Honeypot Threat Analysis — July 6, 2026
Critical threat level — massive coordinated attack activity across all honeypot services.
Cybersecurity Analysis of 2026-07-06
Overview:
The honeypot system maintained by honey-ai.dev on a Raspberry Pi 5 in Spain encountered a significant increase in activity and threats over the past day, with 206 attackers from various geographical locations. The top IPs were identified as “95.79.26.121,” “123.169.208.166,” “65.109.125.86,” “213.209.159.115,” and “91.92.40.10.” The most common passwords were 8c6976e5b5410415, indicating a lack of strong password policies.
Threat Overview:
The day’s attack patterns highlighted several significant threats:
- SSH Brute Force: 1157 connections attempted, with 555 successful logins. This indicates that users may be unaware of the need for secure passwords and proper access controls.
- HTTP Scans: 28 unique IPs made HTTP requests, possibly probing the system’s availability or attempting to find vulnerabilities.
- IDS Alerts: The Honey Pot detected 9839 alerts from a total of 589 IPs, with critical severity. This suggests that the IDS is effectively monitoring and responding to threats.
Geographic Analysis:
The top five countries identified by the honeypot are United States (1012), China (502), Belgium (202), Pakistan (164), and Netherlands (162). The honeypot system has been effective in tracking these locations, suggesting that the threat actors may be attempting to bypass traditional security measures.
SSH Brute Force:
The day saw 1157 connections attempted via SSH. Of these, 555 were successful, indicating a high volume of users who are not practicing good security hygiene or using strong passwords.
Post-Exploitation Activities:
Post-exploitation activities such as changing system settings (e.g., locking .ssh directory) and gaining temporary access through TTY commands suggest that attackers may have gained unauthorized access to the honeypot.
Web Scanning:
The honeypot received 142 unique HTTP requests, which could indicate probing for vulnerabilities or seeking out services on the network. The presence of specific paths like “/dispatch.asp,” ”/”, and “/SDK/webLanguage” suggests a targeted approach towards finding exploitable points on the system.
IDS & Scan Intel:
A total of 9839 alerts were detected by Honey Pot’s Intrusion Detection System, with critical severity. This high alert count indicates that the honeypot is successfully detecting threats but may need to be enhanced for better situational awareness and response.
Malware:
There was no malware activity recorded on this day, which suggests a focus on exploiting vulnerabilities rather than deploying malicious payloads.
Tarpit:
The honeypot did not trap any connections due to tarpitting, indicating that the threat actors were using legitimate methods (e.g., legitimate HTTP requests) to bypass detection. This is a strength of the honey pot system but also highlights the need for continuous improvement in the IDS and network defenses.
Canarytokens:
Two types of “canarytokens” were identified: AWS tokens from unknown, user-agent strings with Go-http-client/1.1, and an example from 66.154.119.224 (user-agent: Go-http-client/1.1). This suggests that there is a need to enhance the defense against known threats and potential reconnaissance techniques.
MCP Trap:
The honeypot did not trap any sessions due to multiple reasons including legitimate HTTP requests, which are common in network environments. However, it still does not indicate any tarpitting or other unusual behavior patterns.
Portscans:
No portscans were detected, suggesting that the system’s default settings and security measures have effectively blocked these types of attacks.
AI Defense:
There was no injection blocking or leak detection activity recorded on this day, indicating a lack of effective countermeasures against common web application vulnerabilities.
Community Defense:
Given the high volume of threats and the presence of multiple attack patterns (SSH brute force, HTTP probing), it is important to communicate with the community and security experts for better threat intelligence sharing and improved defense strategies. This can include regular updates to IDS, enhanced monitoring systems, and collaboration with other honeypot operators.
Conclusion:
The honeypot system demonstrated a high level of effectiveness in detecting threats, but continued improvements are needed in areas such as malware detection, tarpitting protection, and better community engagement for threat intelligence sharing. This analysis provides valuable insights into the current security posture and highlights the importance of continuous monitoring and defense strategies.
Pi5/Spain/open-source
This concludes the cybersecurity analysis for 2026-07-06 on the honeypot system at honey-ai.dev, focusing on various attack patterns and defenses.
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.