
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Directory Scan | Behavioral anomaly detected by automated analysis | +0 | |
| DDoS / Flood | 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.
Add 34.89.173.9 to your firewall blocklist. Review logs for successful connections. Enable comprehensive logging on all public-facing services.
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.
34.89.173.9 has been assigned a threat score of 260/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
34.89.173.9 is registered in Frankfurt, Germany, operating on the network of Google LLC. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. The address has been active for 12 days in our monitoring system, producing 245 flagged requests at a rate of ~20.4/day. Our records show 101 malicious IPs originating from Germany, positioning it as a significant contributor to global threat activity. With a threat score of 260/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
Distributed denial of service attacks overwhelm infrastructure with traffic volume. Effective mitigation combines always-on traffic scrubbing, anycast network distribution, rate limiting, and the ability to quickly scale absorption capacity during attacks.
Analyzing User-Agent strings reveals automated tools masquerading as legitimate browsers. Inconsistencies between claimed browser capabilities and actual behavior, impossible version combinations, and known scanner signatures help identify malicious clients.