
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 5 | Medium-risk: admin panels, config files | +50 | |
| Danger medium hits: 6 | Medium-risk: admin panels, config files | +60 | |
| Foreign referer | Referer from unrelated external domain | +10 | |
| Foreign referer seen | 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.
Add 103.65.237.92 to your firewall blocklist. Review logs for successful connections. Enable comprehensive logging on all public-facing services.
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
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.
103.65.237.92 has been assigned a threat score of 70/100 (High). This classifies it as a high-severity threat. Proactive blocking is recommended for sensitive infrastructure.
The address 103.65.237.92 originates from Jakarta, Indonesia, operating on the network of PT Berkah Solusi Teknologi Informasi. It was identified through automated analysis of incoming network traffic across monitored endpoints. During its 84-day observation window, we recorded 42 hostile requests from this IP — roughly 0.5 per day on average. Operating from a residential network, this IP may represent a compromised home gateway or IoT device that has been drafted into a larger attack infrastructure. Indonesia currently accounts for 104 blocked IPs in our database, making it a significant source of malicious traffic. The score of 70/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.
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.
XSS attacks inject malicious scripts into web pages viewed by other users. Reflected XSS uses crafted URLs, while stored XSS persists in databases. Both types can steal session cookies, redirect users, or deface websites.
Correlating logs across web servers, firewalls, DNS, and authentication systems reveals attack patterns invisible in individual log sources. Modern SIEM platforms use statistical analysis to connect related events across time and systems.