
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 | |
| Foreign referer | Referer from unrelated external domain | +10 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
We have detected 5 malicious IPs from this autonomous system.
IP 41.13.2.87 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
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.
41.13.2.87 has been assigned a threat score of 60/100 (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:
Network traffic from 41.13.2.87, located in Johannesburg, South Africa, operating on the network of Vodacom Midrand PT Southern Gauteng Public NAT, has been classified as malicious by our automated threat scoring engine. During its 1-day observation window, we recorded 5 hostile requests from this IP — roughly 5 per day on average. The address belongs to a mobile carrier network. The sustained pattern of malicious requests indicates either a compromised device or deliberate abuse. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. Our records show 260 malicious IPs originating from South Africa, positioning it as a significant contributor to global threat activity. The score of 60/100 warrants active monitoring and rate-limiting. Full blocking is advisable for sensitive systems.
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.
Effective rate limiting must balance protection against abuse with allowing legitimate traffic bursts. Sliding window algorithms, token buckets, and adaptive thresholds based on client reputation provide layered defense against flooding attacks.