
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 12 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 291 | Medium-risk: admin panels, config files | +60 | |
| Burst: 48 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 138 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 16 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 416 | 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: 85 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 200 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 196 | Medium-risk: admin panels, config files | +60 | |
| Burst: 139 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 208 | Medium-risk: admin panels, config files | +60 | |
| Burst: 52 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 171 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 54 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 167 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 9 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 194 | Medium-risk: admin panels, config files | +60 | |
| Burst: 154 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 64 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 189 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 4.223.172.220 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
IP 4.223.172.220 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
IP 4.223.172.220 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
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.
4.223.172.220 has been assigned a threat score of 280/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
The following attack categories were identified:
Network traffic from 4.223.172.220, located in Gävle, Sweden, operating on the network of Microsoft Corporation, has been classified as malicious by our automated threat scoring engine. During its 1-day observation window, we recorded 7 hostile requests from this IP — roughly 7 per day on average. This address belongs to a datacenter or cloud hosting provider. Hosting IPs are frequently leveraged by threat actors who rent cheap VPS instances specifically for conducting attacks. The diversity of 3 separate attack methods suggests a comprehensive attack toolkit — likely an automated scanner that tests for vulnerabilities across multiple categories. With 101 flagged addresses, Sweden represents a significant presence in our threat database. 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.
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.
Analyzing network flows (NetFlow, sFlow, IPFIX) provides visibility into traffic patterns without inspecting packet contents. Flow data reveals scanning activity, data exfiltration, lateral movement, and command-and-control channels at scale.