ABUSE.MOM
THREAT REPORT

IP Threat Report
125.162.218.197

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-05-30 13:27:12
First seen: 2026-03-25 08:00:05
Last seen: 2026-03-25 08:00:05
103

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 103/100. Total malicious requests observed: 1.

DANGER_PATHMETHOD
01

Geolocation & Classification

IP Address
125.162.218.197
Type
Residential
Country
🇮🇩 Indonesia
City
Makassar
ISP
PT. TELKOM INDONESIA
Organization
Unknown
Autonomous System
AS7713 PT Telekomunikasi Indonesia
Hit Count
1
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

2026-03-25 08:00:05
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)
2026-03-25 08:00:05
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

PT. TELKOM INDONESIA
AS7713 · 🇮🇩 Indonesia
06

Recommendations

Actions taken & recommended

  • IP 125.162.218.197 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 125.162.218.197 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
ix.dnsbl.manitu.net
✓ Clean
dnsbl.sorbs.net
✓ Clean
bl.spamcop.net
✓ Clean
zen.spamhaus.org
✓ Clean
dnsbl-1.uceprotect.net
✓ Clean
b.barracudacentral.org
✓ Clean
truncate.gbudb.net
✓ Clean
psbl.surriel.com

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

10

Threat Analysis

125.162.218.197 has been assigned a threat score of 103/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.

📊 Threat Analysis

125.162.218.197 is registered in Makassar, Indonesia, operating on the network of PT. TELKOM INDONESIA. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. Over a period of 1 days, this IP generated 1 malicious requests, averaging approximately 1 requests per day. The address is classified as residential, meaning it likely belongs to an end-user ISP connection. Malicious activity from residential IPs typically indicates device compromise or botnet membership. With 176 flagged addresses, Indonesia represents a significant presence in our threat database. With a threat score of 103/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.

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

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🏢 Same network: AS7713

36.83.117.53 (295)36.77.27.11 (295)36.81.233.32 (295)36.83.122.201 (295)36.83.116.109 (295)View all →
12

Security Intelligence

💡 Cross-Site Scripting (XSS) Attacks

XSS attacks inject malicious scripts into web pages viewed by other users. Reflected XSS uses crafted URLs, while stored XSS persists in databases. Both types can steal session cookies, redirect users, or deface websites.

💡 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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