Extreme Threat
IP 103.220.207.174 is a critical-risk address originating from Bangladesh that has been linked to 387 confirmed hacking intrusion attempts, representing a severe threat to any exposed network service. This address, operated by KS Network Limited under ASN AS59362, was first and most recently reported in October 2025, indicating sustained malicious activity concentrated within a narrow timeframe. The threat level has been assessed at 10 out of 10, the maximum severity rating available in this intelligence system.
The abuse reports for IP 103.220.207.174 were generated exclusively through automated honeypot sensors, with all 387 reports categorizing the observed activity as general hacking attempts. This detection methodology indicates that the malicious traffic was specifically captured by deployed honeypot infrastructure rather than relying solely on passive community reports. Despite the high volume of reports, the confidence score sits at 63%, suggesting that while the threat is well-documented, some attributional uncertainty remains regarding the full scope or ultimate intent of the campaign. The zero activity frequency rating may indicate that the most aggressive phase of activity has subsided, though the historical report volume remains a significant concern for IP reputation databases.
The dominant threat category, hacking activity, encompasses a broad range of intrusion techniques including exploitation attempts against known vulnerabilities, credential-based attacks, and unauthorized access probing. For network operators with exposed services, this classification signals that the source address has been actively engaged in reconnaissance and exploit delivery targeting specific software weaknesses. The concentrated report volume within a single month suggests a coordinated, systematic scanning or exploitation campaign rather than opportunistic, random probing.
Site operators should immediately block IP 103.220.207.174 at the firewall level given its critical threat rating and extensive abuse history. Implementing rate-limiting on authentication endpoints and enforcing strong password policies will reduce the effectiveness of any credential-based intrusion attempts. Deploying fail2ban or equivalent automated banning tools can provide real-time defense by dynamically blocking repeat offenders. Finally, ensuring all exposed software remains current with security patches eliminates the vulnerabilities most commonly targeted by this category of attack.
SC 
HK