AI Trust Validation: Agents Testing Agents at Scale

Last week, 404 Media reported that a hacker was able to inject malicious code into an Amazon Q Developer add-on hosted on GitHub. The code, once merged, was deployed downstream into production environments and instructed the assistant to delete user files. According to the report, this was a proof-of-concept stunt—an adversarial test disguised as an attack. But the implications are very real.

To Amazon’s credit, they say the issue was resolved and no customer data was lost. But notably, there was no public advisory, no CVE, and no warning issued to teams relying on the tool. In a space moving this fast, that’s not just an oversight—that’s a liability.

It’s Time We Treat Trust as a First-Class Deliverable

The biggest takeaway from this event isn’t that an AI system can be compromised. We already knew that. It’s that many teams are still pushing updates without a clear, enforceable model for trust validation before release.

We’re building autonomous agents—tools designed to think and act independently. Yet too often, we’re still testing them like static apps. That mismatch is where risk compounds.

At Swept, we believe:

1. Every release should pass adversarial interrogation. Not just functional testing. You should be actively trying to break your agent the way a red team would—prompt injection, model subversion, malicious dependency, misuse of tools.
   
   
2. Agents should be tested by agents. If your software is built to reason, simulate, and self-adjust—why not point that capability inward? Let one agent question the assumptions of another. Trust loops are not a futuristic idea; they’re an under-utilized safeguard today.
   
   
3. Agentic testing is the only way to reach scale. The behavioral search space of an autonomous system grows exponentially. Human QA simply can’t cover that surface area in a reasonable time or budget, but agent-driven test harnesses operate at machine speed and cost, making thorough coverage feasible.
   
   
4. You can’t validate trust retroactively. Post-incident audits are important, but they’re cleanup. If we want to prevent these kinds of failures, trust has to be embedded from the start. Certification, reproducible builds, and agent-native validation must become standard.
   
   

TL;DR: This Was Preventable

Yes, the AWS incident is concerning—but it’s also predictable. And, most importantly, preventable.

If we build from a foundation of trust validation—where releases aren’t just pushed, but interrogated—then we reduce the surface area for exactly this kind of exploit.

Let’s move beyond the checklist. Let’s make trust the spec.