pax_global_header00006660000000000000000000000064146566354460014535gustar00rootroot0000000000000052 comment=4fae4a2f7a4a6c0be271a49d676e69592c1592a7 SploitScan-0.10.5/000077500000000000000000000000001465663544600136775ustar00rootroot00000000000000SploitScan-0.10.5/.github/000077500000000000000000000000001465663544600152375ustar00rootroot00000000000000SploitScan-0.10.5/.github/workflows/000077500000000000000000000000001465663544600172745ustar00rootroot00000000000000SploitScan-0.10.5/.github/workflows/release.yml000066400000000000000000000012751465663544600214440ustar00rootroot00000000000000name: Release on: push: tags: - 'v*.*.*' jobs: build-and-publish: runs-on: ubuntu-latest steps: - name: Check out the code uses: actions/checkout@v4 - name: Set up Python uses: actions/setup-python@v5 with: python-version: '3.8' - name: Install build tools run: | python -m pip install --upgrade pip pip install build twine - name: Build the wheel run: python -m build - name: Publish to PyPI env: TWINE_USERNAME: "__token__" TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }} run: twine upload dist/* - name: Cleanup build files run: rm -rf dist build *.egg-info SploitScan-0.10.5/.gitignore000066400000000000000000000000301465663544600156600ustar00rootroot00000000000000 sploitscan/config.json SploitScan-0.10.5/CHANGELOG.md000066400000000000000000000110741465663544600155130ustar00rootroot00000000000000# πŸ“† Changelog ## [13. August 2024] - Version 0.10.5 - **General Improvements**: Prevent IndexError by checking for non-empty lists before accessing elements. ## [18. July 2024] - Version 0.10.4 - **CVE ID Export**: Fixed the display of the CVE ID not exporting in HTML. - **Enhanced CVE Retrieval**: Fixed the retrieval of missing CVE information if nested differently. ## [30. June 2024] - Version 0.10.3 - **Main Function Refactoring**: Refactored the main function into smaller, modular functions to improve maintainability and readability. - **Public Exploit Display Enhancements**: Reworked the public exploit display to include the total number of exploits and better error handling. - **Improved Error Handling**: Enhanced error handling for API key configurations and data fetching, especially for VulnCheck. ## [30. June 2024] - Version 0.10.2 - **Custom Configuration Path**: Added support for specifying a custom configuration file path using the `--config` or `-c` command-line argument. - **Platform-Specific Directories**: Added support for platform-specific (*nix, macOS, Windows) configuration directories. - **Debug Mode**: Improved debug output for configuration file loading. ## [26. June 2024] - Version 0.10 - **HackerOne Integration**: Added support for searching through HackerOne and displays if the CVE was used in any Bug Bounty program including its rank and severity distribution. - **General Improvements**: Various bug fixes. ## [24. May 2024] - Version 0.9 - **AI-Powered Risk Assessment**: Integrated OpenAI for detailed risk assessments, potential attack scenarios, mitigation recommendations, and executive summaries (needs OpenAI API key). - **CVE Information Retrieval**: Due to API rate limits and instabilities replaced NIST NVD with [CVE Program](https://github.com/CVEProject/cvelistV5). - **General Improvements**: Various bug fixes and performance improvements. ### [18. May 2024] - Version 0.8 - **HTML Export Functionality**: Introduced the ability to export vulnerability data to HTML reports. - **Packet Storm Integration**: Added support for fetching exploit data from Packet Storm. - **Enhanced Display Functions**: Added CVE_GITHUB_URL as CVE source, and functions to output the most updated CVE source. - **Code Refactoring**: Refactored code to improve maintainability and readability due to the growing code base. ## [11. May 2024] - Version 0.7 - **Nuclei Template Integration**: Added support for discovery of Nuclei templates, enhancing vulnerability data sources. - **Enhanced Display Functions**: Refined visual output across all display functions for consistency and readability. - **General Improvements**: Various bug fixes and performance improvements such as improved error handling. ## [06. May 2024] - Version 0.6.1 - **Import File Capabilities**: Added support for importing vulnerability data directly from Docker Scout scan files. ## [05. May 2024] - Version 0.6 - **Import File Capabilities**: Added support for importing vulnerability data directly from Nessus, Nexpose, and OpenVAS scan files. - **Expanded Command-Line Options**: Introduced new command-line options to specify the import file and its type. - **Robust Configuration Management**: Improved error handling for missing or malformed configuration files. - **General Improvements**: Various bug fixes and performance improvements. ## [02. March 2024] - Version 0.5 - **ExploitDB Integration**: Added support for fetching exploit data from ExploitDB. - **CVSS Enhancements**: Added support for CVSS 2 and CVSS 3.x - **Docker support** - **Code fixes** ## [28. February 2024] - Version 0.4 - **VulnCheck Integration**: Added support for fetching exploit data from VulnCheck, enhancing the exploit information available. - **API Key Configuration**: Introduced the requirement for a VulnCheck API key, specified in config.json. - **Requirements satisfied for Debian Integration** ## [17. February 2024] - Version 0.3 - **Additional Information**: Added further information such as references & vector string - **Removed**: Star count in publicly available exploits ## [15. January 2024] - Version 0.2 - **Multiple CVE Support**: Now capable of handling multiple CVE IDs in a single execution. - **JSON and CSV Export**: Added functionality to export results to JSON and CSV files. - **Enhanced CVE Display**: Improved visual differentiation and information layout for each CVE. - **Patching Priority System**: Introduced a priority rating system for patching, influenced by various factors including the availability of public exploits. ## [13th January 2024] - Version 0.1 - Initial release of SploitScan.SploitScan-0.10.5/Dockerfile000066400000000000000000000002761465663544600156760ustar00rootroot00000000000000FROM python:3.9-slim-buster WORKDIR /app COPY . /app COPY sploitscan/config.json /app/config.json RUN pip install --no-cache-dir -r requirements.txt ENTRYPOINT ["python", "sploitscan.py"] SploitScan-0.10.5/LICENSE000066400000000000000000001044711465663544600147130ustar00rootroot00000000000000GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007 Copyright (C) 2007 Free Software Foundation, Inc. 