UNB Researcher's 'Trust Passport' Would Stamp Every AI Reply with Its Risk Profile

What if every AI-generated reply came with its own Trust Passport — a stamp-sized summary of how much confidence you should actually place in it?

That's the idea behind a poster from UNB's Canadian Institute for Cybersecurity researcher Vidushi Agarwal, set to appear at the PST Cybersecurity Summit 2026 in Fredericton on Aug. 20.

The problem: confident, unverifiable answers

Enterprises are wiring large language models into pipelines that retrieve documents, call tools, and answer directly to employees and customers. LLMs deliver those answers with uniform confidence — whether the underlying retrieval was solid, the tool call was risky, or the model is improvising. For a business deciding whether to act on an AI answer, that flat confidence is the problem.

The approach: a risk snapshot per response

The Trust Passport concept gives each AI response a clear snapshot of potential risks across four signals:

• Unreliable retrieved information — did the sources the model leaned on actually support the answer?
• Sensitive-data exposure — did the pipeline surface confidential or personal data it shouldn't have?
• Risky tool use — did the model invoke tools or actions that carry consequence?
• Weak factual support — is the answer grounded, or is it plausible-sounding filler?

By bringing those signals together, the passport lets users quickly gauge how much confidence a response deserves — and, the poster argues, make better-informed decisions when working with LLMs.

Why it matters

"Trust but verify" is the operating principle of most security-conscious AI deployments, and verification is currently manual and ad hoc. A standardised per-response risk label is the kind of infrastructure that could make enterprise LLM adoption safer — and it's a research direction squarely in the wheelhouse of the institute that anchors Fredericton's security cluster.

Sources

• Canadian Institute for Cybersecurity: Research Spotlight post — project summary, author, and the four risk signals