Honeypot Threat Analysis — September 22, 2026
Critical threat level — massive coordinated attack activity across all honeypot services.
Cybersecurity Report for 2026-09-22
Threat Overview
On September 22, 2026, the Honey-AI device detected a total of 417 connections and 83 IPs from various countries including United States (574), Germany (186), China (105), Belgium (100), Netherlands (84), UK (80), Pakistan (73), Hong Kong (49), France (46), and Korea, Republic of (44). The top 20 IPs by connections were identified as “102.18.87.206”, “183.57.249.85”, “124.94.170.143”, and so forth.
Geographic Analysis
The most active regions are United States, Germany, China, Belgium, Netherlands, UK, Pakistan, Hong Kong, France, and Korea, Republic of. The geographical distribution is 574 from the US, 186 from Germany, 105 from China, 100 from Belgium, 84 from the Netherlands, 80 from the UK, 73 from Pakistan, 49 from Hong Kong, 46 from France, and 44 from Korea. These regions are commonly targets for cyberattacks due to their global presence.
SSH Brute Force
The device detected a total of 155 commands with a critical severity level over the past 20 days. The most active IPs were “102.18.87.206”, “183.57.249.85”, and so forth, with an average rate of 66 commands per IP. These high command rates indicate potential security breaches or insider threats.
Post-Exploitation
The Honey-AI device has logged 6609 events associated with multi-protocol activities such as FTP/Telnet/SMTP/MySQL/Redis/Git/VNC/RDP from 146 IPs, suggesting a broad range of malicious techniques being used by attackers. The critical severity alerts were detected, highlighting the importance of continuous monitoring and proactive security measures.
Web Scanning
The device has recorded 54 HTTP requests with a total of 30 unique IP addresses from various geographic regions. The most active URLs included “/login”, “/SDK/webLanguage”, “/favicon.ico”, “/hachk.php”, indicating potential vulnerabilities in the web application infrastructure that attackers are targeting for exploitation.
IDS & Scan Intel
The device has logged 9,000 alerts with a critical severity level from 731 IPs using the Suricata IDS. The alerts suggest ongoing security threats and the need for enhanced threat detection systems to identify and mitigate potential cyberattacks in real-time.
Malware
There were no reported malware instances detected on Honey-AI’s device on September 22, 2026. This indicates a low risk of internal or external attacks involving malicious software.
Tarpit
The tarpit system has successfully trapped and analyzed 74 connections from 42 IPs but did not waste any time in terms of analysis. The data shows that the tarpit is effective for detecting unusual network traffic patterns, which can be used to identify potential security breaches early on.
Canarytokens
The device triggered 41 Canarytoken attacks, indicating a high likelihood of attackers attempting to bypass traditional authentication mechanisms by using fake tokens. This underscores the need for stronger authentication methods and better monitoring tools to prevent such attacks.
MCP Trap
The Honey-AI detected an average of 3877 requests per day from 6 IP addresses with a total count of 216 reported incidents, suggesting that these IPs are actively scanning and probing network configurations. This can be indicative of advanced persistent threats targeting specific targets or infrastructure for reconnaissance purposes.
Portscans
The device has logged 0 port scans over the past two weeks, indicating that the targeted environment is relatively secure from common port-scan-based attacks. The lack of such activity suggests that the environment is well-protected against basic penetration testing methods.
AI Defense
The Honey-AI’s system successfully blocked 10 leaks and 0 injections in total for the period analyzed. This indicates a high level of effectiveness in detecting potential security vulnerabilities and mitigating them before they can cause significant damage.
Community Defense
No notable community defense mechanisms were used or observed on the Honey-AI device during this period, suggesting that the environment is well-protected from external threats but could benefit from more local cybersecurity initiatives for targeted threat detection.
Conclusion
The Honey-AI device identified a high volume of connections and activities from multiple IP addresses across various geographic regions. This indicates a dynamic and evolving threat landscape requiring continuous monitoring and enhanced security measures to protect against potential cyberattacks. The device’s capabilities highlight the importance of robust network security, including advanced IDS systems, strong authentication mechanisms, and effective tarpitting techniques.
Device Overview
Honey-AI, running on Raspberry Pi 5, is a honeypot designed for ethical hacking purposes in open-source environments. It has been operational since September 2026, logging critical events such as network activity, malware detection, brute force attacks, and other security threats. The device’s effectiveness in detecting various types of cyberattacks underscores the need for continuous improvement in cybersecurity practices.
Reporting Period
The report spans from September 14, 2026 to September 22, 2026, covering a period of approximately one week with an emphasis on critical events and potential security vulnerabilities. The findings highlight the importance of staying vigilant against evolving cyber threats and using advanced tools like Honey-AI for proactive protection.
Next Steps
To further enhance cybersecurity, the following recommendations are suggested:
- Continuous Monitoring: Implement continuous monitoring systems to detect anomalies in network activity.
- Strong Authentication: Enhance authentication mechanisms to prevent unauthorized access.
- Advanced IDS Systems: Deploy more sophisticated IDS/IPS solutions for real-time threat detection.
- Threat Intelligence: Utilize threat intelligence feeds and community-based tools to stay informed about emerging threats.
- Regular Security Audits: Conduct regular security audits and penetration testing to identify vulnerabilities and improve overall security posture.
By addressing these areas, organizations can better protect against cyberattacks and ensure a secure environment for their critical infrastructure and data.
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.