ABUSE.MOM
THREAT REPORT

IP Threat Report
172.6.86.47

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-05-27 20:50:09
First seen: 2026-04-08 07:00:06
Last seen: 2026-04-08 07:00:06
65

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 65/100. Total malicious requests observed: 1.

BOT_UAUA_CHANGED
01

Geolocation & Classification

IP Address
172.6.86.47
Type
Residential
Country
🇺🇸 United States
City
San Jose
ISP
AT&T Enterprises, LLC
Organization
AT&T Enterprises, LLC
Autonomous System
AS7018 AT&T Enterprises, LLC
Hit Count
1
02

Detection Signatures

SignatureDescriptionPointsSeverity
UA bot: pythonKnown bot/crawler User-Agent detected+40
UA changed for same IPMultiple User-Agents — bot rotation technique+25
Σ = 65
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

2026-04-08 07:00:06
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)
2026-04-08 07:00:06
Last malicious request observed
Total score reached: 65/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

AT&T Enterprises, LLC
AS7018 · 🇺🇸 United States
06

Recommendations

Actions taken & recommended

  • IP 172.6.86.47 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

🤖 User-Agent Anomaly Defense

IP 172.6.86.47 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.

09

Blacklist Status (DNSBL)

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

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

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

10

Threat Analysis

172.6.86.47 has been assigned a threat score of 65/100 (High). At this threat level, the IP is considered high risk. Firewall rules should be updated to deny traffic from this source.

The following attack categories were identified:

User-Agent Anomaly

📊 Threat Analysis

172.6.86.47 is registered in San Jose, United States, operating on the network of AT&T Enterprises, LLC. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. 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. Detected suspicious User-Agent anomalies including empty, forged, or rapidly rotating UA strings — characteristic of automated scanning tools. United States currently accounts for 164 blocked IPs in our database, making it a significant source of malicious traffic. At 65/100, this IP presents a meaningful threat. Implement rate limiting with escalation to blocking.

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: AS7018

107.193.87.25 (170)107.127.21.1 (155)69.154.140.39 (140)172.126.122.197 (135)108.227.1.19 (135)View all →
12

Security Intelligence

💡 HTTP Header Analysis for Threat Detection

Examining HTTP headers beyond User-Agent reveals attack tools and automated scripts. Missing standard headers, unusual ordering, non-standard values, and inconsistencies with claimed client identity all serve as reliable detection signals.

💡 Supply Chain Security Challenges

Attacks targeting software supply chains compromise trusted update mechanisms to distribute malware at scale. Dependency confusion, typosquatting in package registries, and compromised build pipelines threaten even organizations with strong direct security postures.

🔍 Check Any IP Address

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