
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 3 | High-risk paths: shells, RCE vectors, exploits | +75 | |
| Danger medium hits: 2 | Medium-risk: admin panels, config files | +20 | |
| POST requests present | Behavioral anomaly detected by automated analysis | +8 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Block 177.63.238.179 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.
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.
177.63.238.179 has been assigned a threat score of 103/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
The address 177.63.238.179 originates from São Paulo, Brazil, operating on the network of Vivo. It was identified through automated analysis of incoming network traffic across monitored endpoints. Over a period of 1 days, this IP generated 1 malicious requests, averaging approximately 1 requests per day. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. Brazil currently accounts for 151 blocked IPs in our database, making it a significant source of malicious traffic. With a threat score of 103/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
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.
Credential stuffing uses stolen username-password pairs from data breaches to attempt logins across many websites. Since users frequently reuse passwords, these automated attacks achieve success rates of 0.1-2%, which translates to thousands of compromised accounts from millions of attempts.
Analyzing attack patterns at the AS (Autonomous System) level reveals which networks harbor the most malicious activity. Some ASes have abuse rates orders of magnitude higher than average, indicating lax enforcement of acceptable use policies.