IP Threat Report
167.172.136.185
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Burst 6/2s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 2 | Medium-risk: admin panels, config files | +20 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| POST seen | Behavioral anomaly detected by automated analysis | +8 | |
| Probe 302→404 | Behavioral anomaly detected by automated analysis | +20 | |
| UA changed | Multiple User-Agents — bot rotation technique | +25 | |
| UA suspicious | Behavioral anomaly detected by automated analysis | +15 |
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 4069 malicious IPs from this autonomous system.
Recommendations
Actions taken & recommended
- IP 167.172.136.185 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
🔎 Path Enumeration Protection
Block scanning from 167.172.136.185: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
🌊 Traffic Flood Defense
IP 167.172.136.185 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
🤖 User-Agent Anomaly Defense
IP 167.172.136.185 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
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
167.172.136.185 has been assigned a threat score of 158/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
The following attack categories were identified:
📊 Threat Analysis
167.172.136.185 is registered in North Bergen, United States, operating on the network of DigitalOcean, LLC. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. The address has been active for 2 days in our monitoring system, producing 82 flagged requests at a rate of ~41/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. With 3 different attack patterns detected, this IP exhibits behavior characteristic of advanced automated scanning frameworks. Our records show 36,228 malicious IPs originating from United States, positioning it as a major contributor to global threat activity. At 158/100, 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.
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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.
💡 Rate Limiting and Throttling Strategies
Effective rate limiting must balance protection against abuse with allowing legitimate traffic bursts. Sliding window algorithms, token buckets, and adaptive thresholds based on client reputation provide layered defense against flooding attacks.