
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 64 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 201 | 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: 24 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 86 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 87 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 186 | Medium-risk: admin panels, config files | +60 | |
| Burst: 85 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 96 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 87 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 88 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Danger medium hits: 2 | Medium-risk: admin panels, config files | +20 | |
| Burst: 84 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 128 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 303 | Medium-risk: admin panels, config files | +60 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Address UA spoofing from 4.204.246.56: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Block scanning from 4.204.246.56: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
IP 4.204.246.56 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
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.
4.204.246.56 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:
Threat intelligence analysis has linked 4.204.246.56 to malicious activity originating from Toronto, Canada, operating on the network of Microsoft Corporation. The address has been under observation since its initial detection. Our sensors captured 41 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~41 requests per 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. The diversity of 3 separate attack methods suggests a comprehensive attack toolkit — likely an automated scanner that tests for vulnerabilities across multiple categories. Our records show 101 malicious IPs originating from Canada, positioning it as a significant contributor to global threat activity. A score of 280/100 places this address in the top tier of severity. Block and investigate any historical connections.
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.
Advanced techniques enable threat detection while minimizing privacy impact. Encrypted DNS, differential privacy in analytics, and federated learning for threat models allow effective security monitoring without unnecessary surveillance of legitimate user behavior.