Honeypot Threat Analysis — June 19, 2026
Critical threat level — massive coordinated attack activity across all honeypot services.
2026-06-19 Analysis Report
On June 19th, the cybersecurity analyst at honey-ai.dev encountered a significant influx of activity on their Raspberry Pi honeypot in Spain. This period marked by an unusually high number of connections and commands, coupled with multiple reported attacks and vulnerabilities, necessitates careful analysis.
Threat Overview
The day began with 724 SSH connections from 472 IPs, followed by 98 distinct command executions across various protocols including FTP, Telnet, SMTP, MySQL, Redis, Git, VNC, RDP. The number of critical IDS alerts (8196) indicates the severity of the threats encountered, with a total of over 207 attackers.
Geographic Analysis
The most prolific attacks originated from United States (368 IPs), China (268 IPs), Singapore (85 IPs), India (78 IPs), United Kingdom (68 IPs), Germany (67 IPs), Belgium (64 IPs), Netherlands (61 IPs), Pakistan (59 IPs), and Korea, Republic of (56 IPs). This geographical distribution underscores the global nature of cyber threats.
Top Threats
The majority of attacks were characterized by multiple protocols such as FTP/Telnet/SMTP/MySQL/Redis/Git/VNC/RDP. The critical IDS alerts indicate significant security vulnerabilities that have been exploited. The detailed list of HTTP paths reveals targeted endpoints, including ones for password reset and other sensitive operations.
Command Execution Details
The commands executed were diverse in nature but often involved manipulation of system files or directories to gain unauthorized access. For instance, the use of cat /proc/cpuinfo combined with grep name highlighted potential hardware information extraction. The command /bin/./uname -s -v -n -r -m suggested that this was a targeted operation aimed at identifying the operating system version.
Malware Detection
There were no malware incidents detected during the period, indicating that the honeypot had successfully identified the nature of the threats but could not capture any malicious payloads. This is significant in understanding the level of sophistication and intent behind these attacks.
Tarpit Analysis
A notable event was the trapping of 6 connections from 5 different IP addresses, which would have been otherwise open to further exploitation if not for this intervention. The tarpitting technique effectively slowed down potential attackers, preventing them from completing their intended activities.
Malware Tokens
The day’s events included a series of tokens used by Boto3 and Python users, indicating the presence of compromised or misconfigured systems within the network. This suggests that there is room for improvement in user education regarding security best practices.
MCP Trap Analysis
There were 3 requests from an IP address with suspicious activity flagged by the MCP trap tool, which did not result in any malware capture but was a crucial detection mechanism in identifying potential intrusions. The fact that no malware was captured underscores the importance of continuous monitoring and updating of threat intelligence databases.
Portscans & AI Defense
The absence of port scans (0/0) and injections blocked (0 injection, 0 leak) indicates robust security measures in place. This suggests a well-managed environment with adequate defenses against common attack vectors.
Community Defense
Given the high volume of threats encountered, it is essential to maintain open communication channels with community members for updates on threat trends and best practices. The blog post serves as a valuable resource for sharing insights from this honeypot experience.
In conclusion, while the day was marked by significant activity, the analysis reveals both an urgent need for continuous improvement in security measures and a robust defense system that effectively identified and mitigated threats during this period. This underscores the importance of staying vigilant against evolving cyber threats and adapting security strategies accordingly.
Pi5/Spain/open-source
This report is based on real-world data collected by honey-ai.dev’s Raspberry Pi 5 honeypot in Spain, capturing a range of critical indicators that highlight both proactive measures taken and ongoing challenges.
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.