
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Burst 14/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 49/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 50/10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 143 | Medium-risk: admin panels, config files | +60 | |
| Danger medium hits: 165 | Medium-risk: admin panels, config files | +60 | |
| Danger medium hits: 171 | Medium-risk: admin panels, config files | +60 | |
| Danger medium hits: 258 | Medium-risk: admin panels, config files | +60 | |
| Danger medium hits: 286 | Medium-risk: admin panels, config files | +60 | |
| Danger strong hits: 14 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger strong hits: 16 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger strong hits: 18 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger strong hits: 21 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger strong hits: 32 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Probe 302→404 | Behavioral anomaly detected by automated analysis | +20 | |
| UA suspicious | Behavioral anomaly detected by automated analysis | +15 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 191.235.105.17 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 191.235.105.17.
Address UA spoofing from 191.235.105.17: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
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.
191.235.105.17 has been assigned a threat score of 280/100 (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:
Network traffic from 191.235.105.17, located in São Paulo, Brazil, operating on the network of Microsoft Corporation, has been classified as malicious by our automated threat scoring engine. During its 2-day observation window, we recorded 536 hostile requests from this IP — roughly 268 per day on average. 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. Our records show 13 malicious IPs originating from Brazil, positioning it as a notable contributor to global threat activity. 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.
Distributed denial of service attacks overwhelm infrastructure with traffic volume. Effective mitigation combines always-on traffic scrubbing, anycast network distribution, rate limiting, and the ability to quickly scale absorption capacity during attacks.
GraphQL APIs introduce specific vulnerabilities including introspection information disclosure, query complexity attacks, batching abuse, and authorization bypass through nested queries. Depth limiting, cost analysis, and field-level authorization address these GraphQL-specific threats.