
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 11 | High-risk paths: shells, RCE vectors, exploits | +100 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Block 167.86.85.138 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.
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.
167.86.85.138 has been assigned a threat score of 100/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
IP address 167.86.85.138 has been traced to Nuremberg, Germany, operating on the network of Contabo GmbH. Our threat detection systems have flagged this address based on observed malicious behavior patterns. During its 4-day observation window, we recorded 356 hostile requests from this IP — roughly 89 per day on average. The IP is classified as hosting/datacenter infrastructure, commonly associated with rented servers used for automated attack campaigns, botnet command-and-control, or vulnerability scanning at scale. At 100/100, this is an extremely high-risk address. All traffic should be considered hostile.
This IP belongs to a hosting or data center provider. Malicious traffic from hosting infrastructure often originates from compromised VPS instances, rented servers used for scanning campaigns, or abused free-tier cloud accounts. Hosting providers typically respond to abuse reports within 24-72 hours.
Command injection occurs when attackers insert operating system commands through application inputs. Successful exploitation grants direct server access, enabling data theft, malware installation, and lateral movement across networks.
Threat scoring combines multiple signals — request patterns, known signatures, IP reputation, geographic risk, and behavioral analysis — into a single actionable metric. Weighted scoring models allow tuning sensitivity to balance security with usability.