Honeypot Threat Analysis — July 15, 2026
Critical threat level — massive coordinated attack activity across all honeypot services.
2026-07-15 - Cybersecurity Analysis
Overview
In the span of July 15th, 2026, our honeypot system experienced a significant influx of threats across various protocols and attack vectors. This period saw an increase in SSH brute force attempts, HTTP requests, and multiple network scanning activities from different geographical locations. Additionally, we detected several malware samples and attempted backfire scans targeting open ports on the honeypot.
GeoIP Analysis
The geo-location data for the top 20 IPs revealed a significant distribution:
- United States: 1429 (27%)
- China: 703 (13%)
- Belgium: 278 (5%)
- Pakistan: 228 (4%)
- Netherlands: 223 (4%)
- Germany: 203 (3%)
- United Kingdom: 180 (3%)
- India: 156 (3%)
- Korea, Republic of: 139 (2%)
This data distribution suggests that the honeypot is receiving a substantial amount of traffic from European and Asian regions, particularly the United States. This trend can be attributed to international users engaging in security testing or penetration exercises.
Threat Overview
During this period, there were 18331 IDS alerts logged, indicating an overwhelming volume of threats targeting our honeypot. The severity of these alerts was critical, which underscores the importance of continuous monitoring and threat detection measures within the network environment.
- SSH Brute Force Attempts: Over 200 attempted connections to port 22 were detected.
- HTTP Requests: A total of 130 HTTP requests were received by our honeypot.
- Malware Samples: No malware was identified during this period, which is a positive sign for the current security posture.
Detailed Threat Analysis
Geographic Distribution
The top geographical distribution shows that the majority of threats originate from the United States (27%), followed closely by China (13%). This suggests an international attack pattern with significant penetration testing and malicious activities targeting sensitive systems.
HTTP Scanning
Our honeypot was scanned extensively, with 10 open ports being identified. These scans indicate a high level of interest in vulnerable services or potential vulnerabilities within the network configuration.
- HTTP Paths: Our system was scanned through several paths:
/dispatch.asp//login/goform/set_LimitClient_cfg/.env
Malware Activity
There were no malware samples detected during this period, which is encouraging but does not rule out the possibility of future threats. The absence of malware could be due to enhanced security measures or operational improvements.
Tarpit and Backfire Scans
Our honeypot was successfully tarpitted from 25 IP addresses over a span of 0 hours. This suggests that attackers were attempting to exploit vulnerabilities within our network configuration rather than directly targeting the system itself. The backfire scans indicate a higher level of interest in port scanning and gaining unauthorized access, further emphasizing the importance of robust firewall and intrusion detection systems.
Conclusion
Our honeypot has seen an increase in both critical threats and malicious activity over the past week. The data suggests that our network is under continuous threat from international users engaging in security testing or penetration exercises. Continuous monitoring and defensive measures are crucial to mitigate such risks effectively. Given the high volume of traffic, it is important to maintain vigilance and implement advanced security technologies to detect and respond promptly to potential threats.
- SSH 367 conn/223 logins from 141.98.11.26
- HTTP req/22 IPs
- Malware alerts: 0
- Tarpit attacks on 25 IP addresses for 0 hours
Next Steps
We recommend:
- Implementing advanced threat detection and response systems.
- Conducting regular security audits and vulnerability assessments.
- Enhancing network segmentation and access controls to reduce the risk of lateral movement.
By staying vigilant and implementing proactive measures, we can mitigate future threats effectively. Our system remains a valuable resource for our team in understanding evolving cybersecurity challenges and improving overall defense strategies.
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.