
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| POST seen | Behavioral anomaly detected by automated analysis | +8 | |
| UA bot: python | Known bot/crawler User-Agent detected | +40 | |
| UA changed | Multiple User-Agents — bot rotation technique | +25 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Address UA spoofing from 38.60.221.123: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
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.
38.60.221.123 has been assigned a threat score of 73/100 (High). This classifies it as a high-severity threat. Proactive blocking is recommended for sensitive infrastructure.
The following attack categories were identified:
IP address 38.60.221.123 has been traced to Moscow, Russia, operating on the network of Kaopu Cloud HK Limited. Our threat detection systems have flagged this address based on observed malicious behavior patterns. Our sensors captured 459 malicious requests from this address across a 2-day span, reflecting a sustained attack cadence of ~229.5 requests per day. Operating from a residential network, this IP may represent a compromised home gateway or IoT device that has been drafted into a larger attack infrastructure. The IP exhibits User-Agent manipulation, switching between different browser identities or sending empty headers. A threat score of 73/100 places this IP in the high-risk category. Blocking at the firewall level is recommended.
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.
TLS fingerprinting creates unique identifiers based on how clients negotiate encrypted connections. The JA3 and JA4 methods generate hashes from TLS ClientHello parameters, enabling identification of specific tools and malware regardless of IP address changes.
Cache poisoning manipulates web cache behavior to serve malicious content to other users. By identifying unkeyed inputs that influence cached responses, attackers can inject JavaScript, redirect users, or cause denial of service at scale through the cache infrastructure.