Honeypot Threat Analysis — June 20, 2026
Critical threat level — massive coordinated attack activity across all honeypot services.
Threat Overview
As of June 20th, 2026, the honey-ai.dev honeypot in Spain has encountered a significant surge in malicious activity. This period saw an influx of 135 attackers attempting to gain unauthorized access or perform reconnaissance on the honeypot. The primary threat vectors included SSH brute force attacks and HTTP requests.
SSH Brute Force
SSH connections from multiple IP addresses were attempted, with a notable spike on June 20th at 423 login attempts over 292 hours. This indicates an ongoing attack pattern where attackers are repeatedly attempting to gain access via SSH without proper authentication mechanisms in place.
HTTP Requests
The honeypot experienced a substantial increase in HTTP traffic from various IPs, with 40 requests logged out of 8 IPs. The specific paths accessed include /SDK/webLanguage, /cgi-bin/luci/;stok=/locale, and others that suggest potential reconnaissance against the honeypot’s services.
IDS & Scan Intel
The Honey-ai Dev honeypot experienced a high volume of alerts from Suricata Intrusion Detection System, with 7051 critical events logged out of 552 IPs. This indicates an active network scanning and testing environment where attackers are probing the capabilities of the honeypot’s services.
Malware
There were no malware samples captured during this period, which is consistent with the lack of previous reports from AbuseIPDB. The absence of malware suggests that the primary threat was focused on gaining unauthorized access rather than executing malicious payloads.
Tarpit & Backfire Scans
Of note are 11 tarpits and backfire scans attempted against various IP addresses in Spain, with a particular focus on United States targets (64.62.197.x) and Belgium targets (45.8.132.114). These scans suggest ongoing reconnaissance efforts by attackers looking to identify vulnerabilities or probe the capabilities of specific network segments.
MCP Trap & Portscans
The honeypot received 3 requests from a single IP address using Boto3 library, indicating an attempt at port scanning but with no further data captured. This suggests that while these scans were initiated, they did not result in any additional information being logged or acted upon.
AI Defense
Despite the presence of malicious activity, there was no evidence of artificial intelligence-based defenses being breached during this period. The absence of such defenses is consistent with a traditional honeypot environment where machine learning and AI techniques are generally not expected to be compromised by standard hacking tools.
Community Defense
There were no community defense mechanisms in place on the honey-ai.dev system that could have detected or prevented any of these attacks. This underscores the effectiveness of the honeypot as a deterrent for attackers looking to test its capabilities.
Conclusion
As of June 20th, 2026, the honey-ai.dev honeypot in Spain encountered an overwhelming influx of threats from multiple IP addresses attempting to gain unauthorized access or perform reconnaissance. The success rate was relatively low at 135 attackers out of a total potential attack volume, indicating that while the system is effective as a deterrent for traditional hacking techniques, it may not be entirely immune to sophisticated actors using other methods.
The analysis highlights the importance of maintaining robust defenses against both known and emerging threats in network security environments. The honey-ai.dev honeypot continues to serve an important role in testing and improving security measures across various industries and sectors.
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.