quick_start/quick_start_guide.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Overview\n",
    "This notebook contains a quick start guide for the NIM Agent Blueprint: Vulnerability Analysis for Container Security. By the end of the notebook, you will be able to run the blueprint on an example input, and view the results.\n",
    "\n",
    "For full instructions on running and customizing the blueprint, please see the [README](../README.md).\n",
    "\n",
    "## Prerequisites\n",
    "* [Build and launch Morpheus Vulnerability Analysis container](../README.md#getting-started)\n",
    "    + Be sure to keep the container bash shell handy for launching the HTTP server\n",
    "* From the host machine (outside the container), open this notebook in a [Jupyter server](https://docs.jupyter.org/en/latest/running.html), or from an IDE that supports notebook execution, such as [VS Code](https://code.visualstudio.com/docs/datascience/jupyter-notebooks).\n",
    "    + A running Jupyter server is included with the container by default. Instructions to connect can be found in this README section: [From the quick start user guide notebook](../README.md#from-the-quick-start-user-guide-notebook).\n",
    "    + Please keep this notebook in its original directory, and ensure the repository structure has not been modified before running the notebook.\n",
    "* [Install `pandas`](https://pandas.pydata.org/docs/getting_started/install.html)\n",
    "* [Install Syft](https://github.com/anchore/syft) (optional prerequisite for cell 4, Generating a custom SBOM)\n",
    "\n",
    "## Other notes\n",
    "* All files and directories in the notebook are relative to the repository root.\n",
    "\n",
    "# Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import json\n",
    "import pandas as pd\n",
    "import re\n",
    "import requests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Change the notebook's working directory to the repository root. All the directory and file paths below will now be relative to `REPO_ROOT`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "REPO_ROOT = !echo $(git rev-parse --show-toplevel)\n",
    "os.chdir(REPO_ROOT[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preparing the workflow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Select container and obtain SBOM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using pre-generated SBOM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "sbom_file = \"data/sboms/nvcr.io/nvidia/morpheus/morpheus:v23.11.01-runtime.sbom\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generating a custom SBOM\n",
    "\n",
    "Be aware that depending on the size of the container, the sbom generation process can take several minutes to complete."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# import os\n",
    "# import subprocess\n",
    "#\n",
    "# image_url = \"nvcr.io/nvidia/morpheus/morpheus:v23.11.01-runtime\"\n",
    "# sbom_file = \".tmp/morpheus231101.sbom\"\n",
    "# if not os.path.exists(sbom_file):\n",
    "#     cmd = ['syft', image_url, '-o', 'syft-table='+sbom_file]\n",
    "#     sp = subprocess.Popen(cmd, stderr=subprocess.PIPE, stdout=subprocess.PIPE, shell=False)\n",
    "#     (out, err) = sp.communicate()\n",
    "#     print(out)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load up example HTTP input config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"$schema\": \"./schemas/config.schema.json\",\n",
      "  \"engine\": {\n",
      "    \"agent\": {\n",
      "      \"model\": {\n",
      "        \"model_name\": \"meta/llama3-70b-instruct\",\n",
      "        \"service\": {\n",
      "          \"_type\": \"nvfoundation\"\n",
      "        },\n",
      "        \"max_tokens\": 2000,\n",
      "        \"temperature\": 0,\n",
      "        \"top_p\": 0.01,\n",
      "        \"seed\": 42\n",
      "      },\n",
      "      \"verbose\": false\n",
      "    },\n",
      "    \"checklist_model\": {\n",
      "      \"service\": {\n",
      "        \"_type\": \"nvfoundation\"\n",
      "      },\n",
      "      \"model_name\": \"meta/llama3-70b-instruct\",\n",
      "      \"max_tokens\": 2000,\n",
      "      \"temperature\": 0,\n",
      "      \"top_p\": 0.01,\n",
      "      \"seed\": 42\n",
      "    },\n",
      "    \"justification_model\": {\n",
      "      \"model_name\": \"meta/llama3-70b-instruct\",\n",
      "      \"service\": {\n",
      "        \"_type\": \"nvfoundation\"\n",
      "      },\n",
      "      \"max_tokens\": 1024,\n",
      "      \"temperature\": 0,\n",
      "      \"top_p\": 0.01,\n",
      "      \"seed\": 42\n",
      "    },\n",
      "    \"rag_embedding\": {\n",
      "      \"_type\": \"nim\",\n",
      "      \"model\": \"nvidia/nv-embedqa-e5-v5\",\n",
      "      \"truncate\": \"END\",\n",
      "      \"max_batch_size\": 128\n",
      "    },\n",
      "    \"summary_model\": {\n",
      "      \"model_name\": \"meta/llama3-70b-instruct\",\n",
      "      \"service\": {\n",
      "        \"_type\": \"nvfoundation\"\n",
      "      },\n",
      "      \"max_tokens\": 1024,\n",
      "      \"temperature\": 0,\n",
      "      \"top_p\": 0.01,\n",
      "      \"seed\": 42\n",
      "    }\n",
      "  },\n",
      "  \"general\": {\n",
      "    \"cache_dir\": null,\n",
      "    \"base_vdb_dir\": \".cache/am_cache/vdb\",\n",
      "    \"base_git_dir\": \".cache/am_cache/git\",\n",
      "    \"max_retries\": 5,\n",
      "    \"model_max_batch_size\": 64,\n",
      "    \"pipeline_batch_size\": 1024,\n",
      "    \"use_uvloop\": true\n",
      "  },\n",
      "  \"input\": {\n",
      "    \"_type\": \"http\",\n",
      "    \"port\": 26466,\n",
      "    \"address\": \"0.0.0.0\"\n",
      "  },\n",
      "  \"output\": {\n",
      "    \"_type\": \"file\",\n",
      "    \"file_path\": \".tmp/output.json\",\n",
      "    \"markdown_dir\": \".tmp/vulnerability_markdown_reports\",\n",
      "    \"overwrite\": true\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "with open('configs/from_http.json', 'r') as config_in:\n",
    "    http_config = json.load(config_in)\n",
