IP Threat Report
91.193.232.5
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Directory Scan | Behavioral anomaly detected by automated analysis | +0 | |
| Foreign referer | Referer from unrelated external domain | +10 | |
| UA bot: Go-http-client | Known bot/crawler User-Agent detected | +40 | |
| UA changed | Multiple User-Agents — bot rotation technique | +25 |
Observed Activity
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Timeline
Network Provider
We have detected 2930 malicious IPs from this autonomous system.
Recommendations
Actions taken & recommended
- IP 91.193.232.5 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Other malicious IPs detected in the same /24 subnet — consider blocking 91.193.232.0/24
- 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 91.193.232.5 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
🤖 User-Agent Anomaly Defense
IP 91.193.232.5 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Neighbors in 91.193.232.0/24
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
Blacklist Status (DNSBL)
This IP was checked against major DNS-based blacklists used by mail servers and firewalls worldwide.
Checked: Spamhaus, SpamCop, Barracuda, SORBS, CBL, UCEProtect. Results may change over time.
Threat Analysis
91.193.232.5 has been assigned a threat score of 100/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
The following attack categories were identified:
📊 Threat Analysis
91.193.232.5 is registered in Atlanta, United States, operating on the network of Clouvider Limited. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. During its 119-day observation window, we recorded 892 hostile requests from this IP — roughly 7.5 per day on average. This address belongs to a datacenter or cloud hosting provider. Hosting IPs are frequently leveraged by threat actors who rent cheap VPS instances specifically for conducting attacks. The dual attack vectors of Path Enumeration combined with User-Agent Anomaly indicate a coordinated assault rather than opportunistic scanning. Our records show 36,306 malicious IPs originating from United States, positioning it as a major contributor to global threat activity. At 100/100, this is an extremely high-risk address. All traffic should be considered hostile.
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.
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💡 Remote Code Execution (RCE)
RCE vulnerabilities allow attackers to execute arbitrary code on target servers. These critical flaws often arise from deserialization bugs, template injection, or file upload vulnerabilities, and represent the highest severity class of web application weaknesses.
💡 CAPTCHA and Bot Detection
CAPTCHAs remain a primary bot defense but face increasing bypass rates from AI-powered solvers. Modern alternatives include invisible behavioral analysis, proof-of-work challenges, and device fingerprinting that detect bots without impacting user experience.