Ollama Enum

documentation/modules/auxiliary/scanner/http/ollama_info.md

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+## Vulnerable Application
+
+This module identifies ollama instances and enumerates the LLM
+models which have been loaded and are running.
+
+### Building Image
+
+Write the following dockerfile.
+
+```dockerfile
+FROM ollama/ollama
+
+EXPOSE 11434
+
+VOLUME /root/.ollama
+
+RUN /bin/ollama serve & \
+    sleep 5 && \
+    /bin/ollama pull llama3.2:1b && \
+    /bin/ollama pull qwen3.5:0.8b && \
+    /bin/ollama pull smollm:135m && \
+    printf 'FROM smollm:135m\nSYSTEM "you are an AI assistant and this is your system prompt"\n' > /Modelfile && \
+    /bin/ollama create my-model -f /Modelfile
+
+RUN printf '#!/bin/bash\n/bin/ollama serve &\nsleep 3\ncurl -s http://localhost:11434/api/chat -d '"'"'{"model":"my-model","stream":false,"messages":[{"role":"user","content":"warmup"}]}'"'"'\nwait\n' > /start.sh && \
+    chmod +x /start.sh
+
+ENTRYPOINT []
+CMD ["/start.sh"]
+```
+
+Build and start it.
+
+```
+docker build -t my-ollama .
+docker run -d -p 11434:11434 --name my-ollama my-ollama
+```
+
+## Verification Steps
+
+1. Start the ollama docker
+2. Start msfconsole
+3. Do: `use auxiliary/scanner/http/ollama_info`
+4. Do: `set rhosts [IPs]`
+5. Do: `run`
+6. You should get information about the models in teh ollama instance
+
+## Options
+
+## Scenarios
+
+### Docker image
+
+```
+msf > use auxiliary/scanner/http/ollama_info
+msf auxiliary(scanner/http/ollama_info) > set rhosts 127.0.0.1
+rhosts => 127.0.0.1
+msf auxiliary(scanner/http/ollama_info) > run
+[*] Checking 127.0.0.1
+[*]   Found model: my-model:latest
+[*]   Found model: smollm:135m
+[*]   Found model: qwen3.5:0.8b
+[*]   Found model: llama3.2:1b
+[*] 127.0.0.1 Ollama Models
+=======================
+
+  Name      Release  Status     Size       Parameter Size  Temperature  System Prompt
+  ----      -------  ------     ----       --------------  -----------  -------------
+  llama3.2  1b       Installed  1.23 GB    1.2B            N/A          N/A
+  my-model  latest   Running    130.77 MB  134.52M         0.2          you are an AI assistant and this is your system prompt
+  qwen3.5   0.8b     Installed  988.05 MB  873.44M         1            N/A
+  smollm    135m     Installed  87.49 MB   134.52M         0.2          N/A
+
+[*] Scanned 1 of 1 hosts (100% complete)
+[*] Auxiliary module execution completed
+```