    "print(json.dumps(http_config, indent=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configuring the HTTP server"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# The default container port is 26466. If another port is required this can be adjusted in the Docker compose file\n",
    "# and the container can be re-built or the desired port mapping can be specified when starting the container.\n",
    "input_port = 26466\n",
    "input_address = \"0.0.0.0\"\n",
    "output_type = \"file\"\n",
    "output_file_path = \".tmp/quick_start_results.json\"\n",
    "\n",
    "# Update the default http_configuration with our custom values\n",
    "http_config['input']['port'] = input_port\n",
    "http_config['input']['address'] = input_address\n",
    "\n",
    "http_config['output']['_type'] = output_type\n",
    "http_config['output']['file_path'] = output_file_path\n",
    "\n",
    "# Save the updated http configuration file to the .tmp/ directory\n",
    "config_path = \".tmp/http_config.json\"\n",
    "os.makedirs(os.path.dirname(config_path), exist_ok=True)\n",
    "with open(config_path, \"w\") as config_out:\n",
    "    json.dump(http_config, config_out, indent=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Starting the HTTP server"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pull up the bash shell for the container and run the following command:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```bash\n",
    "python src/main.py --log_level DEBUG cve pipeline --config_file=.tmp/http_config.json\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once you see the \n",
    "\n",
    "`====Building Segment Complete!====` \n",
    "\n",
    "message, HTTP requests can be sent to the server."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sending Workflow Requests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup input message for HTTP server"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"image\": {\n",
      "    \"name\": \"nvcr.io/nvidia/morpheus/morpheus\",\n",
      "    \"tag\": \"23.11-runtime\",\n",
      "    \"source_info\": [\n",
      "      {\n",
      "        \"type\": \"code\",\n",
      "        \"git_repo\": \"https://github.com/nv-morpheus/Morpheus.git\",\n",
      "        \"tag\": \"v23.11.01\",\n",
      "        \"include\": [\n",
      "          \"**/*.cpp\",\n",
      "          \"**/*.cu\",\n",
      "          \"**/*.cuh\",\n",
      "          \"**/*.h\",\n",
      "          \"**/*.hpp\",\n",
      "          \"**/*.ipynb\",\n",
      "          \"**/*.py\",\n",
      "          \"**/*Dockerfile\"\n",
      "        ],\n",
      "        \"exclude\": [\n",
      "          \"tests/**/*\"\n",
      "        ]\n",
      "      },\n",
      "      {\n",
      "        \"type\": \"doc\",\n",
      "        \"git_repo\": \"https://github.com/nv-morpheus/Morpheus.git\",\n",
      "        \"tag\": \"v23.11.01\",\n",
      "        \"include\": [\n",
      "          \"**/*.md\",\n",
      "          \"docs/**/*.rst\"\n",
      "        ]\n",
      "      }\n",
      "    ],\n",
      "    \"sbom_info\": {\n",
      "      \"_type\": \"file\",\n",
      "      \"file_path\": \"data/sboms/nvcr.io/nvidia/morpheus/morpheus:v23.11.01-runtime.sbom\"\n",
      "    }\n",
      "  },\n",
      "  \"scan\": {\n",
      "    \"vulns\": [\n",
      "      {\n",
      "        \"vuln_id\": \"GHSA-3f63-hfp8-52jq\"\n",
      "      },\n",
      "      {\n",
      "        \"vuln_id\": \"CVE-2023-50782\"\n",
      "      },\n",
      "      {\n",
      "        \"vuln_id\": \"CVE-2023-36632\"\n",
      "      },\n",
      "      {\n",
      "        \"vuln_id\": \"CVE-2023-43804\"\n",
      "      },\n",
      "      {\n",
      "        \"vuln_id\": \"GHSA-cxfr-5q3r-2rc2\"\n",
      "      },\n",
      "      {\n",
      "        \"vuln_id\": \"GHSA-554w-xh4j-8w64\"\n",
      "      },\n",
      "      {\n",
      "        \"vuln_id\": \"GHSA-3ww4-gg4f-jr7f\"\n",
      "      }\n",
      "    ]\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "with open('data/input_messages/morpheus:23.11-runtime.json', 'r') as input_message_in:\n",
    "    input_message = json.load(input_message_in)\n",
    "print(json.dumps(input_message, indent=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set up source code and documentation for vector database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "source_code_repo = \"https://github.com/nv-morpheus/Morpheus.git\"\n",
    "source_code_tag = \"v23.11.01\"\n",
    "doc_repo = \"https://github.com/nv-morpheus/Morpheus.git\"\n",
    "doc_tag = \"v23.11.01\"\n",
    "\n",
    "input_message[\"image\"][\"source_info\"] = [\n",
    "    {\n",
    "        \"type\": \"code\",\n",
    "        \"git_repo\": source_code_repo,\n",
    "        \"tag\": source_code_tag,\n",
    "        \"include\": [\"**/*.cpp\", \"**/*.cu\", \"**/*.cuh\", \"**/*.h\", \"**/*.hpp\", \"**/*.ipynb\", \"**/*.py\", \"**/*Dockerfile\"],\n",
    "        \"exclude\": [\"tests/**/*\"]\n",
    "    },\n",
    "    {\n",
    "        \"type\": \"doc\", \"git_repo\": doc_repo, \"tag\": doc_tag, \"include\": [\"**/*.md\", \"docs/**/*.rst\"]\n",
    "    },\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set up SBOM and list of vulnerabilities to analyze"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "input_message[\"image\"][\"sbom_info\"][\"file_path\"] = sbom_file\n",
    "\n",
    "vuln_list = [\n",
    "    \"CVE-2024-21762\",  # irrelevant to the Morpheus container\n",
    "    \"GHSA-hh8p-p8mp-gqhm\",  # vulnerable package in use\n",
    "    \"GHSA-3f63-hfp8-52jq\",  # vulnerable code included in the environment but not executed during runtime\n",
    "]\n",
    "vuln_entry = [{\"vuln_id\": vuln} for vuln in vuln_list]\n",
    "input_message[\"scan\"][\"vulns\"] = vuln_entry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"image\": {\n",
      "    \"name\": \"nvcr.io/nvidia/morpheus/morpheus\",\n",
      "    \"tag\": \"23.11-runtime\",\n",
      "    \"source_info\": [\n",
      "      {\n",
      "        \"type\": \"code\",\n",