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Copyright (C) This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . Also add information on how to contact you by electronic and paper mail. If the program does terminal interaction, make it output a short notice like this when it starts in an interactive mode: Copyright (C) This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. This is free software, and you are welcome to redistribute it under certain conditions; type `show c' for details. The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License. Of course, your program's commands might be different; for a GUI interface, you would use an "about box". You should also get your employer (if you work as a programmer) or school, if any, to sign a "copyright disclaimer" for the program, if necessary. For more information on this, and how to apply and follow the GNU GPL, see . The GNU General Public License does not permit incorporating your program into proprietary programs. If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Lesser General Public License instead of this License. But first, please read . SploitScan-0.10.5/README.md000066400000000000000000000337761465663544600151760ustar00rootroot00000000000000# SploitScan ![SPLOITSCAN-LOGO](https://github.com/xaitax/SploitScan/assets/5014849/05f6641c-2279-456f-9e5a-329926529169) ## πŸ“œ Description SploitScan is a powerful and user-friendly tool designed to streamline the process of identifying exploits for known vulnerabilities and their respective exploitation probability. Empowering cybersecurity professionals with the capability to swiftly identify and apply known and test exploits. It's particularly valuable for professionals seeking to enhance their security measures or develop robust detection strategies against emerging threats. ## πŸ“– Table of contents - πŸ“œ [Description](#-description) - 🌟 [Features](#-features) - πŸ’£ [Supported Exploit Databases](#-supported-exploit-databases) - πŸ“ [Supported Vulnerability Scanner Import](#-supported-vulnerability-scanner-import) - βš™οΈ [Installation](#️-installation) - πŸš€ [Usage](#-usage) - πŸ€– [AI-Powered Risk Assessment](#-ai-powered-risk-assessment) - πŸ›‘οΈ [Patching Priority System](#️-patching-priority-system) - πŸ«±πŸΌβ€πŸ«²πŸ½ [Contributing](#-contributing) - πŸ“Œ [Author](#-author) - πŸ“š [References](#-references) ## 🌟 Features - **CVE Information Retrieval**: Fetches CVE details from the National Vulnerability Database. - **EPSS Integration**: Includes Exploit Prediction Scoring System (EPSS) data, offering a probability score for the likelihood of CVE exploitation, aiding in prioritization. - **Public Exploits Aggregation**: Gathers publicly available exploits, enhancing the understanding of vulnerabilities. - **CISA KEV**: Shows if the CVE has been listed in the Known Exploited Vulnerabilities (KEV) of CISA. - **AI-Powered Risk Assessment**: Leverages OpenAI to provide detailed risk assessments, potential attack scenarios, mitigation recommendations, and executive summaries. - **HackerOne Reports**: Shows if the CVE was used within HackerOne Bug Bounty programs including their total rank overall and severity distribution. - **Patching Priority System**: Evaluates and assigns a priority rating for patching based on various factors including public exploits availability. - **Multi-CVE Support and Export Options**: Supports multiple CVEs in a single run and allows exporting the results to HTML, JSON and CSV formats. - **Vulnerability Scanner Import**: Import vulnerability scans from popular vulnerability scanners and search directly for known exploits. - **User-Friendly Interface**: Easy to use, providing clear and concise information. - **Comprehensive Security Tool**: Ideal for quick security assessments and staying informed about recent vulnerabilities. ![sploitscan_v0 10 4](https://github.com/user-attachments/assets/4f0ff4fd-9fb4-453f-92a2-f12f41714edd) ## πŸ’£ Supported Exploit Databases - **[GitHub](https://poc-in-github.motikan2010.net/)** - **[ExploitDB](https://www.exploit-db.com/)** - **[VulnCheck](https://vulncheck.com/)** (requires a **free** VulnCheck API key) - **[Packet Storm](https://packetstormsecurity.com/)** - **[Nuclei](https://github.com/projectdiscovery/nuclei-templates)** ## πŸ“ Supported Vulnerability Scanner Import - **[Nessus](https://www.tenable.com/products/nessus) (.nessus)** - **[Nexpose](https://www.rapid7.com/products/nexpose/) (.xml)** - **[OpenVAS](https://www.openvas.org/) (.xml)** - **[Docker](https://docs.docker.com/scout/) (.json)** ## βš™οΈ Installation ### GitHub ```shell git clone https://github.com/xaitax/SploitScan.git cd sploitscan pip install -r requirements.txt ``` ### pip ```shell pip install --user sploitscan ``` ### Kali/Ubuntu/Debian ```shell apt install sploitscan ``` ### Configuration File Create a `config.json` file in one of the following locations with your API keys: - Current directory - `~/.sploitscan/` - `~/.config/sploitscan/` - `/etc/sploitscan/` - `~/Library/Application Support/sploitscan/` (macOS) - `%APPDATA%/sploitscan/` (Windows) You can also specify a custom configuration file path using the `--config` or `-c` command-line argument. ```json { "vulncheck_api_key": "your_vulncheck_api_key", "openai_api_key": "your_openai_api_key" } ``` ## πŸš€ Usage ```shell $ sploitscan.py -h β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•— β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•”β•β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘β•šβ•β•β–ˆβ–ˆβ•”β•β•β•β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β–ˆβ–ˆβ•— β–ˆβ–ˆβ•‘ β•šβ•β•β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β•β• β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β•šβ•β•β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β•šβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β•šβ–ˆβ–ˆβ–ˆβ–ˆβ•‘ β•šβ•β•β•β•β•β•β•β•šβ•β• β•šβ•β•β•β•β•β•β• β•šβ•β•β•β•β•β• β•šβ•β• β•šβ•β• β•šβ•β•β•β•β•β•β• β•šβ•β•β•β•β•β•β•šβ•β• β•šβ•β•β•šβ•β• β•šβ•β•β•β• v0.10.3 / Alexander Hagenah / @xaitax / ah@primepage.de usage: sploitscan.py [-h] [-e {json,JSON,csv,CSV,html,HTML}] [-t {nessus,nexpose,openvas,docker}] [-i IMPORT_FILE] [-c CONFIG] [-d] [cve_ids ...] SploitScan: Retrieve and display vulnerability data as well as public exploits for given CVE ID(s). positional arguments: cve_ids Enter one or more CVE IDs to fetch data. Separate multiple CVE IDs with spaces. Format for each ID: CVE-YYYY-NNNNN. This argument is optional if an import file is provided using the -i option. options: -h, --help show this help