Here is a question we could not answer well a year ago: what really happens with reading a Deflecto incident report? We can answer it now.
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.
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.
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.
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.
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.
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.
Challenges beat blocks
Blocking lists go stale within minutes when attackers rotate through residential proxies. Proof-of-work does not care where a request comes from; it only cares whether the client is willing to pay the cost.
For a real browser that cost is a few hundred milliseconds, once per session. For a botnet sending a million requests a minute it is a million puzzles a minute — and at that point the attack stops being cheap.
{ "match": { "path": "/wp-login.php", "risk": ">= 40" }, "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.
Would love a follow-up on how you handle HTTP/3 fingerprinting.
Thanks! Yes — the risk score and its components are included in every log record.
Great write-up. We saw almost the same pattern on our login endpoint last month.
Any plans to support per-tenant limits keyed on a JWT claim?
Our auditors asked for exactly this kind of incident evidence under DORA.
Thanks — sharing this with our on-call team.
Would love a follow-up on how you handle HTTP/3 fingerprinting.