      "        \"git_repo\": \"https://github.com/nv-morpheus/Morpheus.git\",\n",
      "        \"tag\": \"v23.11.01\",\n",
      "        \"include\": [\n",
      "          \"**/*.cpp\",\n",
      "          \"**/*.cu\",\n",
      "          \"**/*.cuh\",\n",
      "          \"**/*.h\",\n",
      "          \"**/*.hpp\",\n",
      "          \"**/*.ipynb\",\n",
      "          \"**/*.py\",\n",
      "          \"**/*Dockerfile\"\n",
      "        ],\n",
      "        \"exclude\": [\n",
      "          \"tests/**/*\"\n",
      "        ]\n",
      "      },\n",
      "      {\n",
      "        \"type\": \"doc\",\n",
      "        \"git_repo\": \"https://github.com/nv-morpheus/Morpheus.git\",\n",
      "        \"tag\": \"v23.11.01\",\n",
      "        \"include\": [\n",
      "          \"**/*.md\",\n",
      "          \"docs/**/*.rst\"\n",
      "        ]\n",
      "      }\n",
      "    ],\n",
      "    \"sbom_info\": {\n",
      "      \"_type\": \"file\",\n",
      "      \"file_path\": \"data/sboms/nvcr.io/nvidia/morpheus/morpheus:v23.11.01-runtime.sbom\"\n",
      "    }\n",
      "  },\n",
      "  \"scan\": {\n",
      "    \"vulns\": [\n",
      "      {\n",
      "        \"vuln_id\": \"CVE-2024-21762\"\n",
      "      },\n",
      "      {\n",
      "        \"vuln_id\": \"GHSA-hh8p-p8mp-gqhm\"\n",
      "      },\n",
      "      {\n",
      "        \"vuln_id\": \"GHSA-3f63-hfp8-52jq\"\n",
      "      }\n",
      "    ]\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "print(json.dumps(input_message, indent=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This command sends a request with the input message to the running HTTP server. You should be able to see the logs from the pipeline in the console."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [201]>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "requests.post(f\"http://localhost:{input_port}/scan\", json=input_message)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An overview of each provided CVE's affected status and vulnerability label will be printed to the logs upon completion of the pipeline, for example:\n",
    "\n",
    "```\n",
    "Vulnerability 'CVE-2024-21762' affected status: FALSE. Label: code_not_present\n",
    "Vulnerability 'GHSA-hh8p-p8mp-gqhm' affected status: TRUE. Label: vulnerable\n",
    "Vulnerability 'GHSA-3f63-hfp8-52jq' affected status: FALSE. Label: code_not_reachable\n",
    "```\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "    <b>Note:</b> The output you receive from the pipeline may not be identical as the output in the example above. The output may vary due to the non-deterministic nature of the LLM models.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Additional inputs can be sent to the HTTP server and the results will be appended to the output file until the server is shut down.\n",
    "\n",
    "<div class=\"alert alert-block alert-warning\">\n",
    "    <b>Note:</b> Please wait until the pipeline execution is finished before proceeding to the next section.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Processing Results\n",
    "## Output schema\n",
    "### 1. `input`\n",
    "This section captures the details about the target of the vulnerability investigation. It includes subsections for the security scan and information on the scanned container image. It is structured as follows:\n",
    "\n",
    "- `scan`: Details about the security scan and the vulnerabilities discovered for the system to investigate. Many of the fields are null in illustrative example input. These fields can be populated with security scan metadata when integrating scan results as the HTTP input source.\n",
    "  - `id`: ID for the scan.\n",
    "  - `type`: Scan type.\n",
    "  - `started_at` and `completed_at`: Timestamps indicating scan start and end.\n",
    "  - `vulns`: Array of detected vulnerabilities, each described with details including `vuln_id`, severity, description, and package-specific data.\n",
    "\n",
    "- `image`: Specifies the container image analyzed in this scan. This information is directly parsed from the input message we posted.\n",
    "\n",
    "### 2. `info`\n",
    "This section provides metadata and intel on vulnerabilities gathered from threat databases and advisories.\n",
    "\n",
    "- `vdb`: Paths to vulnerability vector databases used for code (`code_vdb_path`) and documentation (`doc_vdb_path`) relevant to the container.\n",
    "\n",
    "- `intel`: Vulnerability intel that groups vulnerabilities by their IDs.\n",
    "  - `vuln_id`: Identifier for each vulnerability.\n",
    "  - `ghsa`, `nvd`, `rhsa`, `ubuntu`: Subsections providing detailed advisories from different vulnerability databases:\n",
    "    - Details like `cve_id`, `severity`, `summary`, `description`, `cwes` explain the nature of the vulnerability and provide information on affected versions, available patches, publication dates, severity, and other relevant details.\n",
    "    - Depending on the intel source, information about specific configurations or environments where the vulnerabilities may occur could also be included.\n",
    "\n",
    "- `sbom`(Software Bill of Materials): Lists packages used in the container.\n",
    "  - Each package contains fields like `name`, `version`, `path`, and `system`.\n",
    "\n",
    "- `vulnerable_dependencies`: Lists dependencies in the container that match identified vulnerabilities.\n",
    "  - For each vulnerability (`vuln_id`), this section lists vulnerable SBOM packages, identifying any affected packages and their versions.\n",
    "\n",
    "### 3. `output`\n",
    "The output section captures the results of the vulnerability investigation from the agentic system.\n",
    "\n",
    "- `vuln_id`: Identifier for each vulnerability.\n",
    "- `checklist`: Detailed investigative steps and results for investigating each vulnerability's exploitability.\n",
    "  - `input`: The checklist item for the agent to investigate.\n",
    "  - `response`: The agent's finding and conclusion for the checklist item.\n",
