On Monday 8 January 2024 at 15:04 UTC, a search endpoint flood targeted a tax authority portal customer in Southeast Asia. The attack peaked at 559.7 million requests per second and lasted 23 minutes. Traffic originated from 349 autonomous systems in 96 countries, predominantly a Mirai-derived IoT botnet.
| Vector | search endpoint flood |
| Peak | 559.7 million requests per second |
| Duration | 23 min |
| Time to mitigation | 0.760 s |
| Attack traffic reaching origin | 0.039% |
| Legitimate traffic challenged | 0.62% |
Timeline
The attack was preceded by a hacktivist channel announcing the target. Request rates on the targeted routes exceeded their hourly baseline by a factor of 159 within 26 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.
- Lower challenge thresholds on authentication endpoints during high-risk events.
- Review allow-listed partner ranges quarterly.
Is the risk score exposed in the logs so we can build our own dashboards on it?
How do you avoid challenging uptime monitors and partners?
Verified good bots and allow-listed partners bypass challenges entirely.
The billing model is what got our finance team on board, honestly.
Our auditors asked for exactly this kind of incident evidence under DORA.
Clear and practical, thanks.
Could you share the dataset behind the percentages?
This matches what we see in iGaming around big matches.