
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 10 | Medium-risk: admin panels, config files | +60 | |
| Foreign referer seen | Referer from unrelated external domain | +10 | |
| 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 174.136.204.40 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.
174.136.204.40 has been assigned a threat score of 70/100 (High). This score indicates high threat severity. The IP has shown clear patterns of malicious behavior that warrant immediate defensive measures.
Our monitoring infrastructure has identified 174.136.204.40, geolocated to Los Angeles, United States, operating on the network of DMIT Cloud Services, as a source of suspicious network activity. The address has been active for 1 days in our monitoring system, producing 3 flagged requests at a rate of ~3/day. 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. With 101 flagged addresses, United States represents a significant presence in our threat database. At 70/100, this IP warrants immediate defensive action.
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.
Vulnerability scanning is the automated process of probing web applications for known weaknesses. Attackers use tools like Nuclei, Nikto, and ZAP to test thousands of hosts per hour, looking for exposed configuration files, outdated software, and default credentials.
Artificial intelligence enables more convincing phishing content, faster vulnerability discovery, and adaptive attack strategies that learn from defensive responses. AI-generated social engineering and automated exploit development represent growing threats.