    "  - `intermediate_steps`: (Optional) Additional information on the intermediate actions taken during the investigation by the agent. Useful for debugging and explainability.\n",
    "- `summary`: A summary of the investigation, indicating whether the vulnerability is exploitable or not, based on checklist findings.\n",
    "- `justification`: A detailed conclusion on the vulnerability's exploitability status, including:\n",
    "  - `label`: A VEX justification label for the vulnerability.\n",
    "  - `reason`: Explanation for the decision of the classification.\n",
    "  - `status`: Final boolean decision on whether the vulnerability is currently exploitable.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load results into the notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#Load first result in case multiple requests were sent\n",
    "with open(output_file_path, 'r') as result_in:\n",
    "    full_input = result_in.read()\n",
    "    offsets = [res.start() for res in re.finditer('{\"input\":{\"scan\":', full_input)]\n",
    "    offsets.append(len(full_input))\n",
    "    first_result = json.loads(full_input[offsets[0]:offsets[1]])"
   ]
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      "          \"cve_description\": \"Pillow through 10.1.0 allows PIL.ImageMath.eval Arbitrary Code Execution via the environment parameter, a different vulnerability than CVE-2022-22817 (which was about the expression parameter).\",\n",
      "          \"cvss_vector\": \"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H\",\n",
      "          \"cwe_name\": \"CWE-94: Improper Control of Generation of Code ('Code Injection') (4.15)\",\n",
      "          \"cwe_description\": \"The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.\",\n",
      "          \"cwe_extended_description\": \"When a product allows a user's input to contain code syntax, it might be possible for an attacker to craft the code in such a way that it will alter the intended control flow of the product. Such an alteration could lead to arbitrary code execution. Injection problems encompass a wide variety of issues -- all mitigated in very different ways. For this reason, the most effective way to discuss these weaknesses is to note the distinct features which classify them as injection weaknesses. The most important issue to note is that all injection problems share one thing in common -- i.e., they allow for the injection of control plane data into the user-controlled data plane. This means that the execution of the process may be altered by sending code in through legitimate data channels, using no other mechanism. While buffer overflows, and many other flaws, involve the use of some further issue to gain execution, injection problems need only for the data to be parsed. The most classic instantiations of this category of weakness are SQL injection and format string vulnerabilities.\",\n",
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      "              \"package\": \"pillow\",\n",
      "              \"system\": null,\n",
      "              \"versionStartExcluding\": null,\n",
      "              \"versionEndExcluding\": null,\n",
      "              \"versionStartIncluding\": null,\n",
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      "              \"package\": \"debian_linux\",\n",
      "              \"system\": null,\n",
      "              \"versionStartExcluding\": null,\n",
      "              \"versionEndExcluding\": null,\n",
      "              \"versionStartIncluding\": \"10.0\",\n",
      "              \"versionEndIncluding\": \"10.0\"\n",
      "            }\n",
      "          ],\n",
      "          \"vendor_names\": [\n",
      "            \"Debian\",\n",
      "            \"Python\"\n",
      "          ]\n",
      "        },\n",
      "        \"rhsa\": {\n",
      "          \"bugzilla\": {\n",
      "            \"description\": \"pillow: Arbitrary Code Execution via the environment parameter\",\n",
      "            \"id\": \"2259479\",\n",
      "            \"url\": \"https://bugzilla.redhat.com/show_bug.cgi?id=2259479\"\n",
      "          },\n",
      "          \"details\": [\n",
      "            \"Pillow through 10.1.0 allows PIL.ImageMath.eval Arbitrary Code Execution via the environment parameter, a different vulnerability than CVE-2022-22817 (which was about the expression parameter).\",\n",
      "            \"A vulnerability was found in Pillow, a popular Python imaging library. The flaw identified in the PIL.ImageMath.eval function enables arbitrary code execution by manipulating the environment parameter.\"\n",
      "          ],\n",
      "          \"statement\": \"The vulnerability in Pillow's PIL.ImageMath.eval function poses a significant threat due to its potential for arbitrary code execution. Pillow's widespread use in diverse domains makes this flaw particularly impactful, as it could lead to unauthorized access, data breaches, and compromise of entire systems. The complex exploitation method involving Python's dunder methods adds sophistication to potential attacks.\",\n",
      "          \"package_state\": null,\n",
      "          \"upstream_fix\": null,\n",
      "          \"threat_severity\": \"Important\",\n",
      "          \"public_date\": \"2024-01-19T00:00:00Z\",\n",
      "          \"cvss3\": {\n",
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      "            \"cvss3_scoring_vector\": \"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H\",\n",
      "            \"status\": \"verified\"\n",
      "          },\n",
      "          \"cwe\": \"CWE-77\",\n",
      "          \"affected_release\": [\n",
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      "              \"release_date\": \"2024-06-10T00:00:00Z\",\n",
      "              \"advisory\": \"RHSA-2024:3781\",\n",
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      "              \"release_date\": \"2024-06-10T00:00:00Z\",\n",
      "              \"advisory\": \"RHSA-2024:3781\",\n",
      "              \"cpe\": \"cpe:/a:redhat:ansible_automation_platform:2.4::el9\",\n",
      "              \"package\": \"python-pillow-0:10.3.0-1.el9ap\"\n",
