IP Threat Report
34.85.241.128
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 17/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 8/2s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 3 | Medium-risk: admin panels, config files | +30 | |
| Danger strong hits: 57 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| 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 15179 malicious IPs from this autonomous system.
Recommendations
Actions taken & recommended
- IP 34.85.241.128 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 34.85.241.0/24
- 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 34.85.241.128 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 34.85.241.128.
🤖 Bot Detection
Address UA spoofing from 34.85.241.128: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Neighbors in 34.85.241.0/24
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
34.85.241.128 has been assigned a threat score of 250/100 (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
34.85.241.128 is registered in Washington, United States, operating on the network of Google LLC. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. During its 1-day observation window, we recorded 43 hostile requests from this IP — roughly 43 per day on average. Operating from datacenter infrastructure, this IP is typical of addresses used in organized attack operations. Cloud and VPS providers are commonly exploited as launching platforms for automated scanning. With 3 different attack patterns detected, this IP exhibits behavior characteristic of advanced automated scanning frameworks. United States currently accounts for 36,430 blocked IPs in our database, making it a major source of malicious traffic. A score of 250/100 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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💡 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.
💡 Insider Threat Indicators
Insider threats — whether malicious or negligent — account for a significant percentage of data breaches. Behavioral analytics detecting unusual access patterns, data downloads, and privilege escalation help identify insider risks before damage occurs.