💀 critical 🤖 qwen2.5:1.5b

Honeypot Threat Analysis — July 3, 2026

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

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

Cybersecurity Analysis for 2026-07-03

Threat Overview

On July 3, 2026, a honey-pot system managed by the team at Honey-AI.dev encountered various types of threats from an estimated 218 attackers. The primary methods used included SSH brute force attempts and HTTP requests to common web paths.

Geographical Analysis

The top 5 countries identified as having attacked this honeypot are:

  • United States (881 entries)
  • China (450 entries)
  • Belgium (177 entries)
  • Pakistan (151 entries)
  • Netherlands (133 entries)

These locations suggest that the attack vectors could be coming from multiple regions, indicating a diverse threat landscape.

SSH Brute Force

The system experienced 815 SSH connections and 486 login attempts. The attackers were using various passwords such as “4813494d137e1631” and “8c6976e5b5410415”. Despite being protected by strong security measures, the system remained vulnerable to brute force attacks.

Web Scanning

The honeypot received 22 HTTP requests from 22 IP addresses. Common paths included “/dispatch.asp”, ”/”, “/SDK/webLanguage”, “/zc?action=getInfo”, and “/.env”.

IDS & Scan Intel

Suricata Intrusion Detection System (IDS) recorded 9706 alerts, targeting various protocols like FTP, Telnet, SMTP, MySQL, Redis, Git, VNC, RDP, and HTTP. The primary threat was identified as “critical” in severity.

Malware

No malware was captured during this period, indicating that the honeypot remained undetected for a significant amount of time despite being set up with various security measures.

Tarpit and Backfire Scans

The system trapped 100 connections from 49 IPs. Additionally, there were ten open scans targeting 11 different IP addresses, but no malware was detected in these instances either.

MCP Trap

A single request to trigger a trap event was made using the AWS token “aws” associated with user-agent “Go-http-client/1.1”. Another request triggered the same event using an AWS token “md/Botocore#1.43.36 ua/2.1 os/linux#5.14.0-592.el9.x86_64 md/arch#x86_64 lan…” for a different IP address.

Portscans

There were no reports of port scans being conducted against the honeypot system during this period, indicating that attackers may be targeting other systems within the same network or attempting to identify vulnerabilities in another device.

Backfire Scans and Tarpit

The data provided does not include any specific targets for backfire scans or tarpits. However, it’s noted that no malware was captured, suggesting that these techniques were not being used against this honeypot system.

MCP Trap and Portscans

No reports of attacks using MCP traps or portscans were present in the data provided.

AI Defense and Community Defense

The system showed zero injections blocked by AI defense measures, which suggests that current security defenses are effective in preventing these types of attacks. There was also no leakage detected during this period, indicating a secure environment for testing purposes.

Threat Overview Summary

In summary, despite being set up as a honeypot with advanced security features, the system encountered multiple threats from 218 attackers over the course of the day. The SSH brute force attempts and HTTP requests to common paths were particularly prevalent. While no malware was detected, the presence of tarpits suggests that attackers may be attempting to identify vulnerabilities in another system within the same network.

Conclusion

The results highlight the importance of continuous improvement in security measures for honeypot systems. By monitoring various attack vectors and using advanced defense tools, organizations can better understand their adversaries’ tactics and stay ahead of potential threats.


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.