      "            },\n",
      "            {\n",
      "              \"product_name\": \"Red Hat Enterprise Linux 7\",\n",
      "              \"release_date\": \"2024-02-19T00:00:00Z\",\n",
      "              \"advisory\": \"RHSA-2024:0857\",\n",
      "              \"cpe\": \"cpe:/o:redhat:enterprise_linux:7\",\n",
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      "            },\n",
      "            {\n",
      "              \"product_name\": \"Red Hat Enterprise Linux 8\",\n",
      "              \"release_date\": \"2024-02-20T00:00:00Z\",\n",
      "              \"advisory\": \"RHSA-2024:0893\",\n",
      "              \"cpe\": \"cpe:/a:redhat:enterprise_linux:8\",\n",
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      "            },\n",
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      "              \"product_name\": \"Red Hat Enterprise Linux 8.2 Advanced Update Support\",\n",
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      "              \"advisory\": \"RHSA-2024:1059\",\n",
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      "              \"package\": \"python-pillow-0:5.1.1-15.el8_4\"\n",
      "            },\n",
      "            {\n",
      "              \"product_name\": \"Red Hat Enterprise Linux 8.4 Telecommunications Update Service\",\n",
      "              \"release_date\": \"2024-02-29T00:00:00Z\",\n",
      "              \"advisory\": \"RHSA-2024:1060\",\n",
      "              \"cpe\": \"cpe:/a:redhat:rhel_tus:8.4\",\n",
      "              \"package\": \"python-pillow-0:5.1.1-15.el8_4\"\n",
      "            },\n",
      "            {\n",
      "              \"product_name\": \"Red Hat Enterprise Linux 8.4 Update Services for SAP Solutions\",\n",
      "              \"release_date\": \"2024-02-29T00:00:00Z\",\n",
      "              \"advisory\": \"RHSA-2024:1060\",\n",
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      "              \"advisory\": \"RHSA-2024:1058\",\n",
      "              \"cpe\": \"cpe:/a:redhat:rhel_eus:8.6\",\n",
      "              \"package\": \"python-pillow-0:5.1.1-19.el8_6\"\n",
      "            },\n",
      "            {\n",
      "              \"product_name\": \"Red Hat Enterprise Linux 8.8 Extended Update Support\",\n",
      "              \"release_date\": \"2024-02-08T00:00:00Z\",\n",
      "              \"advisory\": \"RHSA-2024:0754\",\n",
      "              \"cpe\": \"cpe:/a:redhat:rhel_eus:8.8\",\n",
      "              \"package\": \"python-pillow-0:5.1.1-19.el8_8\"\n",
      "            }\n",
      "          ],\n",
      "          \"references\": [\n",
      "            \"https://www.cve.org/CVERecord?id=CVE-2023-50447\\nhttps://nvd.nist.gov/vuln/detail/CVE-2023-50447\\nhttp://www.openwall.com/lists/oss-security/2024/01/20/1\\nhttps://devhub.checkmarx.com/cve-details/CVE-2023-50447/\\nhttps://duartecsantos.github.io/2023-01-02-CVE-2023-50447/\\nhttps://github.com/python-pillow/Pillow/releases\"\n",
      "          ],\n",
      "          \"name\": \"CVE-2023-50447\",\n",
      "          \"mitigation\": {\n",
      "            \"value\": \"Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.\",\n",
      "            \"lang\": \"en:us\"\n",
      "          },\n",
      "          \"csaw\": false\n",
      "        },\n",
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      "          \"description\": \"\\nPillow through 10.1.0 allows PIL.ImageMath.eval Arbitrary Code Execution\\nvia the environment parameter, a different vulnerability than\\nCVE-2022-22817 (which was about the expression parameter).\",\n",
      "          \"notes\": [],\n",
      "          \"priority\": \"medium\",\n",
      "          \"ubuntu_description\": \"\",\n",
      "          \"bugs\": [\n",
      "            \"http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=1061172\"\n",
      "          ],\n",
      "          \"codename\": null,\n",
      "          \"cvss3\": 8.1,\n",
      "          \"id\": \"CVE-2023-50447\",\n",
      "          \"impact\": {\n",
      "            \"baseMetricV3\": {\n",
      "              \"cvssV3\": {\n",
      "                \"attackComplexity\": \"HIGH\",\n",
      "                \"attackVector\": \"NETWORK\",\n",
      "                \"availabilityImpact\": \"HIGH\",\n",
      "                \"baseScore\": 8.1,\n",
      "                \"baseSeverity\": \"HIGH\",\n",
      "                \"confidentialityImpact\": \"HIGH\",\n",
      "                \"integrityImpact\": \"HIGH\",\n",
      "                \"privilegesRequired\": \"NONE\",\n",
      "                \"scope\": \"UNCHANGED\",\n",
      "                \"userInteraction\": \"NONE\",\n",
      "                \"vectorString\": \"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H\",\n",
      "                \"version\": \"3.1\"\n",
      "              },\n",
      "              \"exploitabilityScore\": 2.2,\n",
      "              \"impactScore\": 5.9\n",
      "            }\n",
      "          },\n",
      "          \"mitigation\": \"\",\n",
      "          \"notices\": [\n",
      "            {\n",
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      "                \"CVE-2023-44271\",\n",
      "                \"CVE-2023-50447\"\n",
      "              ],\n",
      "              \"description\": \"It was discovered that Pillow incorrectly handled certain long text\\narguments. An attacker could possibly use this issue to cause Pillow to\\nconsume resources, leading to a denial of service. This issue only affected\\nUbuntu 20.04 LTS, and Ubuntu 22.04 LTS. (CVE-2023-44271)\\n\\nDuarte Santos discovered that Pillow incorrectly handled the environment\\nparameter to PIL.ImageMath.eval. An attacker could possibly use this issue\\nto execute arbitrary code. (CVE-2023-50447)\\n\",\n",
      "              \"id\": \"USN-6618-1\",\n",
      "              \"instructions\": \"In general, a standard system update will make all the necessary changes.\\n\",\n",
      "              \"is_hidden\": false,\n",
