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David Hawks
David Hawks

AI | Trust | Cyber


What it takes to trust AI at work

How AI systems behave. Where they fail. Why it matters.

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What your AI access allows

What your AI access allows

Agent investigations and stolen cloud credentials expose two different ways for AI activity to escape its intended purpose


David Hawks

1 October 2026

The pain of revoking exposed credentials

Identity

Governance

Operations

The pain of revoking exposed credentials

CISA’s incident shows why the visible secret is only the start of revocation


David Hawks

17 July 2026

A hotel-search became executable Python

Identity

Agents

Operations

A hotel-search became executable Python

The risk between expected and unexpected inputs


David Hawks

13 May 2026

Model finds signs before human diagnosis

Data

Governance

Trust

Model finds signs before human diagnosis

Clinical signals still leave a consequential decision for the people using them


David Hawks

8 May 2026

Railway’s forgotten API

Identity

Agents

Operations

Railway’s forgotten API

Route exposed two different meanings for the word "permission"


David Hawks

1 May 2026

69 agents trade for their owners

Data

Agents

Governance

69 agents trade for their owners

Real goods, real commitments and no approval of each deal


David Hawks

26 April 2026

The AI buildout - dependency risk

Resilience

Ecosystems

Trust

The AI buildout - dependency risk

A forecast measured in trillions reveals the dependencies behind the services


David Hawks

13 April 2026

Trusted tags redirect to malicious code

Identity

Operations

Ecosystems

Trusted tags redirect to malicious code

The scanner still produced its expected result after the theft had occurred


David Hawks

30 March 2026

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Regular briefings on developments in AI and security, and what they mean for our trust in technology.


What it takes to trust AI

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Mechanism first Consequence second No noise
Security in Context Practical Analysis Trust in AI
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