
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Danger medium hits: 5 | Medium-risk: admin panels, config files | +50 | |
| Directory Scan | Behavioral anomaly detected by automated analysis | +0 | |
| Foreign referer | Referer from unrelated external domain | +10 | |
| Probe 302→404 | 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.
Block scanning from 130.44.202.0: 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.
130.44.202.0 has been assigned a threat score of 95/100 (Critical). This represents a critical risk level. Our detection systems have flagged multiple high-confidence indicators of malicious intent from this address.
The following attack categories were identified:
Network traffic from 130.44.202.0, located in New Hampton, United States, operating on the network of Blazing SEO, has been classified as malicious by our automated threat scoring engine. The address has been active for 43 days in our monitoring system, producing 428 flagged requests at a rate of ~10/day. The IP exhibits directory enumeration behavior, systematically requesting non-existent paths to discover hidden files and misconfigured resources. With 109 flagged addresses, United States represents a significant presence in our threat database. A score of 95/100 places this address in the top tier of severity. Block and investigate any historical connections.
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.
Analyzing network flows (NetFlow, sFlow, IPFIX) provides visibility into traffic patterns without inspecting packet contents. Flow data reveals scanning activity, data exfiltration, lateral movement, and command-and-control channels at scale.