Saturday, 10 October 2026 💀 critical 🤖 qwen2.5:1.5b

Honeypot Threat Analysis — October 10, 2026

Critical threat level — massive coordinated attack activity across all honeypot services.

🌍 194 unique attackers ⚡ 22,565 events 📊 View raw data report →
ssh-brute-forcehoneypotweb-scanningmulti-protocolhigh-severitymcp-agent-trapthreat-intelligence

2026-10-10 Honey-ai.dev Security Report

Overview: As of October 10, 2026, the Honey-ai.dev honeypot was under continuous surveillance and analysis by cybersecurity experts. The system recorded a total of 194 attackers who attempted to breach the network via SSH, HTTP, FTP, Telnet, SMTP, MySQL, Redis, Git, VNC, RDP, and various web applications. The attacks were characterized by high severity with 8422 alerts generated by Suricata IDS system.

Threat Analysis:

  • SSH Brute Force: The honeypot received the highest number of SSH attempts, amounting to 167 connections from 22 commands. This indicates that the network is likely being targeted by brute force attacks.

  • HTTP Scanning: HTTP traffic was also significant with 39 requests originating from 104 unique paths and a total of 133 IPs involved.

  • IDS Alerts & Malware: Despite an absence of malware detection, Suricata IDS system generated 8422 alerts, indicating that the honeypot is effective in detecting potential threats. The severity level was critical in most cases (85% of all alerts).

Security Practices and Defenses:

  • Threat Overview & Geographic Analysis: The geographical distribution of attackers shows significant activity from United States (1442), China (401), Germany (365), the United Kingdom (295), Belgium (290), Pakistan (238), Netherlands (193), Korea, Republic of (145), Hong Kong (140), and India (138). This distribution suggests a global network approach to security breaches.

  • SSH Brute Force: The high number of SSH attempts indicates that the honeypot is effective in detecting brute force attacks. The use of strong authentication mechanisms, such as public key-based encryption, significantly reduces this risk.

  • IDS & Scan Intel: Suricata IDS system generated 8422 alerts, indicating a robust monitoring mechanism for potential threats. However, despite generating alerts, no malware was captured today.

Community Defense:

  • Canarytokens: The honeypot had six triggers set up to detect and respond to suspicious activities, with no malicious activity recorded.

  • MCP Trap & TTY Commands: Two tarpit connections were established, indicating that the honeypot is designed to intercept and analyze incoming traffic. Additionally, 41 sessions involving TTY commands were observed.

Tools & Techniques:

  • Tarpit Toolkits: The use of tools like Go-http-client/1.1 and Boto3/1.43.70 was noted, suggesting that attackers are using various libraries to automate penetration testing or security assessments.

  • MSSQL Scanner: 1845 connections were made for MSSQL scanning, indicating an active interest in exploiting known vulnerabilities.

Conclusion:

The Honey-ai.dev honeypot has demonstrated its effectiveness in detecting and responding to a wide range of cyber threats. The high number of attackers suggests that the network is being used as part of a larger security testing or penetration exercise rather than for malicious intent. Continuous improvement in security measures, including stronger authentication methods, robust IDS systems, and comprehensive threat detection mechanisms, will help maintain the effectiveness of such honeypot setups.

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.

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This analysis was generated by qwen2.5:1.5b running locally on the same Raspberry Pi 5 that operates the honeypots. No data leaves the device. All threat data is sourced from real attacks captured in the last 24 hours.

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