
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: spider | Known bot/crawler User-Agent detected | +40 | |
| Burst: 5 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Foreign referer seen | Referer from unrelated external domain | +10 |
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 111.225.148.22: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 111.225.148.22.
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.
111.225.148.22 has been assigned a threat score of 85/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
The following attack categories were identified:
Our monitoring infrastructure has identified 111.225.148.22, geolocated to Shijiazhuang, China, operating on the network of Chinanet, as a source of suspicious network activity. Our sensors captured 7 malicious requests from this address across a 80-day span, reflecting a sustained attack cadence of ~0.1 requests per 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. Our records show 240 malicious IPs originating from China, positioning it as a significant contributor to global threat activity. The score of 85/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.
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.
Attacks targeting software supply chains compromise trusted update mechanisms to distribute malware at scale. Dependency confusion, typosquatting in package registries, and compromised build pipelines threaten even organizations with strong direct security postures.