
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Directory Scan | Behavioral anomaly detected by automated analysis | +0 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Add 62.60.130.223 to your firewall blocklist. Review logs for successful connections. Enable comprehensive logging on all public-facing services.
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.
62.60.130.223 has been assigned a threat score of 65/100 (High). The IP is rated as a high-level threat. Network administrators should implement blocking rules and monitor for any connections from this address.
Network traffic from 62.60.130.223, located in Tehran, Iran, operating on the network of Cipher Operations DOO Beograd - Novi Beograd, has been classified as malicious by our automated threat scoring engine. Over a period of 12 days, this IP generated 1,128 malicious requests, averaging approximately 94 requests per day. Our records show 48 malicious IPs originating from Iran, positioning it as a notable contributor to global threat activity. At 65/100, this IP presents a meaningful threat. Implement rate limiting with escalation to blocking.
The vast IPv6 address space makes traditional sequential scanning impractical. However, attackers use DNS records, certificate transparency logs, and predictable address patterns to identify active IPv6 hosts, adapting their techniques to the expanded address space.
WAFs inspect HTTP traffic to block common attacks but require careful tuning. Overly aggressive rules cause false positives while permissive configurations miss attacks. Modern WAFs combine signature matching with behavioral analysis and machine learning.