Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

A Technical blog series on where sensitive data moves in an AI workflow, what decisions Protecto makes at each point, and what enterprises get from enforcing policy once instead of everywhere.

Zero Trust is often summarized as “never trust, always verify.” More precisely, it is a security model built on the premise that trust should never be granted implicitly based on where a user, device, workload, or resource sits. That makes Zero Trust much bigger than deploying a particular product or turning on a handful of access policies.

Telling employees to “use AI responsibly” leaves too much open to interpretation.

This post is based on Mackenzie's conversation with Jason Haddix on The Secure Disclosure podcast. Listen to the full episode or watch below. Jason Haddix has topped the Bugcrowd leaderboards, run security as CISO of Ubisoft, and wrote The Bug Hunter's Methodology, the playbook a lot of working pentesters learned from, so his read on the direction of the field is worth listening to. He believes that “90% of pen tests will be done by AI” in the near future.

The blast radius of a prompt injection against your coding assistant was set weeks ago, by whoever built the dev environment image. Same assistant, same model, same injected sentence: on a laptop it collects every repository, SSH key and cloud login the developer holds; on a provisioned dev box it collects an organization token plus whatever the image left behind; on a CI runner it collects a deployment credential and a network path to production. Three environments, three incidents, one payload.

Leaked credentials now reach public sources faster than any security team can review them by hand. GitGuardian Public Secrets Monitoring runs agents over every public incident and returns a comprehensive verdict.

Security teams already know employees use generative AI. The harder problem is buying the right platform before unsanctioned apps move sensitive data outside your visibility and control. UpGuard research found 81% of employees and 88% of security leaders use unapproved AI tools, and 45% of workers find a workaround when their employer blocks an app. That last number should shape your buying criteria more than the first two. Demand doesn't disappear when you block it. It moves somewhere you can't see.

An application that was AI-free at the last audit may be processing corporate data through a language model today. Nobody procured it, nobody approved it and nobody was asked. A vendor shipped a release. ‍ Third-party AI governance is built almost entirely around procurement. Assess the vendor, negotiate terms, sign a data processing agreement, add the tool to a register. The apparatus requires a purchasing event, and an embedded feature produces none, so the apparatus never engages. ‍