
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 9 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 240 | Medium-risk: admin panels, config files | +60 | |
| Burst: 43 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 140 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 6 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 238 | Medium-risk: admin panels, config files | +60 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Burst: 42 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 131 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 48 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 157 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 50 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 134 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 150 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 45 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 125 req / 10s | Abnormally fast request rate — automated scanning | +35 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 20.251.15.206 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 20.251.15.206.
Block scanning from 20.251.15.206: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
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.
20.251.15.206 has been assigned a threat score of 280/100 (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:
Network traffic from 20.251.15.206, located in Lorenskog, Norway, operating on the network of Microsoft Corporation, has been classified as malicious by our automated threat scoring engine. The address has been active for 1 days in our monitoring system, producing 6 flagged requests at a rate of ~6/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 3 different attack patterns detected, this IP exhibits behavior characteristic of advanced automated scanning frameworks. Norway currently accounts for 101 blocked IPs in our database, making it a significant source of malicious traffic. At 280/100, 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.
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.
Correlating logs across web servers, firewalls, DNS, and authentication systems reveals attack patterns invisible in individual log sources. Modern SIEM platforms use statistical analysis to connect related events across time and systems.