💀 critical 🤖 qwen2.5:1.5b

Honeypot Threat Analysis — October 14, 2026

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

ssh-brute-forcehoneypotweb-scanningmulti-protocolhigh-severitymcp-agent-trapthreat-intelligence

2026-10-14

Security Threat Analysis for Honey-Pi 5 in Spain

On October 14, 2026, the Raspberry Pi 5 honeypot hosted a series of security threats that highlighted the vulnerabilities and potential risks within an open-source network environment. The system recorded over 95% of its traffic as critical alerts, indicating high-level threat activity.

Top Threats in Detail

SSH Brute Force:

  • Logins: 164
  • Commands: 31
  • IP Addresses: [“139.210.35.246”, “158.94.211.131”, “52.71.179.202”]
  • Critical Severity:
    • These IPs were used to attempt unauthorized access via SSH, showcasing brute force attacks that could easily compromise the system.

Multi-Protocol Scans:

  • Events: 7859
  • IP Addresses: [“202.163.102.167”, “202.163.68.210”]
  • Critical Severity:
    • These IPs were detected engaging in multiple protocols such as FTP, Telnet, SMTP, MySQL, Redis, Git, and RDP scans, suggesting an attempt to map the network or test for vulnerabilities.

HTTP Traffic:

  • Requests: 104
  • IP Addresses: [“202.163.102.167”, “202.163.68.210”]
  • Critical Severity:
    • The requests were from legitimate users, indicating a mix of normal traffic and potential malicious activity.

IDS Alerts:

  • Alerts: 95819
  • IP Addresses: [“67 IPs”]
  • Critical Severity:
    • An exceptionally high number of IDS alerts (95819) suggests an extensive monitoring environment, likely including Honey-Pi’s own security tools. The use of these alerts could indicate multiple attacks or a highly sensitive network.

Malware Capture:

  • Actions: No malware captured
  • Critical Severity:
    • Despite the high number of threats and potential vulnerabilities, no malware was detected on the system, which is both good and concerning depending on how the honeypot is used in terms of detection capabilities and threat intelligence.

Geographical Analysis

Geographic Distribution:

  • Total IP Addresses: 5511
  • Top Countries:
    • United States: 1662 (30%)
    • China: 441 (8%)
    • Germany: 392 (7%)
    • Belgium: 342 (6%)
    • United Kingdom: 313 (5%)
    • Pakistan: 258 (4%)
    • Netherlands: 219 (3%)
    • Hong Kong: 156 (2%)
    • Korea, Republic of: 148 (2%)

Top IPs:

  • [“139.210.35.246”, “158.94.211.131”]
    • These IPs were primarily located in the United States and China, suggesting a mix of legitimate users and potentially malicious actors targeting these regions.

Malware and AI Defense

Malware:

  • Actions: No malware captured
  • AI Defense:
    • The honeypot utilized artificial intelligence to detect potential threats. It successfully blocked 15 attacks that could have been attempts for data exfiltration or other malicious activities, indicating effective use of AI in monitoring and defense.

Community Defense:

  • Actions: No reported incidents
    • While the community did not report any specific defenses or countermeasures against known threats, the honeypot itself was able to maintain its integrity by detecting these threats and mitigating them through automated responses.

Summary

The October 14, 2026, security threat analysis of Honey-Pi 5 in Spain highlighted a robust but sensitive environment. The system detected over 95% critical alerts from multiple protocols and IP addresses, demonstrating the effectiveness of its IDS/IPS setup. Despite the high number of threats, no malware was captured, indicating an effective use of detection tools.

The geographical distribution showed a mix of legitimate users and potential malicious actors, emphasizing the importance of geographic diversification in security monitoring. The honeypot’s ability to detect attacks and mitigate them through automated responses highlights its effectiveness in protecting against both known and emerging threats.

For future improvements, focusing on more advanced threat intelligence could enhance detection capabilities further. Additionally, maintaining a strong community defense strategy will ensure that attackers are deterred or neutralized before they cause significant damage.


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.