IP Threat Report
34.176.243.48
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 13/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 46/10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 40 | Medium-risk: admin panels, config files | +60 | |
| Danger strong hits: 241 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| POST seen | Behavioral anomaly detected by automated analysis | +8 | |
| 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
Recommendations
Actions taken & recommended
- IP 34.176.243.48 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 34.176.243.0/24
- 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 34.176.243.48 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
🌊 Flood / DDoS Mitigation
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 34.176.243.48.
🤖 User-Agent Anomaly Defense
IP 34.176.243.48 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Neighbors in 34.176.243.0/24
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
34.176.243.48 has been assigned a threat score of 288/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.
The following attack categories were identified:
📊 Threat Analysis
The address 34.176.243.48 originates from Santiago, CL, operating on the network of Google LLC. It was identified through automated analysis of incoming network traffic across monitored endpoints. Over a period of 1 days, this IP generated 56 malicious requests, averaging approximately 56 requests per day. 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. With 3 different attack patterns detected, this IP exhibits behavior characteristic of advanced automated scanning frameworks. CL currently accounts for 101 blocked IPs in our database, making it a significant source of malicious traffic. At 288/100, 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.
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.
💡 Digital Forensics Fundamentals
Digital forensics preserves and analyzes electronic evidence following attacks. Proper chain of custody, forensic imaging, timeline reconstruction, and artifact analysis are essential for understanding attack scope, attribution, and preventing recurrence.