
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 |
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 172.98.32.118: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
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.
172.98.32.118 has been assigned a threat score of 75/100 (High). At this threat level, the IP is considered high risk. Firewall rules should be updated to deny traffic from this source.
The following attack categories were identified:
172.98.32.118 is registered in an unknown location. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. Our sensors captured 2 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~2 requests per day. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. The score of 75/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.
RCE vulnerabilities allow attackers to execute arbitrary code on target servers. These critical flaws often arise from deserialization bugs, template injection, or file upload vulnerabilities, and represent the highest severity class of web application weaknesses.
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.