
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: python | Known bot/crawler User-Agent detected | +40 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 45.130.203.219 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
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.
45.130.203.219 has been assigned a threat score of 65/100 (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 45.130.203.219, located in Aïn Taya, DZ, operating on the network of GSL Networks Pty LTD, has been classified as malicious by our automated threat scoring engine. Over a period of 20 days, this IP generated 4 malicious requests, averaging approximately 0.2 requests per day. The address is classified as residential, meaning it likely belongs to an end-user ISP connection. Malicious activity from residential IPs typically indicates device compromise or botnet membership. Detected suspicious User-Agent anomalies including empty, forged, or rapidly rotating UA strings — characteristic of automated scanning tools. Our records show 151 malicious IPs originating from DZ, positioning it as a significant contributor to global threat activity. At 65/100, this IP presents a meaningful threat. Implement rate limiting with escalation to blocking.
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.
TLS fingerprinting creates unique identifiers based on how clients negotiate encrypted connections. The JA3 and JA4 methods generate hashes from TLS ClientHello parameters, enabling identification of specific tools and malware regardless of IP address changes.
VPN exit nodes aggregate traffic from many users, creating mixed reputation profiles. While legitimate users seek privacy, attackers exploit VPN services to anonymize malicious activity, making IP-based blocking of VPN nodes a complex policy decision.