ABUSE.MOM
THREAT REPORT

IP Threat Report
132.196.65.22

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-05-26 21:02:38
First seen: 2026-05-23 17:40:11
Last seen: 2026-05-24 10:21:08
280

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 280/100. Total malicious requests observed: 135.

BURSTDANGER_PATHRATIO_404REDIRECT_PROBEUA_SUS
01

Geolocation & Classification

IP Address
132.196.65.22
Type
Hosting
Country
🇺🇸 United States
City
Des Moines
ISP
Microsoft Corporation
Organization
Microsoft Azure Cloud (centralus)
Autonomous System
AS8075 Microsoft Corporation
Hit Count
135
02

Detection Signatures

SignatureDescriptionPointsSeverity
404 ratio 40-60%Majority of requests returned 404 — enumeration+15
Burst 18/2sAbnormally fast request rate — automated scanning+35
Burst 19/2sAbnormally fast request rate — automated scanning+35
Burst 20/2sAbnormally fast request rate — automated scanning+35
Burst 36/10sAbnormally fast request rate — automated scanning+35
Burst 61/10sAbnormally fast request rate — automated scanning+35
Burst 69/10sAbnormally fast request rate — automated scanning+35
Burst 70/10sAbnormally fast request rate — automated scanning+35
Burst 71/10sAbnormally fast request rate — automated scanning+35
Danger medium hits: 198Medium-risk: admin panels, config files+60
Danger medium hits: 202Medium-risk: admin panels, config files+60
Danger medium hits: 24Medium-risk: admin panels, config files+60
Danger medium hits: 303Medium-risk: admin panels, config files+60
Danger strong hits: 3High-risk paths: shells, RCE vectors, exploits+75
Danger strong hits: 4High-risk paths: shells, RCE vectors, exploits+100
Danger strong hits: 6High-risk paths: shells, RCE vectors, exploits+100
Danger strong hits: 8High-risk paths: shells, RCE vectors, exploits+100
Probe 302→404Behavioral anomaly detected by automated analysis+20
UA suspiciousBehavioral anomaly detected by automated analysis+15
Σ = 945
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

2026-05-23 17:40:11
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
404 ratio 40-60% (+15), Burst 18/2s (+35), Burst 19/2s (+35)
2026-05-24 10:21:08
Last malicious request observed
Total score reached: 280/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

Microsoft Corporation
AS8075 · 🇺🇸 United States
06

Recommendations

Actions taken & recommended

  • IP 132.196.65.22 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

🔎 Directory Scan Defense

IP 132.196.65.22 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.

🌊 Traffic Flood Defense

IP 132.196.65.22 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.

🤖 Bot Detection

Address UA spoofing from 132.196.65.22: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.

09

Blacklist Status (DNSBL)

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

✓ Clean
b.barracudacentral.org
✓ Clean
psbl.surriel.com
✓ Clean
spam.dnsbl.sorbs.net
✓ Clean
cbl.abuseat.org
✓ Clean
zen.spamhaus.org
✓ Clean
dnsbl.dronebl.org
✓ Clean
bl.spamcop.net
✓ Clean
bl.blocklist.de

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

10

Threat Analysis

132.196.65.22 has been assigned a threat score of 280/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.

The following attack categories were identified:

Path EnumerationRequest FloodingUser-Agent Anomaly

📊 Threat Analysis

132.196.65.22 is registered in Des Moines, United States, operating on the network of Microsoft Corporation. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. During its 1-day observation window, we recorded 135 hostile requests from this IP — roughly 135 per day on average. 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 diversity of 3 separate attack methods suggests a comprehensive attack toolkit — likely an automated scanner that tests for vulnerabilities across multiple categories. With 101 flagged addresses, United States represents a significant presence in our threat database. With a threat score of 280/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly 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

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🏢 Same network: AS8075

74.241.249.229 (340)20.151.111.128 (308)4.182.24.88 (285)20.65.61.3 (283)4.205.39.97 (283)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.

💡 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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