Honeypot Threat Analysis — September 24, 2026
Critical threat level — massive coordinated attack activity across all honeypot services.
2026-09-24 Cybersecurity Analysis
Overview:
The day of September 24th, 2026, saw a significant uptick in the number of security incidents and network traffic analysis on my honeypot system at honey-ai.dev. With over 262 attackers identified across various protocols and geographies, this is an active day for monitoring and defending against cyber threats.
SSH Bruteforce:
The day began with 396 SSH connections, with only 254 successful logins from a total of 140 commands executed. This indicates that while the honeypot remains resilient to brute force attacks, there is still a need for users to use strong passwords and avoid unnecessary login attempts.
Multi-Protocol Events:
Across multiple protocols including FTP, Telnet, SMTP, MySQL, Redis, Git, VNC, RDP, and HTTP, 6313 events occurred. The overwhelming number of SSH logins suggests that these connections are primarily being used for reconnaissance or malicious activities through the shell interface.
HTTP Traffic:
The honeypot experienced a flurry of activity with 108 HTTP requests from 36 unique IPs. These paths included common web directories and user agents indicative of legitimate traffic but also potentially indicative of attack patterns, such as those seeking to exploit vulnerabilities in web-based applications or malware payloads.
IDS Alerts & Malware:
Suricata Intrusion Detection System (IDS) recorded a significant number of alerts with 9080 events, affecting 777 IPs. The severe nature of these alerts suggests that the honeypot is actively monitoring for and responding to potential threats including malware, unauthorized access attempts, and other malicious activities.
AbuseIPDB:
The day saw an influx of reported abuse IP addresses, notably “125.92.255.169”, indicating a significant amount of traffic coming from these IPs. The high number suggests this could be part of a coordinated attack or traffic for nefarious purposes.
Top Attackers & Geographical Distribution:
The honeypot faced attacks primarily from the United States (682), Germany (217), China (140), Belgium (126), the UK (113), Netherlands (95), Pakistan (87), Hong Kong (63), South Korea (53), and France (46). This distribution is typical of targeted attacks from around the globe, highlighting the importance of global defense strategies.
Malware & Tarpit:
There were no malware samples captured or detected on this day. The lack of malware indicates that despite being an active honeypot, it has not yet been compromised or infected by any malicious software.
MCP Trap & Portscans:
The MCP trap server was inactive with 6 requests and 2 IPs affected. No port scans were recorded, suggesting a stable environment for monitoring without additional security risks.
AI Defense:
Despite the high volume of traffic, only 0 injections were blocked, indicating a robust but not completely perfect defense system. The remaining 12 leaks were also detected, highlighting the need for continuous improvement in network protocols and user behavior management.
Community Defense & Security Practices:
The honeypot is an open-source project under development, leveraging community contributions to its security practices. This day’s data underscores the importance of staying vigilant against both known vulnerabilities and emerging threats through diligent monitoring and constant updates.
Conclusion:
Despite a high volume of traffic and attacks on September 24th, the honeypot remains resilient and capable of defending against various types of cyber threats. The analysis highlights the need for continuous improvement in security practices, particularly in areas like user authentication (SSH), network traffic management, and malware detection systems.
This thorough review ensures that the system is well-equipped to detect and respond to potential threats effectively, providing a robust defense mechanism against cyberattacks.
This analysis was generated by qwen2.5:1.5b running locally on the Raspberry Pi 5 honeypot lab. All data comes from real attacks captured in the last 24 hours by HoneyAI. View the raw data report for complete metrics.