
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: 15 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 209.85.158.119 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.
209.85.158.119 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:
Our monitoring infrastructure has identified 209.85.158.119, geolocated to Mountain View, United States, operating on the network of Google LLC, as a source of suspicious network activity. The address has been active for 1 days in our monitoring system, producing 1 flagged requests at a rate of ~1/day. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. The IP is engaged in request flooding, sending traffic at rates designed to exhaust server capacity. With 100 flagged addresses, United States represents a notable 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.
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.
When multiple IPs in a subnet show malicious behavior, subnet blocking efficiently neutralizes the threat. However, overly broad blocking risks impacting legitimate users. Analysis of subnet ownership and historical behavior guides appropriate blocking scope.