Setting Up Cloud-Based Honeypots in AWS, Azure, and GCP

In today’s dynamic threat landscape, proactive defense strategies like honeypots are becoming increasingly essential for identifying, understanding, and mitigating cyber threats. As enterprises move their workloads to the cloud, deploying cloud-based honeypots across major platforms like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) provides visibility into attacker behaviors in the cloud-native environment.

This article will guide you through setting up honeypots in these cloud platforms, compare best practices, and explore how to use cyber deception technology as part of a broader cloud security strategy.

What is a Cloud-Based Honeypot?

A honeypot is a decoy system or resource designed to mimic legitimate assets, luring attackers into interacting with it. These interactions are monitored to gather intelligence without exposing real systems.

Cloud-based honeypots emulate virtual machines, services, containers, APIs, or databases running in cloud environments. Their goal is to detect unauthorized access attempts, lateral movement, and misconfigurations—particularly those that wouldn't be caught by traditional perimeter defenses.

Benefits of Deploying Honeypots in the Cloud

• Visibility into attacker behavior in real-world conditions

• Early breach detection before attackers reach sensitive assets

• Threat intelligence enrichment through telemetry

• Validation of security configurations and access controls

• Compliance support through monitoring and auditing capabilities

Choosing the Right Type of Honeypot

Before deployment, decide on the type of honeypot that fits your cloud threat model:

• Low-interaction honeypots: Simulate limited services (e.g., SSH or HTTP) with minimal risk.

• High-interaction honeypots: Deploy real systems or applications for deep analysis.

• Honeytokens: Fake credentials or data artifacts to detect unauthorized access.

• Service emulators: Fake APIs, databases, or containers that mimic cloud-native workloads.

Setting Up Honeypots in AWS

1. Deploying EC2-Based Honeypots

You can create a basic low-interaction honeypot using EC2 instances running tools like Cowrie (SSH), Dionaea, or Snort.

Steps:

• Launch an EC2 instance in a monitored subnet (e.g., DMZ or unused IP range).

• Configure security groups to allow traffic from the internet (e.g., port 22).

• Install honeypot software and set up centralized logging (CloudWatch or ELK).

• Use VPC flow logs for network telemetry.

2. Leverage AWS Marketplace Honeypots

Solutions like Thinkst Canary, T-Pot, or HoneyDB collectors are available as AMIs (Amazon Machine Images) for faster deployment.

3. Integrate with AWS Native Services

• CloudWatch: Monitor logs and metrics.

• GuardDuty: Correlate honeypot activity with threat detection.

• SNS: Send alerts on suspicious interaction.

Setting Up Honeypots in Microsoft Azure

1. Deploy Azure VMs as Decoy Systems

• Use Windows or Linux VMs with fake services (RDP, SMB, SQL).

• Lock them in isolated resource groups with monitoring agents installed.

• Use Azure Network Security Groups (NSGs) to control and log access.

2. Azure Sentinel Integration

• Forward logs from honeypots to Azure Sentinel.

• Create custom alerts for honeypot interaction signatures.

• Use Workbook dashboards for honeypot threat insights.

3. Use Azure Deception Tools

While Azure lacks a built-in deception suite, you can use tools like Modern Honey Network (MHN), Canarytokens.org, or integrate commercial deception platforms.

4. Monitor with Azure Defender

Pair your honeypot deployments with Microsoft Defender for Cloud to monitor suspicious connections and correlate with other cloud security signals.

Setting Up Honeypots in Google Cloud Platform (GCP)

1. Create Decoy Compute Engine Instances

• Deploy small instances running honeypot software (e.g., Glutton, Cowrie).

• Open ports like SSH, RDP, MySQL, or Redis—common attack targets.

• Use Cloud Firewall Rules to simulate misconfigured services.

2. Centralized Logging

• Enable Cloud Logging and Cloud Monitoring for activity tracking.

• Push logs to BigQuery or Pub/Sub for analysis.

3. Deception with GCP Tools

While GCP doesn’t have native deception services, you can use open-source solutions or integrate with third-party platforms (e.g., Attivo, Cymmetria).

4. Alerting and Response

• Use Cloud Functions for serverless alerts and automated response.

• Integrate with Security Command Center (SCC) for incident tracking.

Best Practices for Cloud-Based Honeypots

1. Isolation and Segmentation

Ensure honeypots are isolated from production resources using security groups, VPC peering rules, or firewall policies.

2. Logging and Monitoring

Forward all interaction logs to SIEM or log analytics tools. Use behavioral rules to flag anomalies.

3. Avoid Detection by Attackers

• Rotate banners and fake credentials regularly.

• Mimic realistic configurations.

• Don’t allow full OS fingerprinting.

4. Deploy Across Zones

Place honeypots across multiple regions, VPCs, and accounts to increase coverage and catch attacks on different cloud surfaces.

5. Simulate Real Applications

Use container honeypots or fake APIs (e.g., OpenAPI stubs) to simulate microservices.

Comparing Cloud Platforms

Conclusion

Cloud-based honeypots are essential components in modern cloud deception strategies. Whether you're operating in AWS, Azure, or GCP, deploying honeypots can help detect intrusions, gather attacker intelligence, and validate your cloud defenses. Combined with SIEMs, deception tokens, and automated alerting, honeypots empower security teams to outsmart adversaries and build resilience in cloud-native environments.