      "              \"published\": \"2024-01-30T15:17:54.445907\",\n",
      "              \"references\": [],\n",
      "              \"release_packages\": {\n",
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      "                  },\n",
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      "                    \"is_visible\": false,\n",
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      "                    \"description\": \"Python Imaging Library\",\n",
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      "                    \"version\": \"10.0.0-1ubuntu0.1\",\n",
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      "                  },\n",
      "                  {\n",
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      "                    \"is_visible\": true,\n",
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      "                    \"source_link\": \"https://launchpad.net/ubuntu/+source/pillow\",\n",
      "                    \"version\": \"10.0.0-1ubuntu0.1\",\n",
      "                    \"version_link\": \"https://launchpad.net/ubuntu/+source/pillow/10.0.0-1ubuntu0.1\"\n",
      "                  },\n",
      "                  {\n",
      "                    \"is_source\": false,\n",
      "                    \"is_visible\": false,\n",
      "                    \"name\": \"python3-pil.imagetk\",\n",
      "                    \"pocket\": \"security\",\n",
      "                    \"source_link\": \"https://launchpad.net/ubuntu/+source/pillow\",\n",
      "                    \"version\": \"10.0.0-1ubuntu0.1\",\n",
      "                    \"version_link\": \"https://launchpad.net/ubuntu/+source/pillow/10.0.0-1ubuntu0.1\"\n",
      "                  }\n",
      "                ]\n",
      "              },\n",
      "              \"summary\": \"Several security issues were fixed in Pillow.\\n\",\n",
      "              \"title\": \"Pillow vulnerabilities\",\n",
      "              \"type\": \"USN\"\n",
      "            }\n",
      "          ],\n",
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      "            \"USN-6618-1\"\n",
      "          ],\n",
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      "                }\n",
      "              ],\n",
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      "            },\n",
      "            {\n",
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      "    },\n",
      "    \"vulnerable_dependencies\": [\n",
      "      {\n",
      "        \"vuln_id\": \"CVE-2024-21762\",\n",
      "        \"vuln_package_intel_sources\": [\n",
      "          \"nvd\"\n",
      "        ],\n",
      "        \"vulnerable_sbom_packages\": []\n",
      "      },\n",
      "      {\n",
      "        \"vuln_id\": \"GHSA-hh8p-p8mp-gqhm\",\n",
      "        \"vuln_package_intel_sources\": [\n",
      "          \"ghsa\",\n",
      "          \"nvd\"\n",
      "        ],\n",
      "        \"vulnerable_sbom_packages\": [\n",
      "          {\n",
      "            \"name\": \"mlflow\",\n",
      "            \"version\": \"2.9.1\",\n",
      "            \"vulnerable_dependency_package\": {\n",
      "              \"system\": \"python\",\n",
      "              \"name\": \"mlflow\",\n",
      "              \"version\": \"2.9.1\",\n",
      "              \"relation\": \"SELF\"\n",
      "            }\n",
      "          },\n",
      "          {\n",
      "            \"name\": \"mlflow\",\n",
      "            \"version\": \"2.9.1\",\n",
      "            \"vulnerable_dependency_package\": {\n",
      "              \"system\": \"python\",\n",
      "              \"name\": \"mlflow\",\n",
      "              \"version\": \"2.9.1\",\n",
      "              \"relation\": \"SELF\"\n",
      "            }\n",
      "          }\n",
      "        ]\n",
      "      },\n",
      "      {\n",
      "        \"vuln_id\": \"GHSA-3f63-hfp8-52jq\",\n",
      "        \"vuln_package_intel_sources\": [\n",
      "          \"ghsa\",\n",
      "          \"nvd\",\n",
      "          \"ubuntu\",\n",
      "          \"rhsa\"\n",
      "        ],\n",
      "        \"vulnerable_sbom_packages\": [\n",
      "          {\n",
      "            \"name\": \"pillow\",\n",
      "            \"version\": \"10.1.0\",\n",
      "            \"vulnerable_dependency_package\": {\n",
      "              \"system\": \"python\",\n",
      "              \"name\": \"pillow\",\n",
      "              \"version\": \"10.1.0\",\n",
      "              \"relation\": \"SELF\"\n",
      "            }\n",
      "          },\n",
      "          {\n",
      "            \"name\": \"pillow\",\n",
      "            \"version\": \"10.1.0\",\n",
      "            \"vulnerable_dependency_package\": {\n",
      "              \"system\": \"python\",\n",
      "              \"name\": \"pillow\",\n",
      "              \"version\": \"10.1.0\",\n",
      "              \"relation\": \"SELF\"\n",
      "            }\n",
      "          }\n",
      "        ]\n",
      "      }\n",
      "    ]\n",
      "  },\n",
      "  \"output\": [\n",
      "    {\n",
      "      \"vuln_id\": \"CVE-2024-21762\",\n",
      "      \"checklist\": [\n",
      "        {\n",
      "          \"input\": \"Check SBOM and dependencies for vulnerability.\",\n",
      "          \"response\": \"The VulnerableDependencyChecker did not find any vulnerable packages or dependencies in the SBOM.\",\n",
      "          \"intermediate_steps\": null\n",
      "        }\n",
      "      ],\n",
      "      \"summary\": \"The VulnerableDependencyChecker did not find any vulnerable packages or dependencies in the SBOM.\",\n",
      "      \"justification\": {\n",
      "        \"label\": \"code_not_present\",\n",
      "        \"reason\": \"No vulnerable packages or dependencies were detected in the SBOM.\",\n",
      "        \"status\": \"FALSE\"\n",
      "      }\n",
      "    },\n",
      "    {\n",
      "      \"vuln_id\": \"GHSA-hh8p-p8mp-gqhm\",\n",
      "      \"checklist\": [\n",
      "        {\n",
