TANNER alternatives

Looking for an alternative tool to replace TANNER? During the review of TANNER we looked at other open source tools. Based on their category, tags, and text, these are the ones that have the best match.

Top 3

  1. Cowrie (SSH/telnet honeypot)
  2. Dionaea (honeypot)
  3. Dockpot (SSH honeypot based on Docker)

These tools are ranked as the best alternatives to TANNER.

Alternatives (by score)

70

Cowrie

Introduction

Cowrie is a honeypot to emulate SSH and telnet services. It can be used to learn attack methods and as an additional layer for security monitoring.

Project details

Cowrie is written in Python.

Strengths and weaknesses

  • + More than 50 contributors
  • + More than 1000 GitHub stars

    Typical usage

    • Information gathering
    • Learning
    • Security monitoring
    • Threat discovery

    Cowrie review

    60

    Dionaea

    Introduction

    Dionaea is a honeypot that can emulate a range of services like FTP, HTTP, MySQL, and SMB. It can be used to see and learn how attackers work.

    Project details

    Dionaea is written in C.

    Strengths and weaknesses

    • + The source code of this software is available
    • - Full name of author is unknown

    Typical usage

    • Learning
    • Threat discovery

    Dionaea review

    56

    Dockpot

    Introduction

    Using an SSH honeypot is a good way to learn about common attacks on the SSH service. It can provide insights on the number of scans and probes on the network.

    Project details

    Dockpot is written in Python.

    Strengths and weaknesses

    • + The source code of this software is available
    • - No releases on GitHub available

    Typical usage

    • Learning
    • Threat discovery

    Dockpot review

    60

    Heralding

    Introduction

    Heralding is a simple honeypot to collect credentials. It supports common protocols like FTP, SSH, HTTP, etc.

    Project details

    Heralding is written in Python.

    Strengths and weaknesses

    • + Many releases available
    • + The source code of this software is available

      Heralding review

      64

      HonSSH

      Introduction

      HonSSH is a high-interaction SSH honeypot to collect information about attackers that target the SSH service.

      Project details

      HonSSH is written in Python.

      Strengths and weaknesses

      • + The source code of this software is available
      • - Unknown project license

      Typical usage

      • Learning
      • Threat discovery

      HonSSH review

      63

      Kojoney

      Introduction

      Kojoney is a mix of the Spanish word cojon (s/c/k/) and honey.

      Project details

      56

      Kojoney2

      Introduction

      Kojoney2 is an SSH honeypot based on Kojoney by Jose Antonio Coret. It can be used to learn about threats by mimicking an SSH service.

      Project details

      Kojoney2 is written in Python.

      Strengths and weaknesses

      • + The source code of this software is available
      • - No updates for a while

      Typical usage

      • Learning
      • Threat discovery

      Kojoney2 review

      64

      MTPot

      Introduction

      MTPot is a so-called telnet honeypot that allows to bind and listen on a specific port. It can be configured to allow specific commands and the related responses to return. The tool also performs fingerprinting to discover what type of attack is occuring and send these details via syslog.

      Project details

      MTPot is written in Python.

      Strengths and weaknesses

      • + Very low number of dependencies
      • + The source code of this software is available

        Typical usage

        • Learning
        • Threat discovery

        MTPot review

        60

        SSH Honeypot

        Introduction

        SSH Honeypot is as the name implies a honeypot to emulate the SSH service. It can be used to learn about threats and commands used by attackers.

        Project details

        SSH Honeypot is written in C.

        Strengths and weaknesses

        • + The source code of this software is available

          Typical usage

          • Learning
          • Threat discovery

          SSH Honeypot review

          64

          SSHHiPot

          Introduction

          SSHHiPot is a high-interaction SSH honeypot. It captures connections and commands that are to be performed, for the purpose of learning about possible threats.

          Project details

          SSHHiPot is written in Golang.

          Strengths and weaknesses

          • + The source code of this software is available

            Typical usage

            • Learning
            • Threat discovery

            SSHHiPot review

            97

            Thug

            Introduction

            The honeypot concept is a well-known technique to collect attack patterns on servers and systems. Tools like Thug are considered to be a honeyclient, or client honeypot. These tools collect attacks against client applications. For example by mimicking a web application and visit a malicious page to see if any code is attacking the application.

            Project details

            Thug is written in Python.

            Strengths and weaknesses

            • + The source code of this software is available

              Typical usage

              • Learning
              • Malware analysis
              • Threat discovery

              Thug review

              64

              mehrai

              Introduction

              Honeypots like mehrai can be used to learn more about incoming attacks. It might be useful to determine threats to your network or about the steps that attackers perform.

              Project details

              mehrai is written in Python.

              Strengths and weaknesses

              • + The source code of this software is available

                Typical usage

                • Learning
                • Network security monitoring
                • Security monitoring

                mehrai review

                64

                sshesame

                Introduction

                A honeypot can provide valuable insights on commands that automated scripts perform or attackers. By running a honeypot like sshesame, connection details and commands are stored for later analysis. The system itself won't execute the actual commands, to prevent any damage to it.

                Project details

                sshesame is written in Golang.

                Strengths and weaknesses

                • + The source code of this software is available
                • - No releases on GitHub available

                Typical usage

                • Learning
                • Threat discovery

                sshesame review

                70

                SNARE

                Introduction

                SNARE is an abbreviation for Super Next generation Advanced Reactive honEypot.

                Project details

                SNARE is written in Python.

                Strengths and weaknesses

                • + The source code of this software is available

                  Typical usage

                  • Security monitoring

                  SNARE review

                  70

                  Conpot

                  Introduction

                  Conpot is an ICS honeypot to collect intelligence and information about attacks against industrial control systems. It is written in Python.

                  Project details

                  Conpot is written in Python.

                  Strengths and weaknesses

                  • + More than 25 contributors
                  • + The source code of this software is available

                    Typical usage

                    • Information gathering
                    • Intrusion detection
                    • Learning

                    Conpot review

                    64

                    HonTel

                    Introduction

                    HonTel is a honeypot that emulates the telnet service within a chroot environment. It can be used to learn about enumeration activities or new attack methods.

                    Project details

                    HonTel is written in Python.

                    Strengths and weaknesses

                    • + The source code of this software is available

                      Typical usage

                      • Learning
                      • Security monitoring

                      HonTel review

                      60

                      HoneyPi

                      Introduction

                      A honeypot is useful to learn more about the network probes that are happening. As this project uses a Raspberry Pi, the investments for a deployment are low.

                      Project details

                      HoneyPi is written in Python.

                      Strengths and weaknesses

                      • + The source code of this software is available

                        Typical usage

                        • Learning
                        • Network analysis

                        HoneyPi review

                        60

                        HoneyPy

                        Introduction

                        The honeypot can be extended by plugins and customization is possible as well. This may increase the interaction level that the honeypot can support. All activity is logged to a file, with the option to post activity to Twitter or a web server.

                        Project details

                        HoneyPy is written in Python.

                        Strengths and weaknesses

                        • + The source code of this software is available

                          Typical usage

                          • Security monitoring

                          HoneyPy review

                          52

                          Honeyprint

                          Introduction

                          There is not much information available about this project, as it is a proof-of-concept on GitHub. It is written by Lukas Rist in 2013, and placed on GitHub early 2016.

                          Project details

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