Honeypot Threat Analysis — July 31, 2026
Critical threat level — massive coordinated attack activity across all honeypot services.
Cybersecurity Analysis: 2026-07-31
Threat Overview
As of July 31, 2026, the honey-pot honeypot setup on a Raspberry Pi 5 in Spain experienced an influx of approximately 181 unique attackers. This period marked a significant increase in network activity and security threats against the system.
SSH Brute Force
The most critical threat identified during this analysis was the SSH brute force attempts. A total of 1347 connections were logged, with over 867 commands executed across these sessions. The overwhelming majority (90%) of these users attempted to access the default username “admin” or “root,” indicating a common exploitation method.
Multi-Protocol Activity
The presence of multiple protocols was evident in this period, with a total of 24422 events logged across various services including FTP, Telnet, SMTP, MySQL, Redis, Git, VNC, and RDP. This diversified activity suggests that the honeypot is attracting users from different backgrounds and using varying attack methods.
HTTP Activity
HTTP requests were also detected in significant numbers, with 165 unique requests captured over two days of observation. Users accessed various resources on the honeypot through well-known paths such as “/login”, “/SDK/webLanguage”, “/goform/set_LimitClient_cfg”, and “/v2/_catalog”. This indicates that even authenticated users were attempting to access unauthorized pages.
IDS Alerts
The Suricata Intrusion Detection System (IDS) generated 28962 alerts, highlighting the sophisticated nature of the attackers. These alerts included critical events such as brute force attempts and potential login failures, suggesting a constant threat environment around the honeypot.
Geographic Analysis
The geographic distribution of attackers was predominantly from the United States, with 184 (28%) connections originating from this country. Followed closely by the United Kingdom (59%), China (47%), Germany (31%), Belgium (27%), Netherlands (25%), Pakistan (20%), Turkey (18%), and Vietnam (15%). The presence of attackers from multiple countries underscores the global nature of cyber threats.
SSH Brute Force
The most active session was identified as a brute force attack, attempting to gain unauthorized access through default usernames. This method is common in phishing attempts where users unknowingly provide their credentials due to poor security practices or curiosity about the system’s default configuration.
Post-Exploitation Tools
Multiple post-exploitation tools were detected, including “ssh-rsa AAAAB3NzaC1yc2EAAAABJQAAAQEAr20x: /bin/./uname -s -v -n -r -m” and “cat /proc/cpuinfo grep name wc -l”. These tools indicate that attackers are attempting to gather information about the system’s architecture, which could be used for further exploitation or data exfiltration.
Web Scanning
Web scanning was also a significant activity detected during this period. The honeypot received 165 unique HTTP requests over two days of observation. Users accessed various resources on the honeypot through well-known paths such as “/login”, “/SDK/webLanguage”, “/goform/set_LimitClient_cfg”, and “/v2/_catalog”. This suggests that the honeypot is a useful tool for identifying vulnerabilities in systems.
IDS & Scan Intel
The Suricata IDS system generated 28962 alerts, indicating a high level of activity around the honeypot. These alerts included critical events such as brute force attempts and potential login failures, highlighting the need to continuously monitor and improve security protocols.
Malware Capture
No malware was detected during this period, which is somewhat concerning given that the system has been operational for over 10 months. The lack of malware suggests that the honeypot may be running a less aggressive detection mechanism or that attackers are not targeting known malicious payloads.
Tarpit
Despite the presence of multiple connections being trapped due to tarpitting, no significant downtime was reported as a result of this activity. This indicates that the system’s defenses were effective in preventing further attacks and providing a stable environment for analysis.
Canarytokens
Two triggers were recorded with AWS tokens from different IP addresses, including 213.163.202.89 (user-agent: [aws-sdk-go-v2/1.43.2 ua/2.1 os/linux lang/go#1.25.1 md/GOOS#linux md/GOARCH#amd64 api/s3#1.106.2 m/E,e]). This suggests that the system was successfully captured and is being monitored for further security threats.
MCP Trap
The MCP trap did not generate any requests or activity during this period, indicating a lack of engagement from potential attackers who may have been monitoring the honeypot’s response to various attacks.
Portscans
No port scans were detected during this analysis period. This suggests that the system is effectively filtering out common scanning methods and maintaining a secure environment for its users.
AI Defense
The security measures in place, such as AI defense, did not block any injection or leak attempts, indicating that these tools are effective at preventing known security vulnerabilities from being exploited.
Community Defense
Given the nature of the analysis data, no additional community defense rules were necessary. The provided information is sufficient for analyzing and understanding the threats facing the honeypot system.
Conclusion
The 2026-07-31 period saw a significant increase in network activity around the honey-pot honeypot setup on a Raspberry Pi 5 in Spain, with approximately 181 unique attackers. The primary threat identified was SSH brute force attempts, followed by multi-protocol and HTTP activities.
The lack of malware detection is concerning but does not suggest a serious security breach. The system’s defenses are effective in preventing further attacks, as evidenced by the successful tarpitting of connections and the absence of any reported downtime or system instability.
Moving forward, it is recommended to continue monitoring the honeypot for new threats and vulnerabilities, implementing additional security measures where necessary, and staying updated with the latest cybersecurity trends and best practices.
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.