
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.
Add 102.209.247.2 to your firewall blocklist. Review logs for successful connections. Enable comprehensive logging on all public-facing services.
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 161 | Unknown | Low | Service on port 161 |
Data source: Shodan InternetDB. Scanned independently of abuse.mom.
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.
102.209.247.2 has been assigned a threat score of 103/100 (Critical). This represents a critical risk level. Our detection systems have flagged multiple high-confidence indicators of malicious intent from this address.
Threat intelligence analysis has linked 102.209.247.2 to malicious activity originating from Windhoek, NA, operating on the network of Rocketnet Internet Namibia. The address has been under observation since its initial detection. Our sensors captured 1 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~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. A score of 103/100 places this address in the top tier of severity. Block and investigate any historical connections.
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.
Vulnerability scanning is the automated process of probing web applications for known weaknesses. Attackers use tools like Nuclei, Nikto, and ZAP to test thousands of hosts per hour, looking for exposed configuration files, outdated software, and default credentials.
Artificial intelligence enables more convincing phishing content, faster vulnerability discovery, and adaptive attack strategies that learn from defensive responses. AI-generated social engineering and automated exploit development represent growing threats.