IP Threat Report
45.133.5.165
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 |
Observed Activity
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Timeline
Network Provider
Recommendations
Actions taken & recommended
- IP 45.133.5.165 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Other malicious IPs detected in the same /24 subnet — consider blocking 45.133.5.0/24
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🤖 User-Agent Anomaly Defense
IP 45.133.5.165 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
🔎 Path Enumeration Protection
Block scanning from 45.133.5.165: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
Neighbors in 45.133.5.0/24
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
Blacklist Status (DNSBL)
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.
Threat Analysis
45.133.5.165 has been assigned a threat score of 90/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.
The following attack categories were identified:
📊 Threat Analysis
The address 45.133.5.165 originates from Sydney, Australia, operating on the network of GSL Networks Pty LTD. It was identified through automated analysis of incoming network traffic across monitored endpoints. Our sensors captured 1 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~1 requests per day. The address operates as a VPN/proxy exit node. Attackers route traffic through anonymizing services to obscure their real location and evade IP-based security controls. Two attack patterns were identified (User-Agent Anomaly and Path Enumeration), suggesting a semi-automated campaign that targets multiple vulnerabilities. With 109 flagged addresses, Australia represents a significant presence in our threat database. At 90/100, this is an extremely high-risk address. All traffic should be considered hostile.
This IP is associated with a VPN or proxy service. Attackers frequently route their traffic through anonymizing services to obscure their true location. This makes attribution more challenging but the malicious behavior patterns remain detectable.
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💡 User-Agent Analysis Techniques
Analyzing User-Agent strings reveals automated tools masquerading as legitimate browsers. Inconsistencies between claimed browser capabilities and actual behavior, impossible version combinations, and known scanner signatures help identify malicious clients.
💡 Machine Learning in Threat Detection
Machine learning models analyze vast amounts of network traffic to identify attack patterns invisible to rule-based systems. Supervised models classify known attack types while unsupervised models detect anomalies that may indicate novel threats.