modules/auxiliary/scanner/http/ollama_info.rb

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+##
+# This module requires Metasploit: https://metasploit.com/download
+# Current source: https://github.com/rapid7/metasploit-framework
+##
+
+class MetasploitModule < Msf::Auxiliary
+  include Msf::Exploit::Remote::HttpClient
+  include Msf::Auxiliary::Scanner
+
+  def initialize(info = {})
+    super(
+      update_info(
+        info,
+        'Name' => 'Ollama Scanner',
+        'Description' => %q{
+          This module identifies ollama instances and enumerates the LLM
+          models which have been loaded and are running.
+        },
+        'License' => MSF_LICENSE,
+        'Author' => [
+          'h00die'
+        ],
+        'References' => [
+          ['URL', 'https://ollama.readthedocs.io/en/api/']
+        ],
+        'Notes' => {
+          'Stability' => [CRASH_SAFE],
+          'Reliability' => [],
+          'SideEffects' => []
+        }
+      )
+    )
+
+    register_options(
+      [
+        Opt::RPORT(11434),
+        OptString.new('TARGETURI', [true, 'Base URI', '/']),
+      ]
+    )
+  end
+
+  def humanize(bytes)
+    units = ['B', 'KB', 'MB', 'GB', 'TB']
+    i = (Math.log2(bytes) / 10).to_i
+    '%.2f %s' % [bytes.to_f / (1024**i), units[i]]
+  end
+
+  def ollama?
+    res = send_request_cgi({ 'uri' => normalize_uri(datastore['TARGETURI']) })
+
+    return res.body == 'Ollama is running' if res && res.code == 200
+
+    nil
+  end
+
+  def generate
+    res = send_request_cgi({ 'uri' => normalize_uri(datastore['TARGETURI'], 'api', 'generate') })
+
+    return res.get_json_document if res && res.code == 200
+
+    nil
+  end
+
+  def list_local_models
+    res = send_request_cgi({ 'uri' => normalize_uri(datastore['TARGETURI'], 'api', 'tags') })
+
+    return res.get_json_document if res && res.code == 200
+
+    nil
+  end
+
+  def list_running_models
+    res = send_request_cgi({ 'uri' => normalize_uri(datastore['TARGETURI'], 'api', 'ps') })
+
+    return res.get_json_document if res && res.code == 200
+
+    nil
+  end
+
+  def get_model_info(model)
+    post_data = {
+      'model' => model
+    }
+    post_json = JSON.generate(post_data)
+    res = send_request_cgi({
+      'method' => 'POST',
+      'ctype' => 'application/json',
+      'data' => post_json,
+      'uri' => normalize_uri(target_uri.path, 'api', 'show')
+    })
+
+    return res.get_json_document if res && res.code == 200
+
+    nil
+  end
+
+  def get_temperature(details)
+    unless details.nil? || details['parameters'].nil?
+      details['parameters'].each_line do |line|
+        next unless line.start_with?('temperature')
+
+        return line.split[1]
+      end
+    end
+    'N/A'
+  end
+
+  def get_system_prompt(details)
+    unless details.nil? || details['modelfile'].nil?
+      details['modelfile'].each_line do |line|
+        next unless line.start_with?('SYSTEM ')
+
+        return line.split('SYSTEM ')[1]
+      end
+    end
+    'N/A'
+  end
+
+  def run_host(ip)
+    vprint_status("Checking #{ip}")
+    unless ollama?
+      vprint_error('Ollama instance not found')
+      return
+    end
+    models_table = Rex::Text::Table.new(
+      'Header' => "#{ip} Ollama Models",
+      'Indent' => 2,
+      'Columns' => [
+        'Name',
+        'Release',
+        'Status',
+        'Size',
+        'Parameter Size',
+        'Temperature',
+        'System Prompt'
+      ]
+    )
+    running = []
+    local_models = list_running_models
+    local_models['models'].each do |model|
+      vprint_status("  Found model: #{model['name']}")
+      details = get_model_info(model['name'])
+      temperature = get_temperature(details)
+      system_prompt = get_system_prompt(details)
+
+      models_table << [
+        model['name'].split(':')[0],
+        model['name'].split(':')[1],
+        'Running',
+        humanize(model['size']),
+        details.dig('details', 'parameter_size'),
+        temperature,
+        system_prompt
+      ]
+      running << model['name']
+    end
+    local_models = list_local_models
+    local_models['models'].each do |model|
+      next if running.include?(model['name'])
+
+      vprint_status("  Found model: #{model['name']}")
+      details = get_model_info(model['name'])
+      temperature = get_temperature(details)
+      system_prompt = get_system_prompt(details)
+
+      models_table << [
+        model['name'].split(':')[0],
+        model['name'].split(':')[1],
+        'Installed',
+        humanize(model['size']),
+        details.dig('details', 'parameter_size'),
+        temperature,
+        system_prompt
+      ]
+    end
+
+    print_status(models_table.to_s)
+  end
+end