
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Foreign referer seen | Referer from unrelated external domain | +10 | |
| Danger strong hits: 3 | High-risk paths: shells, RCE vectors, exploits | +75 | |
| Imported from old blocklist | Behavioral anomaly detected by automated analysis | +0 |
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 87.106.155.41: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
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.
87.106.155.41 has been assigned a threat score of 85/100 (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:
Our monitoring infrastructure has identified 87.106.155.41, geolocated to Berlin, Germany, operating on the network of IONOS SE, as a source of suspicious network activity. Our sensors captured 8 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~8 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. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. Germany currently accounts for 23 blocked IPs in our database, making it a notable source of malicious traffic. At 85/100, this IP warrants immediate defensive action.
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.
OSINT techniques leverage publicly available information for security research. DNS records, WHOIS data, certificate transparency logs, social media, and code repositories all provide valuable intelligence for threat analysis without requiring special access or tools.