ABUSE.MOM
THREAT REPORT

IP Threat Report
172.59.42.159

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-07-28 14:52:05
First seen: 2026-07-13 22:37:57
Last seen: 2026-07-19 04:08:16
80

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 80/100. Total malicious requests observed: 364.

BURSTREFERER
01

Geolocation & Classification

IP Address
172.59.42.159
Type
Mobile
Country
🇺🇸 United States
City
El Paso
ISP
T-Mobile USA, Inc.
Organization
T-Mobile USA, Inc.
Autonomous System
AS21928 T-Mobile USA, Inc.
Hit Count
364
02

Detection Signatures

SignatureDescriptionPointsSeverity
Burst 32/2sAbnormally fast request rate — automated scanning+35
Burst 33/10sAbnormally fast request rate — automated scanning+35
Foreign refererReferer from unrelated external domain+10
Σ = 80
03

Observed Activity

Reconstructed HTTP requests from server access logs. Target domains redacted for security.

[redacted]
GET
/
200
[redacted]
GET
/page
200
Requests shown: 2 · HTTP 404: 0 · Dangerous patterns: 0

* Typical request patterns for detected signatures. Actual target domains are redacted.

04

Timeline

2026-07-13 22:37:57
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
Burst 32/2s (+35), Burst 33/10s (+35), Foreign referer (+10)
2026-07-19 04:08:16
Last malicious request observed
Total score reached: 80/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

T-Mobile USA, Inc.
AS21928 · 🇺🇸 United States
06

Recommendations

Actions taken & recommended

  • IP 172.59.42.159 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

🌊 Flood / DDoS Mitigation

Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 172.59.42.159.

09

Blacklist Status (DNSBL)

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

✓ Clean
dnsbl.dronebl.org
✓ Clean
cbl.abuseat.org

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

10

Threat Analysis

172.59.42.159 has been assigned a threat score of 80/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.

The following attack categories were identified:

Request Flooding

📊 Threat Analysis

IP address 172.59.42.159 has been traced to El Paso, United States, operating on the network of T-Mobile USA, Inc.. Our threat detection systems have flagged this address based on observed malicious behavior patterns. Over a period of 5 days, this IP generated 364 malicious requests, averaging approximately 72.8 requests per day. This is a mobile network IP. While mobile addresses are typically shared via CGNAT, persistent malicious activity from this specific address suggests automated abuse. Rate-based attacks from this IP aim to overwhelm server resources through high-volume request flooding. United States currently accounts for 107 blocked IPs in our database, making it a significant source of malicious traffic. The score of 80/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.

11

Related Threats

🇺🇸 Top threats from United States

104.28.246.115 (350)104.28.214.122 (350)103.215.74.213 (340)103.168.66.237 (340)34.187.158.4 (340)View all →

🏢 Same network: AS21928

172.56.157.62 (95)172.56.152.136 (80)172.56.155.83 (80)172.56.8.223 (60)172.59.27.6 (60)View all →
12

Security Intelligence

💡 DDoS Mitigation Approaches

Distributed denial of service attacks overwhelm infrastructure with traffic volume. Effective mitigation combines always-on traffic scrubbing, anycast network distribution, rate limiting, and the ability to quickly scale absorption capacity during attacks.

💡 Behavioral Analysis vs Signature Detection

Signature-based detection matches known attack patterns but misses novel threats. Behavioral analysis identifies anomalies in request patterns, timing, and volume, catching zero-day attacks that signatures cannot recognize.

🔍 Check Any IP Address

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