
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Burst: 13 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 13 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| 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 178.46.100.110 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
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.
178.46.100.110 has been assigned a threat score of 130/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.
The following attack categories were identified:
The address 178.46.100.110 originates from Yekaterinburg, Russia, operating on the network of Rostelecom networks. It was identified through automated analysis of incoming network traffic across monitored endpoints. Over a period of 1 days, this IP generated 1 malicious requests, averaging approximately 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. The IP is engaged in request flooding, sending traffic at rates designed to exhaust server capacity. With 190 flagged addresses, Russia represents a significant presence in our threat database. A score of 130/100 places this address in the top tier of severity. Block and investigate any historical connections.
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.
Correlating logs across web servers, firewalls, DNS, and authentication systems reveals attack patterns invisible in individual log sources. Modern SIEM platforms use statistical analysis to connect related events across time and systems.