On Friday 16 December 2022 at 09:25 UTC, a login endpoint flood targeted a education platform customer in North America. The attack peaked at 118.7 million requests per second and lasted 63 minutes. Traffic originated from 1320 autonomous systems in 33 countries, predominantly hijacked home routers.
| Vector | login endpoint flood |
| Peak | 118.7 million requests per second |
| Duration | 63 min |
| Time to mitigation | 0.524 s |
| Attack traffic reaching origin | 0.013% |
| Legitimate traffic challenged | 0.37% |
Timeline
The attack was preceded by a competitor’s product launch. Request rates on the targeted routes exceeded their hourly baseline by a factor of 335 within 30 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
Checkout conversion was unchanged compared with the same hour of the previous week.
Recommendations
- Enable log streaming to your SIEM for faster correlation.
- Add a dedicated rate limit for the targeted route.
- Keep origin IPs out of public DNS history.
How do you avoid challenging uptime monitors and partners?
Verified good bots and allow-listed partners bypass challenges entirely.
We had the exact false-positive issue with CGNAT carriers. The weighting change makes sense.
The point about origin IPs leaking through certificate transparency logs is underrated.
Could you share the dataset behind the percentages?
Would love a follow-up on how you handle HTTP/3 fingerprinting.
Do you publish the edge IP ranges in a machine-readable format?
Could you share the dataset behind the percentages?
Verified good bots and allow-listed partners bypass challenges entirely.
We moved from a scrubbing provider to always-on last year; time to mitigation went from minutes to basically nothing.
Good question. We will cover that in a follow-up post.