
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.
IP 64.188.3.197 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 |
|---|---|---|---|
| 80 | HTTP | Low | HTTP web server — standard web traffic |
| 3128 | Unknown | Low | Service on port 3128 |
| 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 |
| CVE ID | Link |
|---|---|
| CVE-2021-33620 | NVD → |
| CVE-2019-18676 | NVD → |
| CVE-2019-12526 | NVD → |
| CVE-2020-24606 | NVD → |
| CVE-2021-28116 | NVD → |
| CVE-2018-19132 | NVD → |
| CVE-2018-1000027 | NVD → |
| CVE-2025-59362 | NVD → |
| CVE-2020-15810 | NVD → |
| CVE-2019-12520 | NVD → |
| CVE-2020-8450 | NVD → |
| CVE-2020-15811 | NVD → |
| CVE-2024-37894 | NVD → |
| CVE-2023-49285 | NVD → |
| CVE-2021-31806 | NVD → |
| CVE-2019-18677 | NVD → |
| CVE-2025-54574 | NVD → |
| CVE-2019-12521 | NVD → |
| CVE-2019-13345 | NVD → |
| CVE-2018-1000024 | NVD → |
| CVE-2020-15049 | NVD → |
| CVE-2021-31807 | NVD → |
| CVE-2019-12524 | NVD → |
| CVE-2020-14058 | NVD → |
| CVE-2018-19131 | NVD → |
🔴 This host has 56 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 This volume strongly suggests severely outdated software.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.
64.188.3.197 has been assigned a threat score of 70/100 (High). This classifies it as a high-severity threat. Proactive blocking is recommended for sensitive infrastructure.
The following attack categories were identified:
Network traffic from 64.188.3.197, located in Los Angeles, United States, operating on the network of HostPapa, has been classified as malicious by our automated threat scoring engine. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. Operating from a residential network, this IP may represent a compromised home gateway or IoT device that has been drafted into a larger attack infrastructure. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. With 200 flagged addresses, United States represents a significant presence in our threat database. The score of 70/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.
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.
Automated response systems can block threats in milliseconds, far faster than human analysts. However, automation requires careful safeguards — rate limits on blocking actions, automatic expiration, and human review queues prevent automated systems from causing self-inflicted outages.