
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: python | Known bot/crawler User-Agent detected | +40 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 128.123.63.87 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Block scanning from 128.123.63.87: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
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.
128.123.63.87 has been assigned a threat score of 65/100 (High). At this threat level, the IP is considered high risk. Firewall rules should be updated to deny traffic from this source.
The following attack categories were identified:
Threat intelligence analysis has linked 128.123.63.87 to malicious activity originating from Las Cruces, United States, operating on the network of New Mexico State University. The address has been under observation since its initial detection. Our sensors captured 4 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~4 requests per day. The address is classified as residential, meaning it likely belongs to an end-user ISP connection. Malicious activity from residential IPs typically indicates device compromise or botnet membership. The dual attack vectors of User-Agent Anomaly combined with Path Enumeration indicate a coordinated assault rather than opportunistic scanning. United States currently accounts for 102 blocked IPs in our database, making it a significant source of malicious traffic. At 65/100, this IP presents a meaningful threat. Implement rate limiting with escalation to blocking.
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.
TLS fingerprinting creates unique identifiers based on how clients negotiate encrypted connections. The JA3 and JA4 methods generate hashes from TLS ClientHello parameters, enabling identification of specific tools and malware regardless of IP address changes.
Deepfake audio and video enable convincing impersonation of executives and trusted individuals. Real-time voice cloning has been used in successful fraud campaigns, adding a new dimension to social engineering that traditional security training does not address.