Honeypot Threat Analysis — September 12, 2026
Critical threat level — massive coordinated attack activity across all honeypot services.
Cybersecurity Analysis for 2026-09-12
Overview
Today’s threat analysis on the Raspberry Pi 5 honeypot in Spain reveals a significant number of attackers targeting SSH and HTTP services. The overall incident count is high, with critical threats detected by Suricata IDS, indicating that the environment remains vulnerable despite its defensive measures.
Geographical Analysis
The report highlights the top geographical locations where the majority of attacks originated:
- United States: 743 (33%)
- Germany: 214 (9%)
- Belgium: 153 (6%)
- Netherlands: 148 (6%)
- China: 140 (6%)
- United Kingdom: 137 (6%)
This geographical distribution suggests that the honeypot is being used to test security measures in various international environments.
Top IPs and Passwords
The list of top attackers includes:
- IPs: [“85.85.17.46”, “109.205.211.94”, “185.212.251.140”, “80.94.92.55”, “77.90.185.30”]
- Passwords: [“neron”, “zXJl@mwZ”, “t00r!@!”, “740316”, “vice”]
The high number of attacks indicates that SSH and HTTP services are still insecure, especially with default or weak passwords.
HTTP Paths
The most common paths accessed by attackers include:
- ”/”
- “/SDK/webLanguage”
- “/login”
- “/favicon.ico”
- “/judge”
These paths suggest potential exploitation points for further attacks, such as login pages and favicon download.
Tarpit Analysis
Despite attempting to trap 83 connections from 56 IPs, only 0h of tarpitting was wasted. This indicates that the honeypot’s defenses are effective in intercepting external traffic but not necessarily its internal tarpits.
Malware Detection
No malware has been captured today, suggesting a low threat level for this specific environment.
Canarytokens and AWS Tokens
The report includes information on two unknown AWS tokens:
- Token from 172.58.54.130: User-agent: Boto3/1.40.72 md/Botocore#1.40.72 ua/2.1 os/linux#7.0.0-15-generic md/arch#x86_64 lang/python#3.14.4 md/pyimpl#CPyt…
- Token from 172.58.54.130: User-agent: Boto3/1.40.72 md/Botocore#1.40.72 ua/2.1 os/linux#7.0.0-15-generic md/arch#x86_64 lang/python#3.14.4 md/pyimpl#CPyt…
MCP Trap and Portscans
No suspicious backfire scans or portscans have been detected, indicating that the environment is not actively being probed by attackers.
Portscans and MSSQL/Port Scans
The report mentions no suspicious portscans or MSSQL traffic, suggesting a low detection rate for these types of threats.
AI Defense Analysis
No injection attacks were blocked, but 8 leak attempts were detected. This indicates that while the honeypot is effective in defending against common injection-based attacks, it still faces challenges in preventing more sophisticated methods.
Community Defense
The report concludes with a note on ongoing efforts to improve community defense practices: “Continued vigilance and improvement of security protocols are essential for protecting such environments.”
Overall, this analysis underscores the importance of continuous monitoring and updates in cybersecurity measures. The findings highlight the need for organizations to regularly review their honeypot setups and adapt defensive strategies accordingly.
By providing a detailed breakdown of these metrics and analyzing them against potential attack vectors, we can identify areas where improvements are needed to enhance security while continuing to refine our defense mechanisms effectively.
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.