
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Form spam: no_js_check | Spam/malware keywords in request content | +0 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Enable CAPTCHA on all public forms. Add honeypot fields. Rate-limit submissions to 3 per minute per IP. Deploy Akismet or CleanTalk.
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 443 | HTTPS | Low | HTTPS web server — encrypted web traffic |
| 8089 | Unknown | Low | Service on port 8089 |
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.
87.165.30.6 has been assigned a threat score of 70/100 (High). The IP is rated as a high-level threat. Network administrators should implement blocking rules and monitor for any connections from this address.
Our monitoring infrastructure has identified 87.165.30.6, geolocated to Bischofswiesen, Germany, operating on the network of Deutsche Telekom AG, as a source of suspicious network activity. 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 residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. Our records show 159 malicious IPs originating from Germany, positioning it as a significant contributor to global threat activity. 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.
Monitoring dark web forums and marketplaces provides advance warning of planned attacks, leaked credentials, and compromised data. This intelligence feeds into proactive defense measures before attacks reach their targets.