eBPF maps, hash collisions and a very long night (part 3)

Here is a question we could not answer well a year ago: what really happens with eBPF maps, hash collisions and a very long night? We can answer it now.

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.

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.

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.

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.

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.

{ "match": { "path": "/login", "risk": ">= 69" }, "action": "challenge" }

We will follow up with the numbers from the next quarter.

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