ABUSE.MOM
THREAT REPORT

IP Threat Report
213.204.92.54

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-05-27 06:55:08
First seen: 2026-03-08 05:00:05
Last seen: 2026-03-08 05:00:05
103

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 103/100. Total malicious requests observed: 2.

DANGER_PATHMETHOD
01

Geolocation & Classification

IP Address
213.204.92.54
Type
Residential
Country
🇱🇧 LB
City
Aanjar
ISP
TerraNet sal
Organization
Unknown
Autonomous System
AS39010 TerraNet sal
Hit Count
2
02

Detection Signatures

SignatureDescriptionPointsSeverity
Danger strong hits: 3High-risk paths: shells, RCE vectors, exploits+75
Danger medium hits: 2Medium-risk: admin panels, config files+20
POST requests presentBehavioral anomaly detected by automated analysis+8
Σ = 103
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

2026-03-08 05:00:05
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
Danger strong hits: 3 (+75), Danger medium hits: 2 (+20), POST requests present (+8)
2026-03-08 05:00:05
Last malicious request observed
Total score reached: 103/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

TerraNet sal
AS39010 · 🇱🇧 LB
06

Recommendations

Actions taken & recommended

  • IP 213.204.92.54 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 213.204.92.0/24
  • 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 213.204.92.54 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.

07

Neighbors in 213.204.92.0/24

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

213.204.92.54 has been assigned a threat score of 103/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.

📊 Threat Analysis

Our monitoring infrastructure has identified 213.204.92.54, geolocated to Aanjar, LB, operating on the network of TerraNet sal, as a source of suspicious network activity. Our sensors captured 2 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~2 requests per day. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. Our records show 30 malicious IPs originating from LB, positioning it as a notable contributor to global threat activity. A score of 103/100 places this address in the top tier of severity. Block and investigate any historical connections.

This IP is classified as residential, suggesting it may belong to a compromised home device, IoT botnet member, or an infected personal computer. Residential IPs involved in attacks often indicate malware infection without the owner's knowledge.

11

Related Threats

🇱🇧 Top threats from LB

213.204.92.222 (103)213.204.87.92 (103)77.235.149.20 (103)89.108.171.58 (103)94.187.17.18 (103)View all →

🏢 Same network: AS39010

213.204.92.222 (103)213.204.87.92 (103)View all →
12

Security Intelligence

💡 Prototype Pollution Attacks

Prototype pollution manipulates JavaScript object prototypes to inject properties that affect all objects in an application. This can lead to denial of service, property injection, and in some cases remote code execution in Node.js applications.

💡 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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