ABUSE.MOM
THREAT REPORT

IP Threat Report
107.150.3.172

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-07-30 03:33:59
First seen: 2026-06-26 08:41:07
Last seen: 2026-06-27 23:29:02
95

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 95/100. Total malicious requests observed: 240.

01

Geolocation & Classification

IP Address
107.150.3.172
Type
Hosting
Country
🇺🇸 United States
City
Chicago
ISP
HostPapa
Organization
David Wu
Autonomous System
AS36352 HostPapa
Hit Count
240
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

2026-06-26 08:41:07
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
Directory Scan
2026-06-27 23:29:02
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 107.150.3.172 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

⚙️ Defensive Recommendations

Block 107.150.3.172 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.

09

Blacklist Status (DNSBL)

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

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

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

10

Threat Analysis

107.150.3.172 has been assigned a threat score of 95/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.

📊 Threat Analysis

IP address 107.150.3.172 has been traced to Chicago, United States, operating on the network of HostPapa. Our threat detection systems have flagged this address based on observed malicious behavior patterns. Over a period of 1 days, this IP generated 240 malicious requests, averaging approximately 240 requests per day. The IP is classified as hosting/datacenter infrastructure, commonly associated with rented servers used for automated attack campaigns, botnet command-and-control, or vulnerability scanning at scale. Our records show 143 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. At 95/100, this is an extremely high-risk address. All traffic should be considered hostile.

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

💡 Privacy-Preserving Threat Detection

Advanced techniques enable threat detection while minimizing privacy impact. Encrypted DNS, differential privacy in analytics, and federated learning for threat models allow effective security monitoring without unnecessary surveillance of legitimate user behavior.

💡 Server-Side Request Forgery (SSRF)

SSRF attacks trick servers into making requests to internal resources that should not be publicly accessible. This can expose cloud metadata endpoints, internal APIs, and private network services, potentially leading to full infrastructure compromise.

🔍 Check Any IP Address

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