
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Directory Scan | Behavioral anomaly detected by automated analysis | +0 | |
| DDoS / Flood | Behavioral anomaly detected by automated analysis | +0 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Add 20.197.192.242 to your firewall blocklist. Review logs for successful connections. Enable comprehensive logging on all public-facing services.
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.
20.197.192.242 has been assigned a threat score of 280/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
IP address 20.197.192.242 has been traced to São Paulo, Brazil, operating on the network of Microsoft Corporation. Our threat detection systems have flagged this address based on observed malicious behavior patterns. Over a period of 27 days, this IP generated 436 malicious requests, averaging approximately 16.1 requests per day. Brazil currently accounts for 102 blocked IPs in our database, making it a significant source of malicious traffic. With a threat score of 280/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly 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.
CAPTCHAs remain a primary bot defense but face increasing bypass rates from AI-powered solvers. Modern alternatives include invisible behavioral analysis, proof-of-work challenges, and device fingerprinting that detect bots without impacting user experience.