
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 | |
| UA bot: python | Known bot/crawler User-Agent detected | +40 |
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 45.130.203.176: 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.
45.130.203.176 has been assigned a threat score of 65/100 (High). This classifies it as a high-severity threat. Proactive blocking is recommended for sensitive infrastructure.
The following attack categories were identified:
45.130.203.176 is registered in Aïn Taya, DZ, operating on the network of GSL Networks Pty LTD. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. During its 64-day observation window, we recorded 285 hostile requests from this IP — roughly 4.5 per day on average. 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. 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. The score of 65/100 warrants active monitoring and rate-limiting. Full blocking is advisable for sensitive systems.
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.
Brute force attacks systematically try username and password combinations to gain unauthorized access. Modern attacks leverage credential databases from previous breaches, testing millions of combinations using distributed botnets across multiple IP addresses.
False positives erode trust in security systems and waste analyst resources. Effective management requires feedback loops, allowlisting mechanisms, contextual analysis, and regular tuning of detection rules based on operational experience.