
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 |
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 34.92.178.17: 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.
34.92.178.17 has been assigned a threat score of 75/100 (High). The IP is rated as a high-level threat. Network administrators should implement blocking rules and monitor for any connections from this address.
The following attack categories were identified:
The address 34.92.178.17 originates from Hong Kong, Hong Kong, operating on the network of Google LLC. It was identified through automated analysis of incoming network traffic across monitored endpoints. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. Classified as a hosting IP, this address likely runs on a rented server or cloud instance. Attackers prefer datacenter IPs for their high bandwidth and disposable nature. The IP exhibits User-Agent manipulation, switching between different browser identities or sending empty headers. Hong Kong currently accounts for 101 blocked IPs in our database, making it a significant source of malicious traffic. The score of 75/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.
This IP belongs to a hosting or data center provider. Malicious traffic from hosting infrastructure often originates from compromised VPS instances, rented servers used for scanning campaigns, or abused free-tier cloud accounts. Hosting providers typically respond to abuse reports within 24-72 hours.
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.
Analyzing network flows (NetFlow, sFlow, IPFIX) provides visibility into traffic patterns without inspecting packet contents. Flow data reveals scanning activity, data exfiltration, lateral movement, and command-and-control channels at scale.