On Monday 1 August 2022 at 20:16 UTC, a login endpoint flood targeted a online casino customer in the UK. The attack peaked at 230.2 million requests per second and lasted 165 minutes. Traffic originated from 3212 autonomous systems in 11 countries, predominantly a Mirai-derived IoT botnet.
| Vector | login endpoint flood |
| Peak | 230.2 million requests per second |
| Duration | 165 min |
| Time to mitigation | 0.761 s |
| Attack traffic reaching origin | 0.033% |
| Legitimate traffic challenged | 0.78% |
Timeline
The attack was preceded by no stated motive. Request rates on the targeted routes exceeded their hourly baseline by a factor of 660 within 31 seconds. The risk score of participating clients crossed the challenge threshold automatically and proof-of-work difficulty rose with origin load.
What the customer saw
No customer-visible impact. The on-call engineer was notified and acknowledged the incident from the dashboard.
Recommendations
- Enable log streaming to your SIEM for faster correlation.
- Review allow-listed partner ranges quarterly.
- Lower challenge thresholds on authentication endpoints during high-risk events.
Interesting that most attacks are under ten minutes. Our experience is similar.
This matches what we see in iGaming around big matches.
We moved from a scrubbing provider to always-on last year; time to mitigation went from minutes to basically nothing.
Thanks! Yes — the risk score and its components are included in every log record.
Solid runbook advice. The DNS-at-2am point hit home.
Good question. We will cover that in a follow-up post.
The billing model is what got our finance team on board, honestly.
Machine-readable ranges are at /ips.json and via the API.
Great write-up. We saw almost the same pattern on our login endpoint last month.
Would love a follow-up on how you handle HTTP/3 fingerprinting.
Great to hear, thanks for sharing your experience.
Solid runbook advice. The DNS-at-2am point hit home.