
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Burst 12/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 8/2s | Abnormally fast request rate — automated scanning | +35 | |
| Foreign referer | Referer from unrelated external domain | +10 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 188.162.242.203.
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.
188.162.242.203 has been assigned a threat score of 80/100 (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:
188.162.242.203 is registered in Khabarovsk, Russia, operating on the network of PJSC MegaFon. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. Over a period of 5 days, this IP generated 325 malicious requests, averaging approximately 65 requests per day. The address belongs to a mobile carrier network. The sustained pattern of malicious requests indicates either a compromised device or deliberate abuse. Rate-based attacks from this IP aim to overwhelm server resources through high-volume request flooding. With 101 flagged addresses, Russia represents a significant presence in our threat database. A threat score of 80/100 places this IP in the high-risk category. Blocking at the firewall level is recommended.
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.
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.