IP Threat Report
151.240.45.78
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Directory Scan | Behavioral anomaly detected by automated analysis | +0 |
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
Recommendations
Actions taken & recommended
- IP 151.240.45.78 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 151.240.45.0/24
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
⚙️ General Security
Add 151.240.45.78 to your firewall blocklist. Review logs for successful connections. Enable comprehensive logging on all public-facing services.
Neighbors in 151.240.45.0/24
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
151.240.45.78 has been assigned a threat score of 90/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.
📊 Threat Analysis
Our monitoring infrastructure has identified 151.240.45.78, geolocated to Boston, United States, operating on the network of Datacamp Limited, as a source of suspicious network activity. Over a period of 120 days, this IP generated 376 malicious requests, averaging approximately 3.1 requests per day. United States currently accounts for 151 blocked IPs in our database, making it a significant source of malicious traffic. A score of 90/100 places this address in the top tier of severity. Block and investigate any historical connections.
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💡 DNS Sinkholing for Malware Defense
DNS sinkholing redirects queries for known malicious domains to controlled IP addresses. This technique blocks malware communication, prevents data exfiltration, and identifies compromised internal hosts attempting to contact command-and-control servers.
💡 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.