

In February 2026, Dutch telecom provider Odido disclosed a cyber incident affecting personal data tied to more than six million accounts.
Odido is one of the country’s major telecom providers, serving millions. This incident caught my attention for the scale and because the moment data is already stolen, you’re no longer preventing impact, you’re managing consequences...
The Odido story isn’t interesting because attackers were “clever.” It’s interesting because it shows how quickly a familiar pattern becomes large when warning signals exist, but decision pathways lag.
There’s a moment in many incidents where nothing looks “down”… and yet control is already slipping.
Not because systems failed.
Because trust did.
What makes the reporting uncomfortable is precisely that the incident was not exotic or dependent on a movie-plot zero-day. It emerged from a chain of plausible weaknesses: the social manipulation of an employee, access to a customer contact system and permissions that placed a broad set of records within reach.
Most organisations will read this and think: “So… train people better.”
Training matters. But notice what that framing does.
It quietly places the centre of gravity on the individual who took the call.
A more useful lesson is structural: a secure environment shouldn’t rely on a single person being impossible to manipulate — and the way access is designed and governed matters.
This is the boundary leaders tend to underestimate:
We treat identity controls as “security”.
But in practice, identity controls are governance — because they define who can act, what they can reach, and how quickly we can reduce risk without freezing operations.
In other words: the incident doesn’t start when data leaves.
It starts when leaders realise they no longer know what “legitimate access” means.
And once legitimacy is uncertain, every response step becomes governance:
This is the part that doesn’t show up in many incident decks:
Detection buys awareness. Only pre-decided containment buys time.
A system failure is visible: outage, latency, broken process.
A trust failure is quieter: the system is still running, but you can’t prove who is driving.
That is why “we detected it” is not the same as “we controlled it”.
And why “we restored services” is not the same as “we regained governability”.
Odido customers could still use services, according to the company’s own communication.
But the incident still carried weight because identity and access pathways touched sensitive data at scale.
These aren’t technical questions. They force clarity before the next uncomfortable hour arrives.
If you want to make this practical, the next step isn’t more policy, it’s a simple pressure-test of the first-hour decisions.
Don’t start by writing a new policy.
Run a 60-minute identity-trust exercise with three timed phases:
T+0 to T+10: credible signal, incomplete evidence
What do we do immediately that is reversible? Who authorises it?
T+10 to T+30: suspicion of persistence
How do we invalidate active trust (sessions/tokens), and what breaks operationally?
T+30 to T+60: stabilisation
How do we progressively restore controlled access without re-opening the same pathways?
The value isn’t the tabletop discussion.
The value is discovering whether your organisation can execute the first move without debate, confusion, or operational shock.
So, I’ll leave you with a question I find more useful than “How do we prevent every breach?”:
If identity trust broke tomorrow, would your first hour be governed… or negotiated?
I can also share how I pressure-test this in practice through a resilience assessment in your own sandbox environment, with your existing security stack enabled.
If any of these would be useful, feel free to contact me.