message and exit -e {json,JSON,csv,CSV,html,HTML}, --export {json,JSON,csv,CSV,html,HTML} Optional: Export the results to a JSON, CSV, or HTML file. Specify the format: 'json', 'csv', or 'html'. -t {nessus,nexpose,openvas,docker}, --type {nessus,nexpose,openvas,docker} Specify the type of the import file: 'nessus', 'nexpose', 'openvas' or 'docker'. -i IMPORT_FILE, --import-file IMPORT_FILE Path to an import file from a vulnerability scanner. If used, CVE IDs can be omitted from the command line arguments. -c CONFIG, --config CONFIG Path to a custom config file. -d, --debug Enable debug output. ``` ### Single CVE Query ```bash sploitscan CVE-2024-1709 ``` ### Multiple CVE Query ```bash sploitscan CVE-2024-1709 CVE-2024-21413 ``` ### Import from Vulnerability Scanner Specify the type: 'nessus', 'nexpose', 'openvas', or 'docker' and provide the file path. ```bash sploitscan --import-file path/to/yourfile.nessus --type nessus ``` ### Export Results Specify the export format: 'json', 'csv', or 'html'. ```bash sploitscan CVE-2024-1709 -e html ``` ### Docker ```shell docker build -t sploitscan . docker run --rm sploitscan CVE-2024-1709 ``` With a volume mounted from the current directory #### Windows (Powershell) ```shell docker run -v ${PWD}:/app --rm sploitscan CVE-2024-1709 -e JSON ``` #### Linux ```shell docker run -v $(pwd):/app --rm sploitscan CVE-2024-1709 -e JSON ``` ## πŸ€– AI-Powered Risk Assessment SploitScan integrates with OpenAI to provide a comprehensive AI-powered risk assessment for each CVE. This feature includes: - Detailed Risk Assessment: Understand the nature of the vulnerability and its business impact. - Potential Attack Scenarios: Get descriptions of potential attack scenarios leveraging the vulnerability. - Mitigation Recommendations: Receive specific, actionable recommendations to mitigate the risk. - Executive Summary: A concise summary accessible to non-technical stakeholders, highlighting the business impact and urgency. ### Example output ```text $ sploitscan.py CVE-2024-21413 [...] β”Œβ”€β”€β”€[ πŸ€– AI-Powered Risk Assessment ] | | 1. Risk Assessment | ------------------- | The vulnerability identified by CVE-2024-21413 is a critical remote code execution flaw in | Microsoft Outlook with a CVSS score of 9.8. The impact on business operations can be severe due to | its high potential to be exploited over a network without any user interactions or elevated | privileges. This unvalidated input vulnerability (CWE-20) could allow an attacker to execute | arbitrary code on the target system, thereby compromising the confidentiality, integrity, and | availability of critical business data and systems. Given its critical rating and the existence of | multiple exploits on public repositories like GitHub, the likelihood of exploitation is very high. | This necessitates immediate attention from the security teams to mitigate the risks associated. | | 2. Potential Attack Scenarios | ------------------------------ | An attacker could exploit this vulnerability by sending a specially crafted email to a victim | using Microsoft Outlook. Once the email is opened or previewed, the malicious payload would | execute, allowing the attacker to gain control over the victim's system. The process involves: 1. | Crafting a malicious email leveraging the specific flaw in email handling within Microsoft | Outlook. 2. Sending the email to the intended victim. 3. Upon opening or previewing the email, the | victim’s system executes the malicious code. The potential outcomes of this attack include theft | of sensitive information, installation of malware or ransomware, and compromising other systems | within the same network due to lateral movement capabilities. | | 3. Mitigation Recommendations | ------------------------------ | Immediate mitigation recommendation includes: 1. Applying the latest security patches provided by | Microsoft. Reference: https://msrc.microsoft.com/update-guide/vulnerability/CVE-2024-21413 2. | Implementing network-level protections such as email filtering and network segmentation to limit | the spread of potential infections. 3. Conducting regular security awareness training for users to | recognize phishing and malicious emails. 4. Monitoring network and system activity for signs of | suspicious behavior and unauthorized execution. 5. Regularly backing up critical data and ensuring | the integrity of backups. | | 4. Executive Summary | --------------------- | CVE-2024-21413, a critical remote code execution vulnerability in Microsoft Outlook, poses a | significant risk to businesses due to its potential to be exploited without user interaction. | Multiple exploit proofs are publicly available, increasing the likelihood of attacks. | Organizations must act swiftly by applying the necessary patches from Microsoft, enhancing their | email security protocols, and educating their staff to identify potential phishing attempts. | Mitigating this vulnerability is essential to protect sensitive information, maintain business | integrity, and ensure system availability, thus preventing potential financial and reputational | damage. Immediate action is crucial to safeguard the organization against this severe threat. | └──────────────────────────────────────── ``` ## πŸ›‘οΈ Patching Priority System The Patching Prioritization System in SploitScan provides a strategic approach to prioritizing security patches based on the severity and exploitability of vulnerabilities. It's influenced by the model from [CVE Prioritizer](https://github.com/TURROKS/CVE_Prioritizer), with enhancements for handling publicly available exploits. Here's how it works: - A+ Priority: Assigned to CVEs listed in CISA's KEV or those with publicly available exploits. This reflects the highest risk and urgency for patching. - A to D Priority: Based on a combination of CVSS scores and EPSS probability percentages. The decision matrix is as follows: - A: CVSS score >= 6.0 and EPSS score >= 0.2. High severity with a significant probability of exploitation. - B: CVSS score >= 6.0 but EPSS score < 0.2. High severity but lower probability of exploitation. - C: CVSS score < 6.0 and EPSS score >= 0.2. Lower severity but higher probability of exploitation. - D: CVSS score < 6.0 and EPSS score < 0.2. Lower severity and lower probability of exploitation. This system assists users in making informed decisions on which vulnerabilities to patch first, considering both their potential impact and the likelihood of exploitation. Thresholds can be changed to your business needs. ## πŸ«±πŸΌβ€πŸ«²πŸ½ Contributing Contributions are welcome. Please feel free to fork, modify, and make pull requests or report issues. Special thanks to: - [Nilsonfsilva](https://github.com/Nilsonfsilva) for support on Debian packaging. - [bcoles](https://github.com/bcoles) for bugfixes. - [Javier Álvarez](https://github.com/jalvarezz13) for bugfixes. - [Romullo](https://github.com/Romullo) for ideas & suggestions. - [davidfortytwo](https://github.com/davidfortytwo) for enhancements (Updated CVE retrieval and PacketStorm addition). - [con-f-use](https://github.com/con-f-use) for support and fixes with setuptools/PyPi. - [Martijn Russchen](https://github.com/martijnrusschen) for his feedback and idea on HackerOne GraphQL. ## πŸ“Œ Author ### Alexander Hagenah - [URL](https://primepage.de) - [Twitter](https://twitter.com/xaitax) - [LinkedIn](https://www.linkedin.com/in/alexhagenah) ## πŸ“š References - [CISA Known Exploited Vulnerabilities Catalog](https://www.cisa.gov/known-exploited-vulnerabilities-catalog) - [CVE Program](https://github.com/CVEProject/cvelistV5) - [ExploitDB](https://www.exploit-db.com/) - [FIRST EPSS](https://www.first.org/epss/api) - [HackerOne](https://hackerone.com/) - [nomi-sec PoC-in-GitHub API](https://poc-in-github.motikan2010.net/) - [OpenAI](https://openai.com/) - [Packet Storm](https://packetstormsecurity.com/) - [ProjectDiscovery Nuclei](https://github.com/projectdiscovery/nuclei-templates) - [VulnCheck](https://vulncheck.com/) SploitScan-0.10.5/docs/000077500000000000000000000000001465663544600146275ustar00rootroot00000000000000SploitScan-0.10.5/docs/sploitscan.1000066400000000000000000000455001465663544600170740ustar00rootroot00000000000000.TH SploitScan 1 "Version 0.10.1" "SploitScan user manual" .SH NAME \fBSploitScan\fP - A tool to fetch and display vulnerability information and public exploits for given CVE IDs. .PP .SH πŸ“œ Description .PP SploitScan is a powerful and user\-friendly tool designed to streamline the process of identifying exploits for known vulnerabilities and their respective exploitation probability. Empowering cybersecurity professionals with the capability to swiftly identify and apply known and test exploits. It's particularly valuable for professionals seeking to enhance their security measures or develop robust detection strategies against emerging threats. .SH πŸ“– Table of contents .RS .IP \(bu 2 πŸ“œ Description \[la]#-description\[ra] .IP \(bu 2 🌟 Features \[la]#-features\[ra] .IP \(bu 2 πŸ’£ Supported Exploit Databases \[la]#-supported-exploit-databases\[ra] .IP \(bu 2 πŸ“ Supported Vulnerability Scanner Import \[la]#-supported-vulnerability-scanner-import\[ra] .IP \(bu 2 βš™οΈ Installation \[la]#️-installation\[ra] .IP \(bu 2 πŸš€ Usage \[la]#-usage\[ra] .IP \(bu 2 πŸ€– AI\-Powered Risk Assessment \[la]#-ai-powered-risk-assessment\[ra] .IP \(bu 2 πŸ›‘οΈ Patching Priority System \[la]#️-patching-priority-system\[ra] .IP \(bu 2 πŸ“† Changelog \[la]#-changelog\[ra] .IP \(bu 2 πŸ«±πŸΌβ€πŸ«²πŸ½ Contributing \[la]#-contributing\[ra] .IP \(bu 2 πŸ“Œ Author \[la]#-author\[ra] .IP \(bu 2 πŸ“š References \[la]#-references\[ra] .RE .SH 🌟 Features .RS .IP \(bu 2 \fBCVE Information Retrieval\fP: Fetches CVE details from the National Vulnerability Database. .IP \(bu 2 \fBEPSS Integration\fP: Includes Exploit Prediction Scoring System (EPSS) data, offering a probability score for the likelihood of CVE exploitation, aiding in prioritization. .IP \(bu 2 \fBPublic Exploits Aggregation\fP: Gathers publicly available exploits, enhancing the understanding of vulnerabilities. .IP \(bu 2 \fBCISA KEV\fP: Shows if the CVE has been listed in the Known Exploited Vulnerabilities (KEV) of CISA. .IP \(bu 2 \fBAI\-Powered Risk Assessment\fP: Leverages OpenAI to provide detailed risk assessments, potential attack scenarios, mitigation recommendations, and executive summaries. .IP \(bu 2 \fBHackerOne Reports\fP: Shows if the CVE was used within HackerOne Bug Bounty programs including their total rank overall and severity distribution. .IP \(bu 2 \fBPatching Priority System\fP: Evaluates and assigns a priority rating for patching based on various factors including public exploits availability. .IP \(bu 2 \fBMulti\-CVE Support and Export Options\fP: Supports multiple CVEs in a single run and allows exporting the results to HTML, JSON and CSV formats. .IP \(bu 2 \fBVulnerability Scanner Import\fP: Import vulnerability scans from popular vulnerability scanners and search directly for known exploits. .IP \(bu 2 \fBUser\-Friendly Interface\fP: Easy to use, providing clear and concise information. .IP \(bu 2 \fBComprehensive Security Tool\fP: Ideal for quick security assessments and staying informed about recent vulnerabilities. .RE .SH πŸ’£ Supported Exploit Databases .RS .IP \(bu 2 \fBGitHub \[la]https://poc-in-github.motikan2010.net/\[ra]\fP .IP \(bu 2 \fBExploitDB \[la]https://www.exploit-db.com/\[ra]\fP .IP \(bu 2 \fBVulnCheck \[la]https://vulncheck.com/\[ra]\fP (requires a \fBfree\fP VulnCheck API key) .IP \(bu 2 \fBPacket Storm \[la]https://packetstormsecurity.com/\[ra]\fP .IP \(bu 2 \fBNuclei \[la]https://github.com/projectdiscovery/nuclei-templates\[ra]\fP .RE .SH πŸ“ Supported Vulnerability Scanner Import .RS .IP \(bu 2 \fBNessus \[la]https://www.tenable.com/products/nessus\[ra] (.nessus)\fP .IP \(bu 2 \fBNexpose \[la]https://www.rapid7.com/products/nexpose/\[ra] (.xml)\fP .IP \(bu 2 \fBOpenVAS \[la]https://www.openvas.org/\[ra] (.xml)\fP .IP \(bu 2 \fBDocker \[la]https://docs.docker.com/scout/\[ra] (.json)\fP .RE .SH βš™οΈ Installation .SS GitHub .PP .RS .nf git clone https://github.com/xaitax/SploitScan.git cd sploitscan pip install \-r requirements.txt .fi .RE .SS pip .PP .RS .nf pip install \-\-user sploitscan .fi .RE .SS Kali/Ubuntu/Debian .PP .RS .nf apt install sploitscan .fi .RE .SS Configuration File .PP Create a \fB\fCconfig.json\fR file in one of the following locations with your API keys: .RS .IP \(bu 2 Current directory .IP \(bu 2 \fB\fC~/.sploitscan/\fR .IP \(bu 2 \fB\fC~/.config/sploitscan/\fR .IP \(bu 2 \fB\fC/etc/sploitscan/\fR .RE .PP .RS .nf { "vulncheck_api_key": "your_vulncheck_api_key", "openai_api_key": "your_openai_api_key" } .fi .RE .SH πŸš€ Usage .PP .RS .nf $ sploitscan.py \-h β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•— β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•”β•β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘β•šβ•β•β–ˆβ–ˆβ•”β•β•β•β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β–ˆβ–ˆβ•— β–ˆβ–ˆβ•‘ β•šβ•β•β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β•β• β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β•šβ•β•β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β•šβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β•šβ–ˆβ–ˆβ–ˆβ–ˆβ•‘ β•šβ•β•β•β•β•β•β•β•šβ•β• β•šβ•β•β•β•β•β•β• β•šβ•β•β•β•β•β• β•šβ•β• β•šβ•β• β•šβ•β•β•β•β•β•β• β•šβ•β•β•β•β•β•β•šβ•β• β•šβ•β•β•šβ•β• β•šβ•β•β•β• v0.10.1 / Alexander Hagenah / @xaitax / ah@primepage.de usage: sploitscan.py [\-h] [\-e {json,JSON,csv,CSV,html,HTML}] [\-t {nessus,nexpose,openvas,docker}] [\-i IMPORT_FILE] [\-d] [cve_ids ...] SploitScan: Retrieve and display vulnerability data as well as public exploits for given CVE ID(s). positional arguments: cve_ids Enter one or more CVE IDs to fetch data. Separate multiple CVE IDs with spaces. Format for each ID: CVE\-YYYY\-NNNNN. This argument is optional if an import file is provided using the \-n option. options: \-h, \-\-help show this help message and exit \-e {json,JSON,csv,CSV,html,HTML}, \-\-export {json,JSON,csv,CSV,html,HTML} Optional: Export the results to a JSON, CSV, or HTML file. Specify the format: 'json', 'csv', or 'html'. \-t {nessus,nexpose,openvas,docker}, \-\-type {nessus,nexpose,openvas,docker} Specify the type of the import file: 'nessus', 'nexpose', 'openvas' or 'docker'. \-i IMPORT_FILE, \-\-import\-file IMPORT_FILE Path to an import file from a vulnerability scanner. If used, CVE IDs can be omitted from the command line arguments. \-d, \-\-debug Enable debug output. .fi .RE .SS Single CVE Query .PP .RS .nf sploitscan CVE\-2024\-1709 .fi .RE .SS Multiple CVE Query .PP .RS .nf sploitscan CVE\-2024\-1709 CVE\-2024\-21413 .fi .RE .SS Import from Vulnerability Scanner .PP Specify the type: 'nessus', 'nexpose', 'openvas', or 'docker' and provide the file path. .PP .RS .nf sploitscan \-\-import\-file path/to/yourfile.nessus \-\-type nessus .fi .RE .SS Export Results .PP Specify the export format: 'json', 'csv', or 'html'. .PP .RS .nf sploitscan CVE\-2024\-1709 \-e html .fi .RE .SS Docker .PP .RS .nf docker build \-t sploitscan . docker run \-\-rm sploitscan CVE\-2024\-1709 .fi .RE .PP With a volume mounted from the current directory .SS Windows (Powershell) .PP .RS .nf docker run \-v ${PWD}:/app \-\-rm sploitscan CVE\-2024\-1709 \-e JSON .fi .RE .SS Linux .PP .RS .nf docker run \-v $(pwd):/app \-\-rm sploitscan CVE\-2024\-1709 \-e JSON .fi .RE .SH πŸ€– AI\-Powered Risk Assessment .PP SploitScan integrates with OpenAI to provide a comprehensive AI\-powered risk assessment for each CVE. This feature includes: .RS .IP \(bu 2 Detailed Risk Assessment: Understand the nature of the vulnerability and its business impact. .IP \(bu 2 Potential Attack Scenarios: Get descriptions of potential attack scenarios leveraging the vulnerability. .IP \(bu 2 Mitigation Recommendations: Receive specific, actionable recommendations to mitigate the risk. .IP \(bu 2 Executive Summary: A concise summary accessible to non\-technical stakeholders, highlighting the business impact and urgency. .RE .SS Example output .PP .RS .nf $ sploitscan.py CVE\-2024\-21413 [...] β”Œβ”€β”€β”€[ πŸ€– AI\-Powered Risk Assessment ] | | 1. Risk Assessment | \-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\- | The vulnerability identified by CVE\-2024\-21413 is a critical remote code execution flaw in | Microsoft Outlook with a CVSS score of 9.8. The impact on business operations can be severe due to | its high potential to be exploited over a network without any user interactions or elevated | privileges. This unvalidated input vulnerability (CWE\-20) could allow an attacker to execute | arbitrary code on the target system, thereby compromising the confidentiality, integrity, and | availability of critical business data and systems. Given its critical rating and the existence of | multiple exploits on public repositories like GitHub, the likelihood of exploitation is very high. | This necessitates immediate attention from the security teams to mitigate the risks associated. | | 2. Potential Attack Scenarios | \-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\- | An attacker could exploit this vulnerability by sending a specially crafted email to a victim | using Microsoft Outlook. Once the email is opened or previewed, the malicious payload would | execute, allowing the attacker to gain control over the victim's system. The process involves: 1. | Crafting a malicious email leveraging the specific flaw in email handling within Microsoft | Outlook. 2. Sending the email to the intended victim. 3. Upon opening or previewing the email, the | victim’s system executes the malicious code. The potential outcomes of this attack include theft | of sensitive information, installation of malware or ransomware, and compromising other systems | within the same network due to lateral movement capabilities. | | 3. Mitigation Recommendations | \-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\- | Immediate mitigation recommendation includes: 1. Applying the latest security patches provided by | Microsoft. Reference: https://msrc.microsoft.com/update\-guide/vulnerability/CVE\-2024\-21413 2. | Implementing network\-level protections such as email filtering and network segmentation to limit | the spread of potential infections. 3. Conducting regular security awareness training for users to | recognize phishing and malicious emails. 4. Monitoring network and system activity for signs of | suspicious behavior and unauthorized execution. 5. Regularly backing up critical data and ensuring | the integrity of backups. | | 4. Executive Summary | \-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\- | CVE\-2024\-21413, a critical remote code execution vulnerability in Microsoft Outlook, poses a | significant risk to businesses due to its potential to be exploited without user interaction. | Multiple exploit proofs are publicly available, increasing the likelihood of attacks. | Organizations must act swiftly by applying the necessary patches from Microsoft, enhancing their | email security protocols, and educating their staff to identify potential phishing attempts. | Mitigating this vulnerability is essential to protect sensitive information, maintain business | integrity, and ensure system availability, thus preventing potential financial and reputational | damage. Immediate action is crucial to safeguard the organization against this severe threat. | └──────────────────────────────────────── .fi .RE .SH πŸ›‘οΈ Patching Priority System .PP The Patching Prioritization System in SploitScan provides a strategic approach to prioritizing security patches