Attack seasonality: sports finals, sales and tax deadlines

Over the last few months we have spent a lot of time on attack seasonality: sports finals, sales and tax deadlines. This is what we learned.

Latency budget

Our budget for the whole filtering pipeline is one millisecond at the 99th percentile. Anything that cannot be decided within that budget runs asynchronously and influences the next request from the same client, not the current one.

That constraint shapes everything: data structures, where state lives and which signals we are willing to compute inline.

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.

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.

Lessons for your own runbook

Know who can change DNS at two in the morning. Know your origin IPs and who can rotate them. Know which routes are expensive, and have a rate limit ready for each of them.

Most outages during attacks are not caused by the attack itself but by rushed changes made while under pressure.

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.

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.