
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Burst: 48 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 162 req / 10s | Abnormally fast request rate — automated scanning | +35 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 169.150.218.38 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 169.150.218.38.
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
This IP was checked against major DNS-based blacklists used by mail servers and firewalls worldwide.
Checked: Spamhaus, SpamCop, Barracuda, SORBS, CBL, UCEProtect. Results may change over time.
169.150.218.38 has been assigned a threat score of 95/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
The following attack categories were identified:
169.150.218.38 is registered in Amsterdam, Netherlands, operating on the network of Datacamp Limited. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. The address has been active for 1 days in our monitoring system, producing 1 flagged requests at a rate of ~1/day. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. The dual attack vectors of User-Agent Anomaly combined with Request Flooding indicate a coordinated assault rather than opportunistic scanning. With 107 flagged addresses, Netherlands represents a significant presence in our threat database. At 95/100, this is an extremely high-risk address. All traffic should be considered hostile.
This IP is classified as residential, suggesting it may belong to a compromised home device, IoT botnet member, or an infected personal computer. Residential IPs involved in attacks often indicate malware infection without the owner's knowledge.
Examining HTTP headers beyond User-Agent reveals attack tools and automated scripts. Missing standard headers, unusual ordering, non-standard values, and inconsistencies with claimed client identity all serve as reliable detection signals.
Correlating logs across web servers, firewalls, DNS, and authentication systems reveals attack patterns invisible in individual log sources. Modern SIEM platforms use statistical analysis to connect related events across time and systems.