
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.
Address UA spoofing from 45.130.203.192: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
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.
45.130.203.192 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.
The following attack categories were identified:
Threat intelligence analysis has linked 45.130.203.192 to malicious activity originating from Aïn Taya, DZ, operating on the network of GSL Networks Pty LTD. The address has been under observation since its initial detection. During its 9-day observation window, we recorded 3 hostile requests from this IP — roughly 0.3 per day on average. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. The IP exhibits User-Agent manipulation, switching between different browser identities or sending empty headers. 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.
Examining HTTP headers beyond User-Agent reveals attack tools and automated scripts. Missing standard headers, unusual ordering, non-standard values, and inconsistencies with claimed client identity all serve as reliable detection signals.
Honeypots are decoy systems designed to attract and study attackers. Networks of honeypots provide early warning of new attack campaigns, reveal attacker tools and techniques, and generate high-confidence threat intelligence with minimal false positives.