
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 6 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 152 | 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: 56 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 152 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 45 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 760 | Medium-risk: admin panels, config files | +60 | |
| Burst: 196 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 200 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 9 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 65 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 62 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 49 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 154 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 166 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 12 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 228 | Medium-risk: admin panels, config files | +60 | |
| Burst: 59 req / 2s | 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 51.103.21.74: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
IP 51.103.21.74 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 51.103.21.74.
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.
51.103.21.74 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:
IP address 51.103.21.74 has been traced to Paris, France, operating on the network of Microsoft. Our threat detection systems have flagged this address based on observed malicious behavior patterns. Over a period of 1 days, this IP generated 9 malicious requests, averaging approximately 9 requests per day. Classified as a hosting IP, this address likely runs on a rented server or cloud instance. Attackers prefer datacenter IPs for their high bandwidth and disposable nature. The combination of 3 distinct attack vectors indicates a sophisticated, multi-pronged threat actor deploying automated tools that probe multiple attack surfaces simultaneously. France currently accounts for 201 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.
False positives erode trust in security systems and waste analyst resources. Effective management requires feedback loops, allowlisting mechanisms, contextual analysis, and regular tuning of detection rules based on operational experience.