
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 4 | Medium-risk: admin panels, config files | +40 | |
| 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 72.57.70.45: 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 |
| 3128 | Unknown | Low | Service on port 3128 |
| 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 |
| 21242 | Unknown | Low | Service on port 21242 |
| 52931 | Unknown | Low | Service on port 52931 |
| 52951 | Unknown | Low | Service on port 52951 |
| CVE ID | Link |
|---|---|
| CVE-2025-62168 | NVD → |
| CVE-2023-49288 | NVD → |
| CVE-2020-24606 | NVD → |
| CVE-2019-18679 | NVD → |
| CVE-2019-18677 | NVD → |
| CVE-2018-1000024 | NVD → |
| CVE-2019-12524 | NVD → |
| CVE-2023-46847 | NVD → |
| CVE-2021-31807 | NVD → |
| CVE-2023-46728 | NVD → |
| CVE-2021-33620 | NVD → |
| CVE-2020-14058 | NVD → |
| CVE-2024-37894 | NVD → |
| CVE-2020-15049 | NVD → |
| CVE-2019-12525 | NVD → |
| CVE-2019-12529 | NVD → |
| CVE-2025-59362 | NVD → |
| CVE-2020-25097 | NVD → |
| CVE-2019-12520 | NVD → |
| CVE-2019-13345 | NVD → |
| CVE-2021-31806 | NVD → |
| CVE-2026-33515 | NVD → |
| CVE-2026-33526 | NVD → |
| CVE-2019-12523 | NVD → |
| CVE-2019-12521 | 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 This volume strongly suggests severely outdated software.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.
72.57.70.45 has been assigned a threat score of 70/100 (High). This score indicates high threat severity. The IP has shown clear patterns of malicious behavior that warrant immediate defensive measures.
The following attack categories were identified:
The address 72.57.70.45 originates from Los Angeles, United States, operating on the network of HostPapa. It was identified through automated analysis of incoming network traffic across monitored endpoints. Our sensors captured 1 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~1 requests per 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. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. United States currently accounts for 201 blocked IPs in our database, making it a significant source of malicious traffic. A threat score of 70/100 places this IP in the high-risk category. Blocking at the firewall level is 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.
SQL injection remains one of the most common web attack vectors. Attackers inject malicious SQL code through input fields to extract database contents, modify data, or gain administrative access. Automated scanners test for SQLi vulnerabilities at massive scale.
WAFs inspect HTTP traffic to block common attacks but require careful tuning. Overly aggressive rules cause false positives while permissive configurations miss attacks. Modern WAFs combine signature matching with behavioral analysis and machine learning.