
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| POST requests present | Behavioral anomaly detected by automated analysis | +8 |
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 138.255.179.115: 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.
138.255.179.115 has been assigned a threat score of 83/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
The following attack categories were identified:
Our monitoring infrastructure has identified 138.255.179.115, geolocated to Porto Alegre, Brazil, operating on the network of Cybernetrs Ltda - ME, as a source of suspicious network activity. The address has been active for 1 days in our monitoring system, producing 1 flagged requests at a rate of ~1/day. Operating from a residential network, this IP may represent a compromised home gateway or IoT device that has been drafted into a larger attack infrastructure. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. With 103 flagged addresses, Brazil represents a significant presence in our threat database. The score of 83/100 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.
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 User-Agent strings reveals automated tools masquerading as legitimate browsers. Inconsistencies between claimed browser capabilities and actual behavior, impossible version combinations, and known scanner signatures help identify malicious clients.