IP Threat Report
34.21.6.180
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 | |
| Danger medium hits: 11 | Medium-risk: admin panels, config files | +60 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Burst: 13 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 13 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 5 | Medium-risk: admin panels, config files | +50 | |
| Burst: 7 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 6 | Medium-risk: admin panels, config files | +60 | |
| Burst: 8 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 12 | Medium-risk: admin panels, config files | +60 | |
| Burst: 14 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 14 req / 10s | Abnormally fast request rate — automated scanning | +35 |
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 34.21.6.180 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 34.21.6.0/24
- 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 34.21.6.180 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 34.21.6.180.
Neighbors in 34.21.6.0/24
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
34.21.6.180 has been assigned a threat score of 180/100 (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 34.21.6.180 originates from Washington, United States, 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 4 malicious requests, averaging approximately 4 requests per day. 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 Request Flooding indicate a coordinated assault rather than opportunistic scanning. United States currently accounts for 143 blocked IPs in our database, making it a significant source of malicious traffic. A score of 180/100 places this address in the top tier of severity. Block and investigate any historical connections.
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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💡 Server-Side Request Forgery (SSRF)
SSRF attacks trick servers into making requests to internal resources that should not be publicly accessible. This can expose cloud metadata endpoints, internal APIs, and private network services, potentially leading to full infrastructure compromise.
💡 Credential Stuffing at Scale
Credential stuffing uses stolen username-password pairs from data breaches to attempt logins across many websites. Since users frequently reuse passwords, these automated attacks achieve success rates of 0.1-2%, which translates to thousands of compromised accounts from millions of attempts.