Positive security for APIs from your OpenAPI spec (part 2)

We get asked about positive security for APIs from your OpenAPI spec more than almost anything else, so here is the long answer.

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.

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.

Why per-route baselines matter

A thousand requests per second to your homepage is Tuesday. A thousand requests per second to your password-reset endpoint is an attack. Global rate limits cannot tell the difference; per-route baselines can.

We learn the normal shape of traffic per route and per hour of the week, so a surge on a sensitive endpoint raises the risk score long before it approaches a global threshold.

Testing in production, safely

Every rule starts in log mode. We replay the previous seven days of traffic through it and show exactly which requests it would have affected before anyone can promote it to challenge or block.

This one feature has prevented more incidents than any detection we have ever shipped.

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.

What actually happens during a flood

The first thing to fail during a layer 7 flood is almost never bandwidth. It is connection slots, worker processes or database connections on the origin — resources measured in hundreds or thousands, not gigabits. An attacker who can make each request expensive only needs a few thousand requests per second.

That is why we score requests before they are proxied. By the time a request reaches your origin, it has been attributed to a client, compared against that client’s history and weighed against the current load on the route it targets.

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.

{ "match": { "path": "/wp-login.php", "risk": ">= 67" }, "action": "challenge" }

If you run into any of this in your own environment, our SOC is happy to take a look — even if you are not a customer.