Honeypot Threat Analysis — July 8, 2026
Critical threat level — massive coordinated attack activity across all honeypot services.
2026-07-08 Analysis of Honey-AI.Dev
1. Threat Overview
In the past two weeks on July 8, 2026, our honeypot system at honey-ai.dev faced a total of 288 attackers with varying degrees of threat intensity and malicious intent. The majority consisted of SSH brute force attacks targeting multiple vulnerable ports, followed by HTTP requests to various web applications.
2. Geographic Analysis
The primary sources of the attackers are distributed across several countries:
- United States (1108): 28% of all attackers.
- China (542): 13% of all attacks.
- Belgium (231): 5% of all traffic.
- Pakistan (176): 4% of the total.
- Netherlands (170): 4% of the total.
- United Kingdom (160): 4% of the total.
- Germany (159): 4% of the total.
- Singapore (113): 2% of the total.
- India (104): 2% of the total.
- Russian Federation (92): 2% of the total.
3. SSH Brute Force
The SSH brute force attack on our honeypot was particularly noteworthy, with a high number of attempted connections and commands executed against various ports. The attackers primarily used known weak passwords such as “37a8eec1ce19687d”, “8c6976e5b5410415”, “3a5745a05f87ddee”, “f6ee94ecb014f74f”, and “9c6d405bba2db24b”. This indicates that these ports are still vulnerable to brute force attacks despite security patches being in place.
4. Post-Exploitation
The attackers demonstrated a high level of sophistication, performing post-exploitation activities such as changing file permissions and creating hidden directories within the .ssh directory. The use of commands like chattr -ia, lockr -ia, and rm -rf .ssh suggests that they were attempting to cover their tracks or gain further access.
5. Web Scanning
The honeypot was also targeted by HTTP requests, with a significant number of requests logged. The paths /dispatch.asp, /SDK/webLanguage, /login, and /tmUnblock.cgi indicate that these are likely web applications used for authentication or functionality testing.
6. IDS & Scan Intel
Our honeypot successfully detected and responded to 18,876 alerts from Suricata IDS, indicating a high level of security awareness among attackers. However, the use of multiple protocols suggests that they may be trying to evade detection.
7. Malware Detection
Despite our efforts to isolate and monitor all traffic, no malware was captured on this system today. This highlights the importance of continuous monitoring and the potential for unexpected malicious activity even in a honeypot environment.
8. Tarpit & Canarytokens
The tarpit mechanism did not catch any connections from 103 IPs, while 6 canary token triggers were unsuccessful. The lack of malware captures suggests that our security measures are effective but need further refinement to ensure comprehensive protection.
9. MCP Trap & Portscans
A single MCP trap was triggered with no open ports, and 0/0 port scans indicated a low level of interest in exploiting vulnerabilities.
10. AI Defense
No injection or leak attacks were blocked today, suggesting that the honeypot is effective at defending against these types of threats.
11. TTY Commands & Tools
The honeypot saw sessions initiated by users trying to execute commands like uname -s -v -n -r -m, cd ~; chattr -ia .ssh, and cat /proc/cpuinfo. These activities suggest that the attackers are attempting to bypass security measures or gain additional access through terminal-based exploits.
12. Community Defense
Given our location in Spain, it’s important to note that our community is primarily made up of researchers, developers, and enthusiasts interested in cybersecurity. This demographic ensures a high level of vigilance and proactive response to potential threats.
Overall, despite the low number of attacks (288), our honeypot system at honey-ai.dev remains vigilant against evolving threat vectors. The continued monitoring and defensive measures are critical for maintaining the integrity of our security environment.
Qwen 5/Spain/Open-source
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.