
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 6 | 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: 5 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Foreign referer seen | Referer from unrelated external domain | +10 | |
| Danger medium hits: 2 | Medium-risk: admin panels, config files | +20 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Block scanning from 31.193.188.238: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 31.193.188.238.
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.
31.193.188.238 has been assigned a threat score of 140/100 (Critical). This represents a critical risk level. Our detection systems have flagged multiple high-confidence indicators of malicious intent from this address.
The following attack categories were identified:
The address 31.193.188.238 originates from Ravenna, Italy, operating on the network of Michele Pietravalle trading as NetJoin. It was identified through automated analysis of incoming network traffic across monitored endpoints. Our sensors captured 4 malicious requests from this address across a 16-day span, reflecting a sustained attack cadence of ~0.3 requests per day. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. Two attack patterns were identified (Path Enumeration and Request Flooding), suggesting a semi-automated campaign that targets multiple vulnerabilities. Our records show 108 malicious IPs originating from Italy, positioning it as a significant contributor to global threat activity. At 140/100, this is an extremely high-risk address. All traffic should be considered hostile.
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.
RCE vulnerabilities allow attackers to execute arbitrary code on target servers. These critical flaws often arise from deserialization bugs, template injection, or file upload vulnerabilities, and represent the highest severity class of web application weaknesses.
Machine learning models analyze vast amounts of network traffic to identify attack patterns invisible to rule-based systems. Supervised models classify known attack types while unsupervised models detect anomalies that may indicate novel threats.