GDPR and request logs: what we store and why

Here is a question we could not answer well a year ago: what really happens with gDPR and request logs: what we store and why? We can answer it now.

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.

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.

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.

Observability first

Every mitigation decision is logged with its reasons, and every log line can be traced to the rule and score components that produced it. When a customer asks why a request was challenged, the answer is a link, not a guess.

Logs stream to the customer’s SIEM within seconds, which also means their security team sees attacks in the same tools they use for everything else.

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.

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.

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.

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.