
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 6 | 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 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Block scanning from 173.232.7.166: 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 |
|---|---|---|---|
| 80 | HTTP | Low | HTTP web server — standard web traffic |
| 8000 | Unknown | Low | Service on port 8000 |
| 8080 | HTTP-Alt | Low | HTTP alternative port — often used for admin panels or proxies |
| 8800 | Unknown | Low | Service on port 8800 |
| CVE ID | Link |
|---|---|
| CVE-2019-12521 | NVD → |
| CVE-2023-49285 | NVD → |
| CVE-2021-28116 | NVD → |
| CVE-2020-8517 | NVD → |
| CVE-2026-32748 | NVD → |
| CVE-2021-33620 | NVD → |
| CVE-2019-18679 | NVD → |
| CVE-2019-12519 | NVD → |
| CVE-2026-33526 | NVD → |
| CVE-2025-59362 | NVD → |
| CVE-2019-18860 | NVD → |
| CVE-2021-46784 | NVD → |
| CVE-2019-12523 | NVD → |
| CVE-2020-14058 | NVD → |
| CVE-2019-12526 | NVD → |
| CVE-2019-18678 | NVD → |
| CVE-2021-28652 | NVD → |
| CVE-2016-10002 | NVD → |
| CVE-2018-19131 | NVD → |
| CVE-2016-2390 | NVD → |
| CVE-2016-3947 | NVD → |
| CVE-2018-19132 | NVD → |
| CVE-2022-41318 | NVD → |
| CVE-2020-15049 | NVD → |
| CVE-2021-31808 | NVD → |
🔴 This host has 59 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 This volume strongly suggests severely outdated software.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.
173.232.7.166 has been assigned a threat score of 105/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
The following attack categories were identified:
The address 173.232.7.166 originates from Henderson, United States, operating on the network of Eonix Corporation. It was identified through automated analysis of incoming network traffic across monitored endpoints. The address has been active for 1 days in our monitoring system, producing 1 flagged requests at a rate of ~1/day. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. The IP exhibits directory enumeration behavior, systematically requesting non-existent paths to discover hidden files and misconfigured resources. Our records show 133 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. With a threat score of 105/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
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.
SSRF attacks trick servers into making requests to internal resources that should not be publicly accessible. This can expose cloud metadata endpoints, internal APIs, and private network services, potentially leading to full infrastructure compromise.
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.