
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 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Block scanning from 216.73.163.95: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
IP 216.73.163.95 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
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.
216.73.163.95 has been assigned a threat score of 100/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
The following attack categories were identified:
Threat intelligence analysis has linked 216.73.163.95 to malicious activity originating from an unknown location. The address has been under observation since its initial detection. The address has been active for 1 days in our monitoring system, producing 3 flagged requests at a rate of ~3/day. Two attack patterns were identified (Path Enumeration and User-Agent Anomaly), suggesting a semi-automated campaign that targets multiple vulnerabilities. A score of 100/100 places this address in the top tier of severity. Block and investigate any historical connections.
SSRF attacks trick servers into making requests to internal resources that should not be publicly accessible. This can expose cloud metadata endpoints, internal APIs, and private network services, potentially leading to full infrastructure compromise.
Insider threats — whether malicious or negligent — account for a significant percentage of data breaches. Behavioral analytics detecting unusual access patterns, data downloads, and privilege escalation help identify insider risks before damage occurs.