ABUSE.MOM
THREAT REPORT

IP Threat Report
104.167.69.168

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-05-22 11:21:27
First seen: 2026-02-28 09:00:05
Last seen: 2026-02-28 09:00:05
85

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 85/100. Total malicious requests observed: 1.

DANGER_PATHRATIO_404REDIRECT_PROBE
01

Geolocation & Classification

IP Address
104.167.69.168
Type
Residential
Country
🇺🇸 United States
City
Los Angeles
ISP
eSited Solutions
Organization
eSited Solutions
Autonomous System
AS22552 eSited Solutions
Hit Count
1
02

Detection Signatures

SignatureDescriptionPointsSeverity
Danger strong hits: 2High-risk paths: shells, RCE vectors, exploits+50
404 ratio 40-60%Majority of requests returned 404 — enumeration+15
Probe pattern 302->404 same pathBehavioral anomaly detected by automated analysis+20
Σ = 85
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

2026-02-28 09:00:05
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
Danger strong hits: 2 (+50), 404 ratio 40-60% (+15), Probe pattern 302->404 same path (+20)
2026-02-28 09:00:05
Last malicious request observed
Total score reached: 85/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

eSited Solutions
AS22552 · 🇺🇸 United States
06

Recommendations

Actions taken & recommended

  • IP 104.167.69.168 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 104.167.69.168 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.

09

Blacklist Status (DNSBL)

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

✓ Clean
Spamhaus ZEN

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

10

Threat Analysis

104.167.69.168 has been assigned a threat score of 85/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.

The following attack categories were identified:

Path Enumeration

📊 Threat Analysis

Our monitoring infrastructure has identified 104.167.69.168, geolocated to Los Angeles, United States, operating on the network of eSited Solutions, as a source of suspicious network activity. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. The IP exhibits directory enumeration behavior, systematically requesting non-existent paths to discover hidden files and misconfigured resources. With 112 flagged addresses, United States represents a significant presence in our threat database. The score of 85/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.

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: AS22552

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12

Security Intelligence

💡 Vulnerability Scanning Explained

Vulnerability scanning is the automated process of probing web applications for known weaknesses. Attackers use tools like Nuclei, Nikto, and ZAP to test thousands of hosts per hour, looking for exposed configuration files, outdated software, and default credentials.

💡 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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