos Preview can take a closed-source, stripped binary, reconstruct plausible source code, and systematically analyze it for vulnerabilities.
Evidence Is Already Here: Edge Devices Under Siege
This isn’t a theoretical risk. That exposure is already being collected – violently – on one category of proprietary…