based on the severity and exploitability of vulnerabilities. It's influenced by the model from CVE Prioritizer \[la]https://github.com/TURROKS/CVE_Prioritizer\[ra], with enhancements for handling publicly available exploits. Here's how it works: .RS .IP \(bu 2 A+ Priority: Assigned to CVEs listed in CISA's KEV or those with publicly available exploits. This reflects the highest risk and urgency for patching. .IP \(bu 2 A to D Priority: Based on a combination of CVSS scores and EPSS probability percentages. The decision matrix is as follows: .RS .IP \(bu 2 A: CVSS score >= 6.0 and EPSS score >= 0.2. High severity with a significant probability of exploitation. .IP \(bu 2 B: CVSS score >= 6.0 but EPSS score < 0.2. High severity but lower probability of exploitation. .IP \(bu 2 C: CVSS score < 6.0 and EPSS score >= 0.2. Lower severity but higher probability of exploitation. .IP \(bu 2 D: CVSS score < 6.0 and EPSS score < 0.2. Lower severity and lower probability of exploitation. .RE .RE .PP This system assists users in making informed decisions on which vulnerabilities to patch first, considering both their potential impact and the likelihood of exploitation. Thresholds can be changed to your business needs. .SH πŸ“† Changelog .SS [26. June 2024] \- Version 0.10 .RS .IP \(bu 2 \fBHackerOne Integration\fP: Added support for searching through HackerOne and displays if the CVE was used in any Bug Bounty program including its rank and severity distribution. .IP \(bu 2 \fBGeneral Improvements\fP: Various bug fixes. .RE .SS [24. May 2024] \- Version 0.9 .RS .IP \(bu 2 \fBAI\-Powered Risk Assessment\fP: Integrated OpenAI for detailed risk assessments, potential attack scenarios, mitigation recommendations, and executive summaries (needs OpenAI API key). .IP \(bu 2 \fBCVE Information Retrieval\fP: Due to API rate limits and instabilities replaced NIST NVD with CVE Program \[la]https://github.com/CVEProject/cvelistV5\[ra]\&. .IP \(bu 2 \fBGeneral Improvements\fP: Various bug fixes and performance improvements. .RE .SS [18. May 2024] \- Version 0.8 .RS .IP \(bu 2 \fBHTML Export Functionality\fP: Introduced the ability to export vulnerability data to HTML reports. .IP \(bu 2 \fBPacket Storm Integration\fP: Added support for fetching exploit data from Packet Storm. .IP \(bu 2 \fBEnhanced Display Functions\fP: Added CVE\fIGITHUB\fPURL as CVE source, and functions to output the most updated CVE source. .IP \(bu 2 \fBCode Refactoring\fP: Refactored code to improve maintainability and readability due to the growing code base. .RE .SS [11. May 2024] \- Version 0.7 .RS .IP \(bu 2 \fBNuclei Template Integration\fP: Added support for discovery of Nuclei templates, enhancing vulnerability data sources. .IP \(bu 2 \fBEnhanced Display Functions\fP: Refined visual output across all display functions for consistency and readability. .IP \(bu 2 \fBGeneral Improvements\fP: Various bug fixes and performance improvements such as improved error handling. .RE .SS [06. May 2024] \- Version 0.6.1 .RS .IP \(bu 2 \fBImport File Capabilities\fP: Added support for importing vulnerability data directly from Docker Scout scan files. .RE .SS [05. May 2024] \- Version 0.6 .RS .IP \(bu 2 \fBImport File Capabilities\fP: Added support for importing vulnerability data directly from Nessus, Nexpose, and OpenVAS scan files. .IP \(bu 2 \fBExpanded Command\-Line Options\fP: Introduced new command\-line options to specify the import file and its type. .IP \(bu 2 \fBRobust Configuration Management\fP: Improved error handling for missing or malformed configuration files. .IP \(bu 2 \fBGeneral Improvements\fP: Various bug fixes and performance improvements. .RE .SS [02. March 2024] \- Version 0.5 .RS .IP \(bu 2 \fBExploitDB Integration\fP: Added support for fetching exploit data from ExploitDB. .IP \(bu 2 \fBCVSS Enhancements\fP: Added support for CVSS 2 and CVSS 3.x .IP \(bu 2 \fBDocker support\fP .IP \(bu 2 \fBCode fixes\fP .RE .SS [28. February 2024] \- Version 0.4 .RS .IP \(bu 2 \fBVulnCheck Integration\fP: Added support for fetching exploit data from VulnCheck, enhancing the exploit information available. .IP \(bu 2 \fBAPI Key Configuration\fP: Introduced the requirement for a VulnCheck API key, specified in config.json. .IP \(bu 2 \fBRequirements satisfied for Debian Integration\fP .RE .SS [17. February 2024] \- Version 0.3 .RS .IP \(bu 2 \fBAdditional Information\fP: Added further information such as references & vector string .IP \(bu 2 \fBRemoved\fP: Star count in publicly available exploits .RE .SS [15. January 2024] \- Version 0.2 .RS .IP \(bu 2 \fBMultiple CVE Support\fP: Now capable of handling multiple CVE IDs in a single execution. .IP \(bu 2 \fBJSON and CSV Export\fP: Added functionality to export results to JSON and CSV files. .IP \(bu 2 \fBEnhanced CVE Display\fP: Improved visual differentiation and information layout for each CVE. .IP \(bu 2 \fBPatching Priority System\fP: Introduced a priority rating system for patching, influenced by various factors including the availability of public exploits. .RE .SS [13th January 2024] \- Version 0.1 .RS .IP \(bu 2 Initial release of SploitScan. .RE .SH πŸ«±πŸΌβ€πŸ«²πŸ½ Contributing .PP Contributions are welcome. Please feel free to fork, modify, and make pull requests or report issues. .PP Special thanks to: .RS .IP \(bu 2 Nilsonfsilva \[la]https://github.com/Nilsonfsilva\[ra] for support on Debian packaging. .IP \(bu 2 bcoles \[la]https://github.com/bcoles\[ra] for bugfixes. .IP \(bu 2 Javier Álvarez \[la]https://github.com/jalvarezz13\[ra] for bugfixes. .IP \(bu 2 Romullo \[la]https://github.com/Romullo\[ra] for ideas & suggestions. .IP \(bu 2 davidfortytwo \[la]https://github.com/davidfortytwo\[ra] for enhancements (Updated CVE retrieval and PacketStorm addition). .IP \(bu 2 con\-f\-use \[la]https://github.com/con-f-use\[ra] for support and fixes with setuptools/PyPi. .IP \(bu 2 Martijn Russchen \[la]https://github.com/martijnrusschen\[ra] for his feedback and idea on HackerOne GraphQL. .RE .SH πŸ“Œ Author .SS Alexander Hagenah .RS .IP \(bu 2 URL \[la]https://primepage.de\[ra] .IP \(bu 2 Twitter \[la]https://twitter.com/xaitax\[ra] .IP \(bu 2 LinkedIn \[la]https://www.linkedin.com/in/alexhagenah\[ra] .RE .SH πŸ“š References .RS .IP \(bu 2 CISA Known Exploited Vulnerabilities Catalog \[la]https://www.cisa.gov/known-exploited-vulnerabilities-catalog\[ra] .IP \(bu 2 CVE Program \[la]https://github.com/CVEProject/cvelistV5\[ra] .IP \(bu 2 ExploitDB \[la]https://www.exploit-db.com/\[ra] .IP \(bu 2 FIRST EPSS \[la]https://www.first.org/epss/api\[ra] .IP \(bu 2 HackerOne \[la]https://hackerone.com/\[ra] .IP \(bu 2 nomi\-sec PoC\-in\-GitHub API \[la]https://poc-in-github.motikan2010.net/\[ra] .IP \(bu 2 OpenAI \[la]https://openai.com/\[ra] .IP \(bu 2 Packet Storm \[la]https://packetstormsecurity.com/\[ra] .IP \(bu 2 ProjectDiscovery Nuclei \[la]https://github.com/projectdiscovery/nuclei-templates\[ra] .IP \(bu 2 VulnCheck \[la]https://vulncheck.com/\[ra] .RE SploitScan-0.10.5/pyproject.toml000066400000000000000000000017311465663544600166150ustar00rootroot00000000000000[build-system] requires = ["setuptools>=65", "wheel"] build-backend = "setuptools.build_meta" [project] name = "sploitscan" version = "0.10.5" description = "SploitScan is a sophisticated cybersecurity utility designed to provide detailed information on vulnerabilities and associated exploits." authors = [ { name = "Alexander Hagenah", email = "ah@primepage.de" } ] license = { file = "LICENSE" } dynamic = [ "readme" ] dependencies = [ "requests~=2.32.2", "jinja2~=3.1.4", "openai~=1.30.2" ] requires-python = ">=3.8" [project.scripts] sploitscan = "sploitscan.sploitscan:cli" [project.urls] homepage = "https://github.com/xaitax/SploitScan" repository = "https://github.com/xaitax/SploitScan" documentation = "https://github.com/xaitax/SploitScan#readme" changelog = "https://github.com/xaitax/SploitScan" [tool.setuptools] dynamic.readme = { file = [ "README.md" ], content-type = "text/markdown" } package-data.sploitscan = [ "templates/*.html", "config.json" ] SploitScan-0.10.5/requirements.txt000066400000000000000000000000561465663544600171640ustar00rootroot00000000000000requests==2.32.2 jinja2==3.1.4 openai==1.30.2 SploitScan-0.10.5/sploitscan.py000066400000000000000000000001441465663544600164270ustar00rootroot00000000000000#!/usr/bin/env python3 from sploitscan.sploitscan import cli if __name__ == "__main__": cli() SploitScan-0.10.5/sploitscan/000077500000000000000000000000001465663544600160565ustar00rootroot00000000000000SploitScan-0.10.5/sploitscan/__init__.py000066400000000000000000000000001465663544600201550ustar00rootroot00000000000000SploitScan-0.10.5/sploitscan/__main__.py000066400000000000000000000001021465663544600201410ustar00rootroot00000000000000from .sploitscan import cli if __name__ == "__main__": cli() SploitScan-0.10.5/sploitscan/config.json000066400000000000000000000000721465663544600202150ustar00rootroot00000000000000{ "vulncheck_api_key": "", "openai_api_key": "" } SploitScan-0.10.5/sploitscan/sploitscan.py000066400000000000000000001214161465663544600206140ustar00rootroot00000000000000#!/usr/bin/env python3 import requests import argparse import datetime import textwrap import threading import itertools import time import json import sys import os import csv import re import xml.etree.ElementTree as ET from openai import OpenAI from jinja2 import Environment, FileSystemLoader VERSION = "0.10.5" BLUE = "\033[94m" GREEN = "\033[92m" YELLOW = "\033[93m" ENDC = "\033[0m" CVE_GITHUB_URL = "https://raw.githubusercontent.com/CVEProject/cvelistV5/main/cves" EPSS_API_URL = "https://api.first.org/data/v1/epss?cve={cve_id}" CISA_URL = "https://www.cisa.gov/sites/default/files/feeds/known_exploited_vulnerabilities.json" NUCLEI_URL = ( "https://raw.githubusercontent.com/projectdiscovery/nuclei-templates/main/cves.json" ) GITHUB_API_URL = "https://poc-in-github.motikan2010.net/api/v1/" VULNCHECK_API_URL = "https://api.vulncheck.com/v3/index/vulncheck-kev" EXPLOITDB_URL = "https://gitlab.com/exploit-database/exploitdb/-/raw/main/files_exploits.csv?ref_type=heads" PACKETSTORM_URL = "https://packetstormsecurity.com/search/?q={cve_id}" HACKERONE_URL = "https://hackerone.com/graphql" CVSS_THRESHOLD = 6.0 EPSS_THRESHOLD = 0.2 PRIORITY_COLORS = { "A+": "\033[91m", "A": "\033[31m", "B": "\033[93m", "C": "\033[94m", "D": "\033[92m", } def fetch_data(url, params=None, headers=None): try: response = requests.get(url, params=params, headers=headers) response.raise_for_status() return response except requests.exceptions.RequestException as e: return f"❌ Error fetching data from {url}: {e}" def fetch_json_data(url, params=None, headers=None): response = fetch_data(url, params, headers) if isinstance(response, str): return None, response try: return response.json(), None except json.JSONDecodeError as e: return None, f"❌ Error parsing JSON data from {url}: {e}" def fetch_github_cve_data(cve_id): cve_year = cve_id.split("-")[1] cve_num = int(cve_id.split("-")[2]) url = f"{CVE_GITHUB_URL}/{cve_year}/{cve_num // 1000}xxx/{cve_id}.json" return fetch_json_data(url) def fetch_epss_score(cve_id): return fetch_json_data(EPSS_API_URL.format(cve_id=cve_id)) def fetch_cisa_data(): data, error = fetch_json_data(CISA_URL) if data and "vulnerabilities" in data: for vulnerability in data["vulnerabilities"]: vulnerability["cisa_status"] = "Yes" vulnerability["ransomware_use"] = vulnerability.get( "knownRansomwareCampaignUse", "Unknown" ) return data, error def fetch_nuclei_data(cve_id): response = fetch_data(NUCLEI_URL) if isinstance(response, str): return None, response try: for line in response.iter_lines(): if line: template = json.loads(line.decode("utf-8")) if template["ID"] == cve_id: return template, None except json.JSONDecodeError as e: return None, f"❌ Error parsing JSON data from {NUCLEI_URL}: {e}" return None, None def fetch_vulncheck_data(cve_id): vulncheck_api_key = config.get("vulncheck_api_key") if not vulncheck_api_key: return None, None headers = { "accept": "application/json", "authorization": f"Bearer {vulncheck_api_key}", } response = fetch_data(VULNCHECK_API_URL, params={"cve": cve_id}, headers=headers) if isinstance(response, str): return None, response try: json_data = response.json() return json_data, None except json.JSONDecodeError as e: return None, f"❌ Error parsing JSON data from VulnCheck: {e}" def fetch_exploitdb_data(cve_id): response = fetch_data(EXPLOITDB_URL) if isinstance(response, str): return [], response try: decoded_content = response.content.decode("utf-8") csv_reader = csv.reader(decoded_content.splitlines(), delimiter=",") header = next(csv_reader) codes_index = header.index("codes") return [ {"id": row[0], "date": row[3]} for row in csv_reader if cve_id in row[codes_index].split(";") ], None except csv.Error as e: return [], f"❌ Error parsing CSV data from {EXPLOITDB_URL}: {e}" def fetch_packetstorm_data(cve_id): response = fetch_data(PACKETSTORM_URL.format(cve_id=cve_id)) if isinstance(response, str): return {}, response return ( {"packetstorm_url": PACKETSTORM_URL.format(cve_id=cve_id)} if "No Results Found" not in