
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 3 | High-risk paths: shells, RCE vectors, exploits | +75 | |
| Danger medium hits: 166 | Medium-risk: admin panels, config files | +60 | |
| Burst: 47 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 132 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| 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: 37 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 115 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 54 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 156 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 4 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 249 | Medium-risk: admin panels, config files | +60 | |
| Burst: 53 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 145 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.
Address UA spoofing from 4.219.12.178: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 4.219.12.178.
Block scanning from 4.219.12.178: 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.
4.219.12.178 has been assigned a threat score of 245/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.
The following attack categories were identified:
4.219.12.178 is registered in Lorenskog, Norway, operating on the network of Microsoft Corporation. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. 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 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. With 108 flagged addresses, Norway represents a significant presence in our threat database. At 245/100, 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.
Examining HTTP headers beyond User-Agent reveals attack tools and automated scripts. Missing standard headers, unusual ordering, non-standard values, and inconsistencies with claimed client identity all serve as reliable detection signals.
Automated response systems can block threats in milliseconds, far faster than human analysts. However, automation requires careful safeguards — rate limits on blocking actions, automatic expiration, and human review queues prevent automated systems from causing self-inflicted outages.