
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| UA changed | Multiple User-Agents — bot rotation technique | +25 | |
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 173.239.213.65 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
Address UA spoofing from 173.239.213.65: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
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.
173.239.213.65 has been assigned a threat score of 100/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.
The following attack categories were identified:
IP address 173.239.213.65 has been traced to Atlanta, United States, operating on the network of Clouvider Limited. Our threat detection systems have flagged this address based on observed malicious behavior patterns. During its 40-day observation window, we recorded 278 hostile requests from this IP — roughly 7 per day on average. 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 Path Enumeration combined with User-Agent Anomaly indicate a coordinated assault rather than opportunistic scanning. United States currently accounts for 214 blocked IPs in our database, making it a significant source of malicious traffic. At 100/100, 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.
SQL injection remains one of the most common web attack vectors. Attackers inject malicious SQL code through input fields to extract database contents, modify data, or gain administrative access. Automated scanners test for SQLi vulnerabilities at massive scale.
Machine learning models analyze vast amounts of network traffic to identify attack patterns invisible to rule-based systems. Supervised models classify known attack types while unsupervised models detect anomalies that may indicate novel threats.