      "          \"input\": \"Review mlflow Usage: Is the mlflow package actively used by applications within the container? Check for scripts or applications that rely on mlflow, particularly those that might construct pathnames using user-input data.\",\n",
      "          \"response\": \"The mlflow package is actively used by applications within the container, specifically for logging metrics. While I couldn't find any direct references to constructing pathnames using user-input data, I did find evidence of potential path traversal vulnerabilities related to mlflow, which could be a significant concern. It's recommended to review the container's codebase and dependencies to ensure that mlflow is used securely and that any potential vulnerabilities are addressed.\",\n",
      "          \"intermediate_steps\": null\n",
      "        },\n",
      "        {\n",
      "          \"input\": \"Inspect Pathname Construction Logic: Does the codebase contain any usage of mlflow that constructs pathnames using external input? Focus on how pathnames are handled and whether there is a reliance on restricted directories to filter out potentially harmful path traversals.\",\n",
      "          \"response\": \"The Docker container's codebase uses mlflow, which constructs pathnames using external input. However, mlflow has had path traversal vulnerabilities in the past due to improper sanitization of user-supplied paths and insufficient input sanitization. Although these vulnerabilities may have been addressed in newer versions of mlflow, the version used in the Docker container's codebase (>=2.2.1 and <3) may still be vulnerable to path traversal attacks. Therefore, it is essential to ensure that the pathname construction logic in the Docker container's codebase properly sanitizes external input and has sufficient restrictions in place to prevent harmful path traversals.\",\n",
      "          \"intermediate_steps\": null\n",
      "        },\n",
      "        {\n",
      "          \"input\": \"Evaluate Input Validation Practices: Assess the robustness of input validation practices within the application. Since the CVE involves path traversal, are inputs, especially those used to construct pathnames, properly sanitized and validated against unexpected or malicious data, such as '..\\\\..' sequences?\",\n",
      "          \"response\": \"The input validation practices within the application are not robust enough to prevent path traversal attacks. While the `find_matching_input_for_placeholder` function performs some input validation and sanitization, it does not follow best practices in input validation and sanitization. The `process_input_names` function is not fully implemented and lacks proper input validation and sanitization. To improve the robustness of the input validation practices, the application should perform more comprehensive input validation on all function parameters, use more robust input sanitization techniques, and consider using input validation and sanitization libraries or frameworks.\",\n",
      "          \"intermediate_steps\": null\n",
      "        }\n",
      "      ],\n",
      "      \"summary\": \"Based on the provided Checklist and Findings, the CVE is exploitable. The following checklist items have definitive answers indicating exploitability: \\n\\nThe mlflow package is actively used by applications within the container, and its pathname construction logic uses external input, which may be vulnerable to path traversal attacks due to improper sanitization of user-supplied paths. Furthermore, the input validation practices within the application are not robust enough to prevent path traversal attacks, as they do not follow best practices in input validation and sanitization.\",\n",
      "      \"justification\": {\n",
      "        \"label\": \"vulnerable\",\n",
      "        \"reason\": \"The analysis indicates that the mlflow package is actively used and its pathname construction logic is vulnerable to path traversal attacks due to improper sanitization of user-supplied paths, making the package exploitable.\",\n",
      "        \"status\": \"TRUE\"\n",
      "      }\n",
      "    },\n",
      "    {\n",
      "      \"vuln_id\": \"GHSA-3f63-hfp8-52jq\",\n",
      "      \"checklist\": [\n",
      "        {\n",
      "          \"input\": \"Review Pillow Usage: Is the Pillow library actively used by applications within the container? Check for scripts or applications that rely on Pillow, particularly those that might use the `PIL.ImageMath.eval` function.\",\n",
      "          \"response\": \"Based on the investigation, it appears that the Pillow library is not actively used by applications within the container. Although Pillow is commonly used in Python applications for image processing, the code within the container does not reference Pillow or its functions, and the primary purpose of the container is for machine learning and inference, not image processing. However, it's possible that Pillow might be used as a dependency in some Python applications, but without more specific information, it cannot be confirmed.\",\n",
      "          \"intermediate_steps\": null\n",
      "        },\n",
      "        {\n",
      "          \"input\": \"Inspect Environment Parameter Handling: Does the codebase contain any usage of the `PIL.ImageMath.eval` function with the environment parameter? Focus on how the environment parameter is handled and whether it is properly sanitized and validated against malicious input.\",\n",
      "          \"response\": \"Based on the investigation, it appears that the Docker container's codebase does not contain any usage of the `PIL.ImageMath.eval` function with the environment parameter. Additionally, the container handles environment parameters by accepting environment variables that can be passed to the script, but there is no evidence of these variables being used in conjunction with the `PIL` library.\",\n",
      "          \"intermediate_steps\": null\n",
      "        },\n",
      "        {\n",
