ABUSE.MOM
THREAT REPORT

IP Threat Report
67.215.225.137

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-07-30 01:15:37
First seen: 2026-06-23 16:48:50
Last seen: 2026-06-27 20:13:38
95

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 95/100. Total malicious requests observed: 592.

01

Geolocation & Classification

IP Address
67.215.225.137
Type
Hosting
Country
🇺🇸 United States
City
Los Angeles
ISP
HostPapa
Organization
HostPapa
Autonomous System
AS36352 HostPapa
Hit Count
592
02

Detection Signatures

SignatureDescriptionPointsSeverity
Directory ScanBehavioral anomaly detected by automated analysis+0
Σ = 0
03

Observed Activity

Reconstructed HTTP requests from server access logs. Target domains redacted for security.

[redacted]
GET
/
200
Requests shown: 1 · HTTP 404: 0 · Dangerous patterns: 0

* Typical request patterns for detected signatures. Actual target domains are redacted.

04

Timeline

2026-06-23 16:48:50
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
Directory Scan
2026-06-27 20:13:38
Last malicious request observed
Total score reached: 95/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

HostPapa
AS36352 · 🇺🇸 United States
06

Recommendations

Actions taken & recommended

  • IP 67.215.225.137 is blocked at application level (HTTP 403)
  • Consider blocking at firewall level (iptables/CSF) to reduce server load
  • Report abuse to the network provider via their abuse contact
  • Ensure sensitive files (.env, .git, backups) are not accessible from the web

⚙️ General Security

Add 67.215.225.137 to your firewall blocklist. Review logs for successful connections. Enable comprehensive logging on all public-facing services.

09

Blacklist Status (DNSBL)

This IP was checked against major DNS-based blacklists used by mail servers and firewalls worldwide.

✓ Clean
spam.dnsbl.sorbs.net
✓ Clean
bl.spamcop.net
✓ Clean
zen.spamhaus.org
✓ Clean
cbl.abuseat.org
✓ Clean
b.barracudacentral.org
✓ Clean
psbl.surriel.com
✓ Clean
dnsbl.dronebl.org
✓ Clean
bl.blocklist.de

Checked: Spamhaus, SpamCop, Barracuda, SORBS, CBL, UCEProtect. Results may change over time.

10

Threat Analysis

67.215.225.137 has been assigned a threat score of 95/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.

📊 Threat Analysis

The address 67.215.225.137 originates from Los Angeles, United States, operating on the network of HostPapa. It was identified through automated analysis of incoming network traffic across monitored endpoints. Over a period of 4 days, this IP generated 592 malicious requests, averaging approximately 148 requests per day. This address belongs to a datacenter or cloud hosting provider. Hosting IPs are frequently leveraged by threat actors who rent cheap VPS instances specifically for conducting attacks. Our records show 145 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. A score of 95/100 places this address in the top tier of severity. Block and investigate any historical connections.

This IP belongs to a hosting or data center provider. Malicious traffic from hosting infrastructure often originates from compromised VPS instances, rented servers used for scanning campaigns, or abused free-tier cloud accounts. Hosting providers typically respond to abuse reports within 24-72 hours.

11

Related Threats

🇺🇸 Top threats from United States

104.28.246.115 (350)104.28.214.122 (350)103.168.66.237 (340)34.187.158.4 (340)34.186.187.208 (340)View all →

🏢 Same network: AS36352

107.175.213.192 (220)104.168.56.78 (205)192.3.177.44 (130)192.161.170.98 (130)107.172.170.111 (130)View all →
12

Security Intelligence

💡 Automated Incident Response

Automated response systems can block threats in milliseconds, far faster than human analysts. However, automation requires careful safeguards — rate limits on blocking actions, automatic expiration, and human review queues prevent automated systems from causing self-inflicted outages.

💡 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.

🔍 Check Any IP Address

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