
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: spider | Known bot/crawler User-Agent detected | +40 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 |
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 112.86.225.193: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
IP 112.86.225.193 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
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.
112.86.225.193 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:
Network traffic from 112.86.225.193, located in Suzhou, China, operating on the network of China Unicom CHINA169 Jiangsu Province Network, has been classified as malicious by our automated threat scoring engine. Over a period of 47 days, this IP generated 3 malicious requests, averaging approximately 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 Path Enumeration indicate a coordinated assault rather than opportunistic scanning. With 241 flagged addresses, China represents a significant presence in our threat database. The score of 75/100 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.
False positives erode trust in security systems and waste analyst resources. Effective management requires feedback loops, allowlisting mechanisms, contextual analysis, and regular tuning of detection rules based on operational experience.