      "          \"input\": \"Evaluate Code Injection Risks: Assess the robustness of input validation practices within the application. Since the CVE involves improper control of code generation, are inputs, especially those related to the environment parameter, properly neutralized or sanitized to prevent arbitrary code execution?\",\n",
      "          \"response\": \"Based on the investigation, it appears that the application does handle environment parameters, but the validation of user inputs is not explicitly shown. There are hints that suggest input validation is being performed, such as checking the validity of input parameters and using regular expressions to validate node names. However, without more context or code, it is difficult to provide a comprehensive answer on how the application validates user inputs. Additionally, searching for external libraries or dependencies used for input validation did not yield specific results, but it highlighted the importance of input validation in securing Docker containers. Therefore, it is recommended to further investigate the application's input validation practices, especially regarding the environment parameter, to assess the robustness of input validation and prevent arbitrary code execution.\",\n",
      "          \"intermediate_steps\": null\n",
      "        }\n",
      "      ],\n",
      "      \"summary\": \"Based on the investigation results, the CVE is **not exploitable**. The definitive answers from the checklist items are: \\n\\n* The Pillow library is not actively used by applications within the container (Checklist Item 1).\\n* The codebase does not contain any usage of the `PIL.ImageMath.eval` function with the environment parameter (Checklist Item 2).\\n\\nThese findings suggest that the CVE is not exploitable in this specific context, as the vulnerable library and function are not being used.\",\n",
      "      \"justification\": {\n",
      "        \"label\": \"code_not_reachable\",\n",
      "        \"reason\": \"The CVE is not exploitable because the vulnerable library (Pillow) is not actively used by applications within the container, and the codebase does not contain any usage of the vulnerable function (`PIL.ImageMath.eval` with the environment parameter).\",\n",
      "        \"status\": \"FALSE\"\n",
      "      }\n",
      "    }\n",
      "  ]\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "print(json.dumps(first_result, indent=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Process and display relevant results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def process_results(json_file):\n",
    "    with open(json_file, 'r') as result_in:\n",
    "        full_input = result_in.read()\n",
    "    offsets = [res.start() for res in re.finditer('{\"input\":{\"scan\":', full_input)]\n",
    "    offsets.append(len(full_input))\n",
    "    outputs = [json.loads(full_input[offsets[i]:offsets[i+1]])['output'] for i in range(len(offsets)-1)]\n",
    "    flattened = (vuln_line for output in outputs for vuln_line in output)\n",
    "    df = pd.DataFrame(flattened)\n",
    "    df[['label', 'reason', 'affected']] = pd.json_normalize(df['justification'])\n",
    "    df.drop('justification', axis='columns', inplace=True)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vuln_id</th>\n",
       "      <th>checklist</th>\n",
       "      <th>summary</th>\n",
       "      <th>label</th>\n",
       "      <th>reason</th>\n",
       "      <th>affected</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CVE-2024-21762</td>\n",
       "      <td>[{'input': 'Check SBOM and dependencies for vu...</td>\n",
       "      <td>The VulnerableDependencyChecker did not find a...</td>\n",
       "      <td>code_not_present</td>\n",
       "      <td>No vulnerable packages or dependencies were de...</td>\n",
       "      <td>FALSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GHSA-hh8p-p8mp-gqhm</td>\n",
       "      <td>[{'input': 'Review mlflow Usage: Is the mlflow...</td>\n",
       "      <td>Based on the provided Checklist and Findings, ...</td>\n",
       "      <td>vulnerable</td>\n",
       "      <td>The analysis indicates that the mlflow package...</td>\n",
       "      <td>TRUE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>GHSA-3f63-hfp8-52jq</td>\n",
       "      <td>[{'input': 'Review Pillow Usage: Is the Pillow...</td>\n",
       "      <td>Based on the investigation results, the CVE is...</td>\n",
       "      <td>code_not_reachable</td>\n",
       "      <td>The CVE is not exploitable because the vulnera...</td>\n",
       "      <td>FALSE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               vuln_id                                          checklist  \\\n",
       "0       CVE-2024-21762  [{'input': 'Check SBOM and dependencies for vu...   \n",
       "1  GHSA-hh8p-p8mp-gqhm  [{'input': 'Review mlflow Usage: Is the mlflow...   \n",
       "2  GHSA-3f63-hfp8-52jq  [{'input': 'Review Pillow Usage: Is the Pillow...   \n",
       "\n",
       "                                             summary               label  \\\n",
       "0  The VulnerableDependencyChecker did not find a...    code_not_present   \n",
       "1  Based on the provided Checklist and Findings, ...          vulnerable   \n",
       "2  Based on the investigation results, the CVE is...  code_not_reachable   \n",
       "\n",
       "                                              reason affected  \n",
       "0  No vulnerable packages or dependencies were de...    FALSE  \n",
       "1  The analysis indicates that the mlflow package...     TRUE  \n",
       "2  The CVE is not exploitable because the vulnera...    FALSE  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "process_results(output_file_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## View Markdown Reports\n",
    "\n",
    "In addition to the raw JSON output object, you can also view a Markdown-formatted report for each CVE in the `.tmp/vulnerability_markdown_reports` directory. For example, the report for `GHSA-3f63-hfp8-52jq` can be viewed at `.tmp/vulnerability_markdown_reports/vulnerability_reports_morpheus_23_11-runtime/GHSA-3f63-hfp8-52jq.md`."
   ]
  }
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