💀 critical 🤖 qwen2.5:1.5b

Honeypot Threat Analysis — August 22, 2026

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

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

Cybersecurity Threat Analysis for August 22, 2026

Overview:

On August 22, 2026, the honeypot system running on a Raspberry Pi 5 in Spain experienced significant activity from a total of 187 attackers over multiple protocols. The primary threat vectors involved SSH brute force attempts and HTTP requests. The system detected critical IDS alerts for nearly 43% of the attackers.

Geo-Location Analysis:

The top three countries with reported abuse IPs were United States (458), China (88), and Germany (67). The system also tracked a number of malware campaigns targeting various regions, including Pakistan, Netherlands, Sweden, and Vietnam.

Threat Overview

Over the period, 753 SSH connections were attempted, leading to approximately 418 logins. Additionally, 128 unique IPs exhibited multiple protocol activities like FTP, Telnet, SMTP, MySQL, Redis, Git, VNC, RDP, totaling 13,795 events. The HTTP requests were limited to five different paths, with a total of 54 requests from 25 IPs.

SSH Brute Force

The most significant threat came from brute force attacks using SSH connections. There were 753 attempted connections and 418 logins, indicating that the system was actively monitoring for these attempts but not yet capturing any successful breaches. The attackers used various passwords including “62eee0dfb96e0bb0”, “8c6976e5b5410415”, and “56925e07167bd335”.

Post-Exploitation

The system successfully executed multiple post-exploitation commands, including:

  • uname -s -v -n -r -m: Retrieving system information.
  • cd ~; chattr -ia .ssh; lockr -ia .ssh: Modifying SSH configuration files.
  • /bin/./uname -s -v -n -r -m: Executing the same command as above.
  • Multiple attempts to execute cat /proc/cpuinfo and check CPU details, followed by a simple head operation on the output.

Web Scanning

The honeypot detected HTTP traffic from 25 IPs, with URLs including “/login”, “/SDK/webLanguage”, and “/goform/set_LimitClient_cfg”. The system did not record any vulnerabilities or specific exploits during this period but instead focused on tracking network activity related to web requests.

IDS & Scan Intel

The honeypot reported nearly 15422 alerts from the Suricata IDS system, with a significant number of alerts classified as critical. This indicates that the system is actively scanning networks and identifying potential threats based on various protocols.

Malware

No malware was captured during this period.

Tarpit & Backfire Scans

The honeypot recorded 94 connections being tarpitted by various IPs, with a total of 0 hours wasted. Additionally, 12 scans were detected, targeting IP addresses like 165.154.100.252, 45.194.67.120, and others.

MCP Trap

The honeypot received 3 requests with no malicious payloads captured. The “user-agent” field indicated a Boto3/1.43.72 botnet activity originating from IP address 64.49.8.54, using various plugins like md/Botocore#1.43.72 ua/2.1 os/windows#2022Server md/arch#amd64 lang/python#3.13.15 md/pyimpl#CPython m/E,b,Z,e cfg/retry-mode#standard.

Portscans

Portscanning was not detected during this period, with 0 open ports being scanned by the honeypot system.

AI Defense

The honeypot did not detect any injection or leak attempts within the monitoring period. The system’s active defense against these threats is based on its configuration and security protocols rather than automated AI systems.

Community Defense

There were no community defenses reported in this period, suggesting that the honeypot network was not actively involved in defensive measures like firewalls or intrusion detection tools.

Conclusion:

The honeypot system successfully identified a significant number of attackers over multiple protocols. The threat vectors primarily focused on brute force SSH connections and web traffic, with limited malicious activity detected within the monitored period. This analysis highlights the importance of continuous monitoring for potential threats in cybersecurity environments.


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.