ABUSE.MOM
THREAT REPORT

IP Threat Report
178.20.31.75

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-05-30 11:10:31
First seen: 2026-02-19 10:41:42
Last seen: 2026-02-19 10:41:42
70

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 70/100. Total malicious requests observed: 1.

FORM_SPAM
01

Geolocation & Classification

IP Address
178.20.31.75
Type
Hosting
Country
🇳🇱 Netherlands
City
Amsterdam
ISP
Alex Largman
Organization
Fine Group Servers Solutions LLC
Autonomous System
AS59651 AS QualityNetwork
Hit Count
1
02

Detection Signatures

SignatureDescriptionPointsSeverity
Form spam: no_js_checkSpam/malware keywords in request content+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

2026-02-19 10:41:42
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
Form spam: no_js_check
2026-02-19 10:41:42
Last malicious request observed
Total score reached: 70/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

Alex Largman
AS59651 · 🇳🇱 Netherlands
06

Recommendations

Actions taken & recommended

  • IP 178.20.31.75 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 178.20.31.0/24
  • Report abuse to the network provider via their abuse contact
  • Ensure sensitive files (.env, .git, backups) are not accessible from the web

📧 Content Abuse Prevention

IP 178.20.31.75 is flooding forms with spam. Implement time-based tokens and block IPs submitting more than 5 forms per hour.

07

Neighbors in 178.20.31.0/24

Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.

09

Blacklist Status (DNSBL)

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

✓ Clean
Spamhaus ZEN

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

10

Threat Analysis

178.20.31.75 has been assigned a threat score of 70/100 (High). This classifies it as a high-severity threat. Proactive blocking is recommended for sensitive infrastructure.

📊 Threat Analysis

IP address 178.20.31.75 has been traced to Amsterdam, Netherlands, operating on the network of Alex Largman. Our threat detection systems have flagged this address based on observed malicious behavior patterns. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. Operating from datacenter infrastructure, this IP is typical of addresses used in organized attack operations. Cloud and VPS providers are commonly exploited as launching platforms for automated scanning. Netherlands currently accounts for 35 blocked IPs in our database, making it a notable source of malicious traffic. The score of 70/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.

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 Netherlands

5.181.169.192 (313)88.218.45.194 (268)178.20.28.30 (268)130.49.10.116 (245)185.101.21.119 (245)View all →

🏢 Same network: AS59651

5.181.169.192 (313)170.168.175.156 (313)170.168.96.250 (313)170.168.175.34 (313)122.8.95.61 (268)View all →
12

Security Intelligence

💡 SQL Injection Campaigns

SQL injection remains one of the most common web attack vectors. Attackers inject malicious SQL code through input fields to extract database contents, modify data, or gain administrative access. Automated scanners test for SQLi vulnerabilities at massive scale.

💡 Web Application Firewall Strategies

WAFs inspect HTTP traffic to block common attacks but require careful tuning. Overly aggressive rules cause false positives while permissive configurations miss attacks. Modern WAFs combine signature matching with behavioral analysis and machine learning.

🔍 Check Any IP Address

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