
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 | |
| Danger medium hits: 7 | Medium-risk: admin panels, config files | +60 | |
| Danger medium hits: 3 | Medium-risk: admin panels, config files | +30 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 151.245.166.147 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
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 |
| 60000 | Unknown | Low | Service on port 60000 |
| CVE ID | Link |
|---|---|
| CVE-2021-33620 | NVD → |
| CVE-2021-28116 | NVD → |
| CVE-2025-59362 | NVD → |
| CVE-2024-37894 | NVD → |
| CVE-2024-25111 | NVD → |
| CVE-2023-49285 | NVD → |
| CVE-2021-31806 | NVD → |
| CVE-2025-54574 | NVD → |
| CVE-2021-31807 | NVD → |
| CVE-2025-62168 | NVD → |
| CVE-2023-49288 | NVD → |
| CVE-2022-41317 | NVD → |
| CVE-2023-46847 | NVD → |
| CVE-2023-5824 | NVD → |
| CVE-2021-31808 | NVD → |
| CVE-2023-50269 | NVD → |
| CVE-2021-46784 | NVD → |
| CVE-2023-46846 | NVD → |
| CVE-2021-28651 | NVD → |
| CVE-2021-28652 | NVD → |
| CVE-2023-49286 | NVD → |
| CVE-2023-46728 | NVD → |
| CVE-2021-28662 | NVD → |
| CVE-2023-46724 | NVD → |
| CVE-2022-41318 | 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 This volume strongly suggests severely outdated software.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.
151.245.166.147 has been assigned a threat score of 105/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.
The following attack categories were identified:
Network traffic from 151.245.166.147, located in Seattle, United States, operating on the network of Sprious LLC, has been classified as malicious by our automated threat scoring engine. During its 15-day observation window, we recorded 5 hostile requests from this IP — roughly 0.3 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. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. With 205 flagged addresses, United States represents a significant presence in our threat database. 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.
Credential stuffing uses stolen username-password pairs from data breaches to attempt logins across many websites. Since users frequently reuse passwords, these automated attacks achieve success rates of 0.1-2%, which translates to thousands of compromised accounts from millions of attempts.
Threat scoring combines multiple signals — request patterns, known signatures, IP reputation, geographic risk, and behavioral analysis — into a single actionable metric. Weighted scoring models allow tuning sensitivity to balance security with usability.