Over the last few months we have spent a lot of time on introducing adaptive proof-of-work difficulty. This is what we learned.
What we changed
We moved the decision from a single threshold to a continuous score, added an explanation to every decision and made every rule testable against historical traffic before it goes live.
The result is fewer late-night pages for our analysts and — more importantly — fewer real users challenged by mistake.
Compliance is a side effect
Regulators increasingly ask for evidence of resilience, not just promises. An incident timeline with start, peak, vectors and impact is exactly the evidence DORA and NIS2 ask for — and it falls out of good observability for free.
We export incident reports in formats auditors can file without anyone rewriting them.
The numbers
Across the last quarter, 71% of challenged clients never attempted a solution, 24% solved one challenge and then behaved normally, and 5% solved challenges repeatedly while continuing to attack — the last group is where analysts spend their time.
Median added latency for legitimate visitors that were challenged was 280 ms on desktop and 410 ms on mid-range Android devices.
What we got wrong
Our first version challenged too eagerly on mobile networks, where thousands of real users share a handful of carrier-grade NAT addresses. Reputation that is shared is reputation that is noisy.
We now weight fingerprint consistency and session behaviour far more heavily than IP reputation for traffic from known mobile carrier ranges.
Measuring success
We track three numbers for every incident: time to mitigation, the share of attack traffic that reached the origin, and the share of legitimate traffic that was challenged. The first should be under a second, the second under 0.1% and the third under 1%.
Those numbers go into every incident report, and they are the same numbers we are measured against in our SLA.
The economics behind it
A booter service rents out a 100 Gbps attack for less than the price of a pizza. Defending against it with bandwidth alone is a race you lose. Defending against it by making each malicious request cost more than it earns is a race you win.
This is the entire idea behind never metering attack traffic: our costs scale with filtering, not with your invoice.
Protecting the origin
None of this matters if the attacker can reach your origin directly. Historical DNS records, certificate transparency logs and misconfigured subdomains leak origin addresses all the time.
Allow-list the edge ranges, enable authenticated origin pulls and treat any origin IP that ever appeared in public DNS as burned.
{ "match": { "path": "/account/reset", "risk": ">= 58" }, "action": "challenge" }
As always, questions and corrections are welcome at [email protected].
Could you share the dataset behind the percentages?
Great write-up. We saw almost the same pattern on our login endpoint last month.
Do you publish the edge IP ranges in a machine-readable format?
We had the exact false-positive issue with CGNAT carriers. The weighting change makes sense.
Great to hear, thanks for sharing your experience.
The point about origin IPs leaking through certificate transparency logs is underrated.
Verified good bots and allow-listed partners bypass challenges entirely.