From Blind Spot to Same-Day Fix: How Tempo Closed a Critical Gap in Their AI Stack
How a company discovered and fixed a critical exposure in their AI infrastructure hours after continuous validation began.
Every security team has a version of the same conversation. Someone asks: “Are we exposed?” And the honest answer, more often than anyone wants to admit, is: “We think so. But we’re not certain.”
That gap between thinking and knowing is where serious incidents begin.
Tempo Beverages, one of Israel’s largest food and beverage companies, knew their digital footprint had grown fast: consumer sites, international brand properties, Azure cloud services, and a new generation of AI-powered applications. What they didn’t know was whether their security reviews were keeping pace.
A Surface That Had Outgrown Its Oversight
As Tempo accelerated its digital transformation, new services and AI capabilities were being deployed continuously — far faster than traditional, scheduled security assessments could reliably track. The team wasn’t operating recklessly. They were operating at the pace modern business demands. But that pace had quietly created blind spots no one knew about.
Periodic penetration tests and point-in-time vulnerability scans had been the standard. The problem: by the time a test runs, the environment it’s assessing has already moved on. New endpoints appear. Services get spun up. AI tools get integrated. Each change shifts the exposure profile in ways that only become visible if someone is continuously watching.
Tempo needed more than a snapshot. They needed a live picture. That’s what brought them to ULTRA RED.
The Vulnerability No One Was Looking For
Within hours of onboarding, ULTRA RED’s platform surfaced a critical exposure in Tempo’s cloud-hosted AI infrastructure — something no previous assessment had caught.
It wasn’t a theoretical flag or a low-confidence alert. It was a fully validated, exploitable vulnerability, with proof-of-concept evidence showing exactly how the risk could be realized. A clear finding that demanded immediate action.
Tempo’s team acted immediately. The issue was closed the same day.
“ULTRA RED found a critical vulnerability in our AI infrastructure that we didn’t know about. The proof-of-concept evidence made it immediately clear what needed to be fixed — we remediated it the same day. This speed and certainty is exactly what we need.”
— Tempo Security Team
Why Traditional Approaches Miss This
The exposure wasn’t a known software flaw or an obvious misconfiguration. It was a legitimate AI service, deployed legitimately, that had become exposed in a way that created real risk. A scheduled pen test wouldn’t have caught it in time. A CVE scanner wouldn’t have flagged it at all.
This is the structural gap that continuous validation is built to close. Modern cloud and AI environments move too fast for point-in-time assessments to keep pace. New services appear. Infrastructure evolves. And with each change, the picture your last assessment captured drifts further from reality.
Validation Over Volume
ULTRA RED validated dozens of attack vectors across Tempo’s cloud, web, and AI surfaces, surfacing only confirmed, real-world risk with evidence to act on. The result was a 2–3× reduction in remediation cycles, not because the team worked harder, but because they worked on the right things with certainty.
“Continuous validation has changed how we approach security. Instead of waiting for the next penetration test to discover what changed, we have live visibility into our attack surface and proof that what ULTRA RED surfaces is real risk, not noise.”
— Tempo Security Team
Three Lessons From the Tempo Story
- AI services are a fast-growing and underassessed attack surface. If your organization is deploying AI on cloud infrastructure, your exposure profile looks different from what your last assessment captured.
- Theoretical risk is not the same as real risk. Validation is the step that turns a list into a decision.
- Time-to-fix is a function of evidence quality. Clear proof removes the friction that slows down response.
Read the full case study to see how Tempo built continuous exposure validation across its cloud, web, and AI infrastructure — and what it means for organizations navigating the same challenge.
