IP Threat Report
34.94.20.43
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 12 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Burst: 7 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 12 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 18 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 34.94.20.43 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 34.94.20.0/24
- 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 34.94.20.43 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 34.94.20.43.
Neighbors in 34.94.20.0/24
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
34.94.20.43 has been assigned a threat score of 205/100 (Critical). This represents a critical risk level. Our detection systems have flagged multiple high-confidence indicators of malicious intent from this address.
The following attack categories were identified:
📊 Threat Analysis
IP address 34.94.20.43 has been traced to Los Angeles, United States, operating on the network of Google LLC. Our threat detection systems have flagged this address based on observed malicious behavior patterns. Over a period of 1 days, this IP generated 2 malicious requests, averaging approximately 2 requests per day. The IP is classified as hosting/datacenter infrastructure, commonly associated with rented servers used for automated attack campaigns, botnet command-and-control, or vulnerability scanning at scale. Two attack patterns were identified (Path Enumeration and Request Flooding), suggesting a semi-automated campaign that targets multiple vulnerabilities. With 141 flagged addresses, United States represents a significant presence in our threat database. With a threat score of 205/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
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
🇺🇸 Top threats from United States
104.28.246.115 (350)104.28.246.113 (340)104.28.246.116 (340)104.28.235.58 (340)104.28.246.122 (340)View all →Security Intelligence
💡 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.
💡 Threat Score Calculation Methods
Threat scoring combines multiple signals — request patterns, known signatures, IP reputation, geographic risk, and behavioral analysis — into a single actionable metric. Weighted scoring models allow tuning sensitivity to balance security with usability.