IP Threat Report
163.5.210.237
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Danger strong hits: 92 | 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: 8 req / 2s | 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 163.5.210.237 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
🤖 User-Agent Anomaly Defense
IP 163.5.210.237 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
🔎 Directory Scan Defense
IP 163.5.210.237 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
🌊 Traffic Flood Defense
IP 163.5.210.237 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
Open Ports & Services
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 5357 | Unknown | Low | Service on port 5357 |
| 5985 | Unknown | Low | Service on port 5985 |
Data source: Shodan InternetDB. Scanned independently of abuse.mom.
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
163.5.210.237 has been assigned a threat score of 230/100 (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
163.5.210.237 is registered in Montréal, France, operating on the network of 12651980 Canada Inc.. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. The combination of 3 distinct attack vectors indicates a sophisticated, multi-pronged threat actor deploying automated tools that probe multiple attack surfaces simultaneously. At 230/100, this is an extremely high-risk address. All traffic should be considered hostile.
This IP is classified as residential, suggesting it may belong to a compromised home device, IoT botnet member, or an infected personal computer. Residential IPs involved in attacks often indicate malware infection without the owner's knowledge.
Related Threats
🏢 Same network: AS399486
151.247.22.88 (195)45.88.91.184 (180)80.76.49.205 (180)79.110.49.80 (175)View all →Security Intelligence
💡 HTTP Header Analysis for Threat Detection
Examining HTTP headers beyond User-Agent reveals attack tools and automated scripts. Missing standard headers, unusual ordering, non-standard values, and inconsistencies with claimed client identity all serve as reliable detection signals.
💡 API Abuse and Enumeration
Modern attacks increasingly target APIs rather than traditional web interfaces. Attackers enumerate endpoints, test for broken authentication, and exploit excessive data exposure. API attacks are harder to detect as they mimic legitimate programmatic access patterns.