IP Threat Report
172.195.104.24
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Burst 128/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 17/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 18/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 36/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 53/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 56/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 61/10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 136 | Medium-risk: admin panels, config files | +60 | |
| Danger medium hits: 221 | Medium-risk: admin panels, config files | +60 | |
| Danger medium hits: 41 | Medium-risk: admin panels, config files | +60 | |
| Danger strong hits: 12 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Danger strong hits: 24 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger strong hits: 77 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Foreign referer | Referer from unrelated external domain | +10 | |
| Probe 302→404 | Behavioral anomaly detected by automated analysis | +20 |
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
Recommendations
Actions taken & recommended
- IP 172.195.104.24 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 172.195.104.24 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
🌊 Traffic Flood Defense
IP 172.195.104.24 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
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
172.195.104.24 has been assigned a threat score of 255/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
The following attack categories were identified:
📊 Threat Analysis
Threat intelligence analysis has linked 172.195.104.24 to malicious activity originating from Querétaro City, Mexico, operating on the network of Foxtel ISP. The address has been under observation since its initial detection. Over a period of 5 days, this IP generated 454 malicious requests, averaging approximately 90.8 requests per day. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. Two attack patterns were identified (Path Enumeration and Request Flooding), suggesting a semi-automated campaign that targets multiple vulnerabilities. Our records show 282 malicious IPs originating from Mexico, positioning it as a significant contributor to global threat activity. A score of 255/100 places this address in the top tier of severity. Block and investigate any historical connections.
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.
Related Threats
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.