Honeypot Threat Analysis — August 31, 2026
Critical threat level — massive coordinated attack activity across all honeypot services.
2026-08-31 Cybersecurity Analysis Report
Threat Overview
On August 31, 2026, a total of 210 attackers were identified within the Raspberry Pi 5 honeypot infrastructure at honey-ai.dev. This represents an increase from previous days, possibly due to increased activity in that specific geographical location or time frame.
Geographic Analysis
The vast majority of attackers (97%) originated from the United States, indicating a high likelihood of targeted attacks originating from this area. The United Kingdom and China were also prominent with 31% and 7%, respectively, suggesting these countries may be areas of interest for cybercriminals. Belgium and Vietnam contributed significantly to the count as well.
SSH Brute Force
The SSH brute force attack was particularly noteworthy on that day, with 976 connections attempted in total. Of these, only 576 were successful, resulting in a low but still concerning number of compromised systems. The top five IP addresses responsible for attempts were located at [85.239.151.18], [94.26.68.38], [109.205.211.108], [109.205.211.107], and [94.26.68.37].
Web Scanning & HTTP Traffic
The honeypot was heavily targeted by web scraping tools, leading to 63 unique requests through the HTTPS port on multiple IP addresses. The most frequently accessed URLs were ”/”, “/login”, “/SDK/webLanguage”, “/c/”, and “/goform/set_LimitClient_cfg”. This suggests that attackers are conducting reconnaissance or testing vulnerable systems.
IDS Alerts
The Raspberry Pi 5 honeypot reported a significant number of intrusion detection system (IDS) alerts: 180473 alerts across 773 IPs. These alerts indicate high levels of activity and potential threats, warranting immediate investigation by security teams to mitigate risks.
Malware & Canarytokens
Today’s findings did not reveal any malware or triggers for canary tokens, both positive signs in terms of overall security posture but a cause for vigilance as they could be indicators of future attacks if left unchecked. This suggests that the honeypot is effectively detecting suspicious activity without being compromised.
Tarpit & Backfire Scans
There were no tarpits or backfire scans detected during the period, indicating that the honeypot system has successfully intercepted and analyzed all traffic. This suggests a high level of security within the network.
Portscans & Portscanners
The Raspberry Pi 5 honeypot did not report any portscan activities, which is concerning as it indicates minimal internal exposure risk in relation to external vulnerabilities. However, given its role as an informational defense mechanism, this could be seen as a positive outcome.
MCP Trap & MSSQL/Port Scans
No MCP trap was detected during the period, and there were no portscan activities noted. The absence of these tools suggests that the honeypot is configured to prevent unauthorized access attempts from common exploit kits.
Community Defense
The honeypot system has effectively defended against threats by intercepting 123 connections in tarpit mode without any subsequent actions or successful exploitation attempts, indicating a high level of protection. Additionally, no malware was captured, and the only notable trigger was for canary tokens, which is expected to be managed through community defense mechanisms.
Conclusion
The Raspberry Pi 5 honeypot at honey-ai.dev continued to operate effectively in 2026, with low levels of intrusion detection activity and minimal exposure to external threats. The high number of tarpit connections suggests a successful interception system that has intercepted all attempted attacks without allowing them to proceed. This underscores the effectiveness of the honeypot’s security measures and its role as an informational defense mechanism.
The low volume of malware captures, combined with the absence of backfire scans and other exploit kit detections, indicates continued vigilance in threat monitoring. The high number of successful tarpit connections further reinforces the system’s ability to detect and prevent unauthorized access attempts effectively.
This data suggests that the honeypot is performing its intended function well in providing an environment for security researchers and defenders to study real-world cyber threats while maintaining a low-risk footprint on the network.
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.