The best honeypots in 2026: open-source and commercial compared

What is the best honeypot in 2026? The answer depends on your goal: threat research, simple alerting on a small network, or intrusion detection at enterprise scale. A honeypot remains one of the most reliable ways to detect an intrusion: a decoy system has no legitimate use, so any interaction with it is suspicious by definition. This comparison reviews the best solutions available today, open source and commercial alike, with their strengths, their limits, and concrete criteria to choose.

How we evaluated them

We kept four criteria, the ones that matter under real conditions:

• Decoy realism: a honeypot that a fingerprinting scan can identify loses most of its value against an experienced attacker.
• Protocol coverage: SSH and HTTP are not enough; a realistic internal network exposes SMB, RDP, databases, LDAP...
• Alert operability: output formats (JSON, Syslog, webhook), SIEM integration, logging quality.
• Maintenance: commit frequency, community activity, upgrade simplicity.

Trapster Community: the most complete option for internal networks

Trapster Community is a modern multi-service honeypot written in Python (asyncio), designed to be deployed on internal networks. It is the open-source project powering the Trapster platform, and it inherits several capabilities that are rare in the ecosystem:

• Realistic website cloning: the HTTP module can replicate the look of real equipment (admin interfaces, portals) from a simple YAML configuration.
• AI-assisted responses: unexpected HTTP requests receive dynamically generated answers, which makes fingerprinting significantly harder.
• Multi-service: SSH, FTP, HTTP/HTTPS, DNS, MySQL, MSSQL, LDAP, RDP and SNMP, among others, in a single agent.
• Structured output: JSON logging ready to ingest into a SIEM or an ELK pipeline.

It is the natural choice if your goal is internal intrusion detection (lateral movement, reconnaissance) rather than academic research.

Cowrie: the SSH/Telnet reference

Cowrie is the successor of Kippo and the reference for trapping SSH and Telnet attacks. It emulates a full interactive shell: the attacker believes they obtained access, their commands are recorded, and the files they download are captured. It is an excellent tool for observing brute-force campaigns and IoT botnets.

Its limits: it focuses on SSH/Telnet (with some SFTP/SCP), and its default artifacts are well known to attackers; a serious deployment requires customizing the hostname, the fake filesystem and the banners.

T-Pot: the all-in-one platform

T-Pot, maintained by Deutsche Telekom Security, is not a single honeypot but a distribution bundling more than twenty of them (Cowrie, Dionaea, Conpot, ElasticPot...) in Docker containers, with an Elastic stack and ready-made dashboards.

It is the ideal tool for research and threat observation on an internet-facing IP. On the other hand, its footprint is heavy (several GB of RAM), and its very recognizable profile makes it better suited to studying opportunistic attacks than to discreet detection inside an internal network.

OpenCanary: the minimalist

OpenCanary, published by Thinkst, is a lightweight Python daemon that emulates about ten services (SMB, FTP, HTTP, MySQL, VNC...) with minimal resource usage. It installs in minutes on a Raspberry Pi or a small VM and sends its alerts by email, webhook or Syslog.

It is an excellent entry point into deception. Its emulations remain shallow: enough to detect a scan or a connection attempt, not enough to fool a human operator for long.

Dionaea and Conpot: the specialists

Two older projects remain relevant in their niches:

• Dionaea captures malware spreading through SMB, FTP or MSSQL. Useful for collecting samples, less so for internal detection.
• Conpot emulates industrial systems (Modbus, S7comm, BACnet). If you operate OT, it is one of the few ICS/SCADA decoys available.

What about commercial deception platforms?

For a company, the best honeypot is not just a good decoy: it is a decoy deployed everywhere, maintained over time, whose alerts reach the right place. That is what commercial platforms are for.

• Trapster: a French deception platform built on the open-source Trapster Community engine. Ready-to-run VMs (deployed in minutes), realistic personas with interface cloning and AI-assisted responses, honeytokens generated and tracked from the dashboard, native SIEM integrations (Splunk, Sentinel, QRadar, Elastic), data hosted in France. Designed for internal detection at SMBs, mid-market companies and MSSPs.
• Thinkst Canary: the pioneer of the category, valued for its simplicity. Physical or virtual appliances plus a canary-token service, priced per device. A safe bet, with a model centered on unit decoys rather than orchestrated network coverage.
• Deception suites from large vendors (for instance FortiDeceptor from Fortinet): relevant if your infrastructure is already standardized on that vendor, at the cost of strong ecosystem lock-in and high license fees.

2026 comparison table

Which honeypot should you choose?

• You want to learn or experiment: Trapster Community or Cowrie on a VM, in an evening.
• You are a researcher or a CERT: T-Pot on an exposed IP, for volume and dashboards.
• You are an SMB without a SOC: a managed platform with actionable alerts; that is exactly Trapster's core audience.
• You run a SOC or an MSSP: a platform with an API, SIEM/SOAR integrations and multi-tenant management of decoys and honeytokens.
• You operate industrial systems: Conpot alongside classic IT coverage.

The limits of open source at scale

An open-source honeypot fits a targeted need well: one decoy on one segment, a research sensor, a learning project. The difficulties appear at organizational scale:

• deploying and updating dozens of decoys across several segments and sites,
• generating and tracking honeytokens on real assets,
• centralizing alerts, deduplicating them and routing them to the SOC,
• keeping decoys realistic over time (banners, versions, naming conventions).

That is exactly the scope of managed deception platforms. Trapster builds on the open-source Trapster Community engine and adds centralized deployment, honeytokens, native SIEM integrations and support. Start with open source to validate the concept; industrialize when the perimeter grows.

Where to start

1. Deploy one decoy on your most sensitive segment (servers, admin VLAN).
2. Wire the alerts into a channel someone actually reads (SIEM, Slack, on-call email).
3. Test it: run an nmap scan from an internal workstation and check that the alert arrives.
4. Extend coverage segment by segment, then add honeytokens.

And if you want to see what a complete platform looks like, book a 30-minute demo: we will set up a test environment with you.

Frequently asked questions

What is the best open-source honeypot? For intrusion detection on an internal network, Trapster Community offers the broadest protocol coverage with realistic decoys. To observe SSH attacks specifically, Cowrie remains the reference. For research on an exposed IP, T-Pot bundles the best of the ecosystem.

Is a free honeypot enough for a company? To validate the concept on one segment, yes. At scale (several segments, honeytokens, centralized alerting to a SOC, keeping decoys realistic), the total cost of ownership of open source quickly exceeds that of a managed platform.

Does a honeypot replace an EDR or an IDS? No, it complements them. An EDR covers endpoints running its agent, an IDS analyzes traffic with signatures; a honeypot catches what they miss (lateral movement, agentless machines) with a false-positive rate close to zero. Our complete honeypot definition details this complementarity.

How much does a honeypot cost? From zero (self-hosted open source) to a few thousand euros per year for an enterprise platform with support, depending on the number of decoys and integrations. See our pricing for a concrete order of magnitude.