Melih Abdulhayoglu
Why perfect detection is impossible—and why claiming it miseducates the market
100% detection
100% protection
It sounds definitive. Reassuring.
It’s also fundamentally false—not just in practice, but in theory.
When a cybersecurity vendor claims 100% detection, they aren’t merely exaggerating. They are misinforming buyers, miseducating decision-makers, and setting expectations no security system—now or ever—can meet.
That’s not opinion.
That’s mathematics.
Detection Cannot Be Perfect—By Definition
100% Detection Is Not Security—It’s Storytelling
At the core of computing lies a proven limit: the Halting Problem, formalized by Alan Turing.
In plain terms:
There is no algorithm that can analyze all programs and always determine how they will behave.
Translated to cybersecurity:
- You cannot fully predict runtime behavior
- You cannot pre-classify every future binary
- You cannot distinguish “good” from “bad” code with certainty
- You cannot achieve 100% detection without either blocking legitimate software or missing novel attacks
This isn’t a tooling gap.
It’s a law of computation.
Claiming otherwise means redefining the problem—or hoping the audience won’t notice.
“But They Mean MITRE…”
Yes, vendors will clarify that 100% detection refers to MITRE ATT&CK evaluations.
That distinction matters—but only if the buyer understands it.
Most don’t.
MITRE is:
- controlled
- retrospective
- scripted
- limited to a subset of known techniques
It does not:
- predict future attacks
- measure unknown tradecraft
- represent live adversarial adaptation
MITRE is valuable—but it is not reality.
Leading with “100% detection” in a hero banner anchors perception long before nuance appears. That’s not education. It’s marketing sleight of hand.
If 100% Detection Were Real, Breaches Wouldn’t Exist.
100% Detection Is Just Predicting the Future
Detection is inherently backward-looking.
Attackers are not.
Claiming perfect detection is equivalent to saying:
“We can predict every future attack technique before it exists.”
No serious discipline claims this.
- Finance doesn’t promise 100% fraud prevention
- Aviation doesn’t promise 100% failure prediction
- Medicine doesn’t promise 100% diagnosis accuracy
Cybersecurity should not pretend it’s exempt from uncertainty.
The Accountability Gap No One Talks About
Here’s the uncomfortable question:
If vendors are so confident in 100% detection, why don’t they publish real-world historical detection statistics?
Other industries do:
- insurance publishes loss ratios
- cloud providers publish uptime SLAs
- aviation publishes incident rates
Cybersecurity vendors publish… marketing.
Meanwhile, when breaches happen:
- victims are forced to disclose
- customers are notified
- reputations are damaged
But when a vendor’s “100% detection” fails?
Nothing.
No public miss rates.
No failure disclosures.
No accountability.
The buyer absorbs the consequences.
The seller keeps the slogan.
Detection Is Not Protection
Detection asks: “Did I recognize this?”
Protection asks: “Did damage occur?”
They are not the same.
A system can detect nothing and still prevent harm.
A system can detect everything it knows and still fail catastrophically on what it doesn’t.
Claiming 100% detection avoids the harder, more honest question:
What happens when detection inevitably fails?
The Honest Position the Industry Avoids
Real cybersecurity begins with one admission:
We cannot predict the future.
Once you accept that, better architectures emerge:
- assume novelty
- assume detection failure
- reduce blast radius
- prevent damage without certainty
That’s how mature engineering disciplines evolve.
Until then, “100% detection” remains what it truly is:
- a mathematical impossibility
- a miseducation of buyers
- and a disservice to cybersecurity as a profession
If someone promises you 100% detection, ask one question:
“Of what—past attacks, or the future?”
Because only one of those is knowable.
