IP Threat Report
45.91.23.160
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Danger strong hits: 212 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 558 | Medium-risk: admin panels, config files | +60 | |
| Burst: 23 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 85 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 374 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 962 | Medium-risk: admin panels, config files | +60 | |
| Burst: 82 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 127 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 50 | Medium-risk: admin panels, config files | +60 | |
| Burst: 24 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 86 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 166 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 412 | Medium-risk: admin panels, config files | +60 |
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 45.91.23.160 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 45.91.23.0/24
- 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 45.91.23.160 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
🌊 Flood / DDoS Mitigation
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 45.91.23.160.
Neighbors in 45.91.23.0/24
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
45.91.23.160 has been assigned a threat score of 255/100 (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
Our monitoring infrastructure has identified 45.91.23.160, geolocated to Montreal, Canada, operating on the network of Datacamp Limited, as a source of suspicious network activity. During its 1-day observation window, we recorded 4 hostile requests from this IP — roughly 4 per day on average. 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. The dual attack vectors of User-Agent Anomaly combined with Request Flooding indicate a coordinated assault rather than opportunistic scanning. Canada currently accounts for 53 blocked IPs in our database, making it a notable source of malicious traffic. A score of 255/100 places this address in the top tier of severity. Block and investigate any historical connections.
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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💡 TLS Fingerprinting (JA3/JA4)
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.
💡 Emerging Threats from AI-Powered Attacks
Artificial intelligence enables more convincing phishing content, faster vulnerability discovery, and adaptive attack strategies that learn from defensive responses. AI-generated social engineering and automated exploit development represent growing threats.