ABUSE.MOM
THREAT REPORT

IP Threat Report
98.159.226.87

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-05-27 11:38:56
First seen: 2026-03-03 13:00:05
Last seen: 2026-03-09 12:00:05
73

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 73/100. Total malicious requests observed: 2.

BOT_UAUA_CHANGEDMETHOD
01

Geolocation & Classification

IP Address
98.159.226.87
Type
Hosting
Country
🇺🇿 UZ
City
Tashkent
ISP
UK-2 Limited
Organization
LogicWeb Inc
Autonomous System
AS13213 THG HOSTING LIMITED
Hit Count
2
02

Detection Signatures

SignatureDescriptionPointsSeverity
UA bot: pythonKnown bot/crawler User-Agent detected+40
UA changed for same IPMultiple User-Agents — bot rotation technique+25
POST requests presentBehavioral anomaly detected by automated analysis+8
Σ = 73
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

2026-03-03 13:00:05
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
UA bot: python (+40), UA changed for same IP (+25), POST requests present (+8)
2026-03-09 12:00:05
Last malicious request observed
Total score reached: 73/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

UK-2 Limited
AS13213 · 🇺🇿 UZ
06

Recommendations

Actions taken & recommended

  • IP 98.159.226.87 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 98.159.226.0/24
  • Report abuse to the network provider via their abuse contact
  • Ensure sensitive files (.env, .git, backups) are not accessible from the web

🤖 Bot Detection

Address UA spoofing from 98.159.226.87: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.

07

Neighbors in 98.159.226.0/24

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.

⛔ LISTED
Spamhaus ZEN

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

10

Threat Analysis

98.159.226.87 has been assigned a threat score of 73/100 (High). The IP is rated as a high-level threat. Network administrators should implement blocking rules and monitor for any connections from this address.

The following attack categories were identified:

User-Agent Anomaly

📊 Threat Analysis

IP address 98.159.226.87 has been traced to Tashkent, UZ, operating on the network of UK-2 Limited. Our threat detection systems have flagged this address based on observed malicious behavior patterns. Over a period of 5 days, this IP generated 2 malicious requests, averaging approximately 0.4 requests per day. Classified as a hosting IP, this address likely runs on a rented server or cloud instance. Attackers prefer datacenter IPs for their high bandwidth and disposable nature. The IP exhibits User-Agent manipulation, switching between different browser identities or sending empty headers. A threat score of 73/100 places this IP in the high-risk category. Blocking at the firewall level is recommended.

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 UZ

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🏢 Same network: AS13213

45.39.50.156 (165)45.38.107.9 (140)194.62.107.198 (75)95.135.253.40 (70)98.159.226.199 (70)View all →
12

Security Intelligence

💡 User-Agent Analysis Techniques

Analyzing User-Agent strings reveals automated tools masquerading as legitimate browsers. Inconsistencies between claimed browser capabilities and actual behavior, impossible version combinations, and known scanner signatures help identify malicious clients.

💡 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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