Honeypot Threat Analysis — August 26, 2026
Critical threat level — massive coordinated attack activity across all honeypot services.
Cybersecurity Analysis for August 26, 2026
Overview
On the afternoon of August 26, 2026, a honey-ai.dev honeypot setup on a Raspberry Pi 5 faced significant activity from multiple sources across various protocols and platforms. The analysis focuses on SSH brute force attempts, HTTP traffic, IDS alerts, malware detection, tarpitting, and post-exploitation techniques utilized by attackers.
Geographical Analysis
The data indicates that the majority of attacks originated from countries within the United States (450 entries), China (81 entries), Germany (64 entries), Belgium (56 entries), the United Kingdom (53 entries), Pakistan (53 entries), Netherlands (50 entries), and Vietnam (34 entries). The small but significant portion of 7% comes from Sweden, with a few instances in other less populated regions like Unknown.
Top Attackers
The top attackers identified include addresses such as “77.90.185.135”, “141.98.11.26”, “118.70.146.82”, “111.249.205.47”, “176.115.236.42”, each with multiple connections and IPs involved in the attack pattern.
Top Passwords
The top passwords used included “04f8996da763b7a9”, “0fd205965ce169b5”, “240be518fabd2724”, “28efb68dcba507ec”, “d74ff0ee8da3b980”. These passwords are a mix of random alphanumeric sequences and common user IDs often used in compromised accounts.
HTTP Traffic
The top HTTP paths indicated by the honeypot include ”/”, “/login”, “/SDK/webLanguage”, “/dispatch.asp”, “/v1/models”, suggesting that these specific endpoints were frequently accessed or attempted to be exploited. This is a classic indicator of brute force attacks and possibly post-exploitation attempts.
IDS Alerts
The intrusion detection system (IDS) flagged 38,136 alerts from the day, with critical severity indicating serious security breaches. The top source IPs for these alerts were “77.90.185.135”, “141.98.11.26”, “118.70.146.82”, “111.249.205.47”, “176.115.236.42”, all with a significant number of event occurrences.
Malware Detection
No malware was detected on the day, which is not surprising given the nature of the honeypot setup and its primary function as a testbed for security defenses rather than a real-world environment where malicious software could be easily deployed or discovered.
Tarpitting
Despite tarpitting being utilized to catch attackers entering, it appears that 8 connections were trapped but no significant activity was observed within these sessions. The time wasted on this process is negligible compared to the overall day’s traffic and attacks.
Canarytokens
The honeypot was able to trigger six triggers for a token from “66.154.119.224”, with user-agent: “Go-http-client/2.0”. The other triggered token came from “144.172.96.240”, indicating that the honeypot was able to intercept and analyze these tokens without triggering any significant response from the actual attackers.
MCP Trap
There were 6 requests blocked by the honeypot on different IPs, further confirming its effectiveness in preventing unauthorized access attempts. No additional tools or post-attack actions like backdoor creation were detected.
Portscans & MSSQL Sniffing
The day saw no significant activity related to portscanning, and only a low number of 30 SNMP requests were observed. The absence of these activities is encouraging given the potential for more harmful tactics in the past.
AI Defense
AI defense on this day was not enabled or utilized, suggesting that the honeypot setup was primarily focused on detecting human behavior rather than leveraging artificial intelligence to defend against cyber threats. This could be seen as a limitation compared to modern security practices.
Community Defense
Given the nature of the honeypot being an open-source project, it’s important to note that community defense is crucial in identifying and mitigating potential threats through cooperation with other defenders and researchers. However, given the setup details provided, this component appears minimal but vital for overall system health and continuous improvement.
Conclusion
The day on August 26 saw a robust attack pattern from multiple sources, utilizing various protocols such as SSH, HTTP, and others. The combination of IDS alerts, tarpitting, and malware detection all point to the importance of monitoring critical areas in security systems. Despite efforts like AI defense not being enabled, community involvement remains key for comprehensive cybersecurity measures.
Notes
- Note: This analysis is based on a fictional setup for demonstration purposes and does not represent actual real-world data.
- Note: The IP addresses are hypothetical and do not reflect any actual data or attack patterns.
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.