
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Danger medium hits: 14 | Medium-risk: admin panels, config files | +60 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Foreign referer seen | Referer from unrelated external domain | +10 | |
| Danger medium hits: 3 | Medium-risk: admin panels, config files | +30 | |
| Danger medium hits: 6 | Medium-risk: admin panels, config files | +60 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Address UA spoofing from 209.163.119.206: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Block scanning from 209.163.119.206: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 4444 | Unknown | Low | Service on port 4444 |
| 8000 | Unknown | Low | Service on port 8000 |
| CVE ID | Link |
|---|---|
| CVE-2024-37894 | NVD → |
| CVE-2023-46728 | NVD → |
| CVE-2022-41317 | NVD → |
| CVE-2023-49288 | NVD → |
| CVE-2021-31807 | NVD → |
| CVE-2021-33620 | NVD → |
| CVE-2021-46784 | NVD → |
| CVE-2022-41318 | NVD → |
| CVE-2023-46847 | NVD → |
| CVE-2025-54574 | NVD → |
| CVE-2021-31806 | NVD → |
| CVE-2024-25617 | NVD → |
| CVE-2021-28652 | NVD → |
| CVE-2024-25111 | NVD → |
| CVE-2021-28116 | NVD → |
| CVE-2023-46724 | NVD → |
| CVE-2023-50269 | NVD → |
| CVE-2021-31808 | NVD → |
| CVE-2023-5824 | NVD → |
| CVE-2025-59362 | NVD → |
| CVE-2023-49285 | NVD → |
| CVE-2024-45802 | NVD → |
| CVE-2025-62168 | NVD → |
| CVE-2021-28651 | NVD → |
| CVE-2023-46846 | NVD → |
🔴 This host has 27 known CVEs associated with its exposed services. This volume strongly suggests severely outdated software. Review each CVE in the NVD database.
Data source: Shodan InternetDB. Scanned independently of abuse.mom.
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.
209.163.119.206 has been assigned a threat score of 130/100 (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:
The address 209.163.119.206 originates from Chicago, United States, operating on the network of Emeigh Investments LLC. It was identified through automated analysis of incoming network traffic across monitored endpoints. Our sensors captured 4 malicious requests from this address across a 18-day span, reflecting a sustained attack cadence of ~0.2 requests per day. The address is classified as residential, meaning it likely belongs to an end-user ISP connection. Malicious activity from residential IPs typically indicates device compromise or botnet membership. The dual attack vectors of User-Agent Anomaly combined with Path Enumeration indicate a coordinated assault rather than opportunistic scanning. United States currently accounts for 204 blocked IPs in our database, making it a significant source of malicious traffic. At 130/100, 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.
TLS fingerprinting creates unique identifiers based on how clients negotiate encrypted connections. The JA3 and JA4 methods generate hashes from TLS ClientHello parameters, enabling identification of specific tools and malware regardless of IP address changes.
Signature-based detection matches known attack patterns but misses novel threats. Behavioral analysis identifies anomalies in request patterns, timing, and volume, catching zero-day attacks that signatures cannot recognize.