IP Threat Report
173.230.135.36
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 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Burst 13/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 14/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 14/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 7/2s | Abnormally fast request rate — automated scanning | +35 | |
| Foreign referer | Referer from unrelated external domain | +10 | |
| Probe 302→404 | Behavioral anomaly detected by automated analysis | +20 | |
| 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 173.230.135.36 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 173.230.135.36: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
🌊 Traffic Flood Defense
IP 173.230.135.36 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
🤖 User-Agent Anomaly Defense
IP 173.230.135.36 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
173.230.135.36 has been assigned a threat score of 140/100 (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
173.230.135.36 is registered in Atlanta, United States, operating on the network of Akamai Technologies, Inc.. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. Our sensors captured 518 malicious requests from this address across a 6-day span, reflecting a sustained attack cadence of ~86.3 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. The diversity of 3 separate attack methods suggests a comprehensive attack toolkit — likely an automated scanner that tests for vulnerabilities across multiple categories. United States currently accounts for 197 blocked IPs in our database, making it a significant source of malicious traffic. At 140/100, 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.
💡 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.