[Blog] Security in the Age of AI: Why Trust Is Moving Closer to Hardware
Posted 04/16/2026 by Mamta Gupta, AVP, Strategic Business Development, Datacenter & Security
In early 2026, a quiet shift became impossible to ignore: artificial intelligence (AI) moved from helping defenders to operating like an attacker at scale. The cybersecurity community took notice when researchers revealed that an advanced AI system, known publicly as Claude Mythos Preview, was able to independently discover and exploit serious software vulnerabilities. Many of these weaknesses had existed for years in widely used operating systems and software, despite extensive testing and review.
What made this moment stand out was not just the number of vulnerabilities uncovered, but the speed at which it happened. Security work that once required skilled experts working for weeks was completed in hours.
That compression changes more than response times. It changes what can be trusted, and where. These events brought a long-standing question into sharper focus: if software can now be analyzed and attacked at machine speed, where should systems place their deepest trust?
How AI is Reshaping the Security Landscape
AI has fundamentally changed the dynamics of software security, not incrementally, but structurally. For decades, cybersecurity strategies have centered on software. Firewalls, monitoring tools, and regular updates were designed around the idea that attacks would be slow enough for humans to detect and respond.
Public disclosures around systems like Mythos challenge that assumption. Independent reporting showed that advanced AI could scan mature codebases, identify subtle problems, verify exploitability, and combine multiple weaknesses into real-world attacks in a matter of hours. As a result, the window between discovering a software flaw and exploiting it has narrowed dramatically.
This shift places unprecedented pressure on software. Software remains essential, but it is inherently exposed. It is designed to be flexible, updatable, and accessible, which makes AI-driven analysis thrive. It does not tire, and it can examine vast systems in ways humans cannot.
Security strategies that depend on vulnerabilities staying hidden for long periods are becoming increasingly unrealistic. In practical terms, software increasingly needs to be treated as a fast‑moving layer rather than the foundation where trust begins and ends.
Why Trust Starts in Hardware
Hardware operates under a different set of constraints. It is physical and manufactured, not downloaded or rewritten. Attacking hardware typically requires physical access, specialized equipment, and deep expertise, raising both cost and complexity. More importantly, hardware can enforce boundaries and invariants that software cannot reliably self-enforce when analyzed at machine-speed. These characteristics make hardware a more stable place to anchor trust as software becomes easier to interrogate.
This is where the concept of a hardware root of trust (HRoT) enters the picture. A HRoT is a secure component built into a system that establishes trust from the moment the device powers on. It allows a system to verify that it is running authorized software and that critical components have not been altered. In an AI-driven threat environment, this creates a known-good starting point, even when everything above it must be assumed to be under constant scrutiny and pressure.
The importance of this approach becomes even clearer in long‑lived systems. Many platforms are expected to operate for years or decades and cannot be frequently updated due to operational constraints, safety requirements, or deployment environments. Hardware‑based trust provides a steady reference point that does not depend on continuous patching or rapid response cycles.
As systems age and threats evolve, trust must move downward through the architecture, anchoring in components that are hard to modify, observe, or undermine.
Hardware and Software Working Together
This shift does not replace software security. Hardware provides stability, while software provides flexibility. Together, they enable stronger security in an AI-accelerated world. For system designers, decision makers, and regulatory bodies, this shift carries concrete implications. If AI dramatically reduces the cost of finding exploitable weaknesses, systems must reduce the value of finding them.
That typically means anchoring identity and integrity in hardware, enforcing secure and measured boot paths, planning for crypto-agility as algorithms and standards evolve, and designing recovery mechanisms that assume compromise is possible. These are architectural decisions, not incremental security features, and they are becoming central to building resilient systems in the AI age.
Re-anchoring Trust in an AI Era
AI systems like Mythos have exposed the limits of old security assumptions. Resilient systems anchor trust where it is hardest to undermine. Hardware roots of trust are becoming central to modern secure system design.
Across the semiconductor ecosystem, this shift is already reflected in practical implementations that combine HRoT, secure boot, device identity, and resilient recovery paths.
At Lattice Semiconductor, this evolution is being addressed not only through a robust portfolio of security-focused products and solutions, but through security leadership. Lattice is advancing low power FPGA‑based approaches to hardware‑rooted trust, supporting secure boot, attestation and trusted updates, crypto-agility, and readiness for post‑quantum requirements across Compute, Communications, Industrial, and other emerging applications.
If you are building or modernizing long‑lived systems, contact us today to evaluate HRoT designs and practical deployment strategies. To explore Lattice’s award-winning security solutions, visit our website.
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