response.text else {} ), None def fetch_hackerone_cve_details(cve_id): headers = { 'content-type': 'application/json' } payload = { "operationName": "CveDiscoveryDetailedViewCveEntry", "variables": { "cve_id": cve_id }, "query": """ query CveDiscoveryDetailedViewCveEntry($cve_id: String!) { cve_entry(cve_id: $cve_id) { rank reports_submitted_count severity_count_unknown severity_count_none severity_count_low severity_count_medium severity_count_high severity_count_critical __typename } } """ } response = requests.post(HACKERONE_URL, headers=headers, json=payload) if response.status_code == 200: try: data = response.json() if 'data' in data and 'cve_entry' in data['data']: return data, None else: return None, "❌ No HackerOne data found for this CVE." except json.JSONDecodeError as e: return None, f"❌ Error parsing JSON data from HackerOne: {e}" else: return None, f"❌ Error fetching data from HackerOne: {response.status_code}: {response.text}" def display_data(title, data, template, error=None): print(f"β”Œβ”€β”€β”€[ {BLUE}{title}{ENDC} ]") if error: print("|") print(f"β”” {error}\n") return if data: print(f"|") for line in template(data): print(line) print() else: print("|") print(f"β”” ❌ No data found.\n") def display_cve_data(cve_data, error=None): def template(data): if not data or "containers" not in data or "cna" not in data["containers"]: return ["β”” ❌ No vulnerability data found."] cve_item = data["containers"]["cna"] published = data["cveMetadata"].get("datePublished", "") if published: published_date = datetime.datetime.fromisoformat(published.rstrip("Z")) published = published_date.strftime("%Y-%m-%d") description = ( next( ( desc["value"] for desc in cve_item.get("descriptions", []) if desc["lang"] == "en" ), "No description available", ) .replace("\n\n", " ") .replace(" ", " ") ) wrapped_description = textwrap.fill( description, width=100, subsequent_indent=" " * 15 ) metrics = cve_item.get("metrics", []) baseScore, baseSeverity, vectorString = "N/A", "N/A", "N/A" for metric in metrics: cvss_data = metric.get("cvssV3_1") or metric.get("cvssV3") if cvss_data: baseScore = cvss_data.get("baseScore", "N/A") baseSeverity = cvss_data.get("baseSeverity", "N/A") vectorString = cvss_data.get("vectorString", "N/A") if baseScore != "N/A": break if baseScore == "N/A": adp = data["containers"].get("adp", []) for adp_entry in adp: for metric in adp_entry.get("metrics", []): cvss_data = metric.get("cvssV3_1") or metric.get("cvssV3") if cvss_data: baseScore = cvss_data.get("baseScore", "N/A") baseSeverity = cvss_data.get("baseSeverity", "N/A") vectorString = cvss_data.get("vectorString", "N/A") if baseScore != "N/A": break if baseScore != "N/A": break return [ f"β”œ Published: {published}", f"β”œ Base Score: {baseScore} ({baseSeverity})", f"β”œ Vector: {vectorString}", f"β”” Description: {wrapped_description}", ] display_data("πŸ” Vulnerability information", cve_data, template, error) def display_epss_score(epss_data, error=None): def template(data): if not data or "data" not in data or not data["data"]: return ["β”” ❌ No data found."] epss_score = data["data"][0].get("epss", "N/A") return ( [ f"β”” EPSS Score: {float(epss_score) * 100:.2f}% Probability of exploitation." ] if epss_score != "N/A" else [] ) display_data("♾️ Exploit Prediction Score (EPSS)", epss_data, template, error) def display_cisa_status(cve_id, cisa_data, error=None): def template(data): if not data or "vulnerabilities" not in data or not data["vulnerabilities"]: return ["β”” ❌ No data found."] for vulnerability in data["vulnerabilities"]: if vulnerability["cveID"] == cve_id: cisa_status = vulnerability["cisa_status"] ransomware_use = vulnerability["ransomware_use"] return [ f"β”œ Listed: {cisa_status}", f"β”” Ransomware: {ransomware_use}", ] return ["β”” ❌ No data found."] display_data("πŸ›‘οΈ CISA KEV Catalog", cisa_data, template, error) def display_public_exploits(github_data, vulncheck_data, exploitdb_data, packetstorm_data, nuclei_data, vulncheck_error=None): def template(): total_exploits = 0 entries = [] if github_data and github_data.get("pocs"): entries.append("β”œ GitHub") sorted_pocs = sorted(github_data["pocs"], key=lambda x: x.get("created_at", ""), reverse=True) if github_data["pocs"] else [] for poc in sorted_pocs: created_at = poc.get("created_at", "N/A") if created_at != "N/A": created_date = datetime.datetime.fromisoformat(created_at) created_at = created_date.strftime("%Y-%m-%d") entries.append(f"β”‚ β”œ Date: {created_at} - {poc.get('html_url', 'N/A')}") total_exploits += 1 entries[-1] = entries[-1].replace("β”œ", "β””") if vulncheck_data and isinstance(vulncheck_data, dict) and vulncheck_data.get("data"): entries.append("β”‚") entries.append("β”œ VulnCheck") sorted_vulncheck = sorted( (xdb for item in vulncheck_data["data"] for xdb in item.get("vulncheck_xdb", [])), key=lambda x: x.get("date_added", ""), reverse=True ) for xdb in sorted_vulncheck: date_added = xdb.get("date_added", "N/A") if date_added != "N/A": try: date_added = datetime.datetime.fromisoformat(date_added.rstrip("Z")).strftime("%Y-%m-%d") except ValueError: pass github_url = xdb.get("clone_ssh_url", "").replace("git@github.com:", "https://github.com/").replace(".git", "") entries.append(f"β”‚ β”œ Date: {date_added} - {github_url}") total_exploits += 1 entries[-1] = entries[-1].replace("β”œ", "β””") if vulncheck_error: entries.append("β”‚") entries.append(f"β”” ❌ VulnCheck Error: {vulncheck_error}") if exploitdb_data: entries.append("β”‚") entries.append("β”œ Exploit-DB") sorted_exploitdb = sorted(exploitdb_data, key=lambda x: x["date"], reverse=True) for item in sorted_exploitdb: url = f"https://www.exploit-db.com/exploits/{item['id']}" entries.append(f"β”‚ β”œ Date: {item['date']} - {url}") total_exploits += 1 entries[-1] = entries[-1].replace("β”œ", "β””") other_entries = [] if packetstorm_data and packetstorm_data.get("packetstorm_url"): other_entries.append(f"PacketStorm: {packetstorm_data['packetstorm_url']}") if nuclei_data and nuclei_data.get("file_path"): base_url = "https://raw.githubusercontent.com/projectdiscovery/nuclei-templates/main/" file_path = nuclei_data["file_path"] full_url = f"{base_url}{file_path}" other_entries.append(f"Nuclei: {full_url}") if other_entries: entries.append("β”‚") entries.append("β”” Other") for index, entry in enumerate(other_entries[:-1]): entries.append(f" β”œ {entry}") entries.append(f" β”” {other_entries[-1]}") if not entries: return ["β”” ❌ No data found."], total_exploits return entries, total_exploits exploits, total = template() print(f"β”Œβ”€β”€β”€[ {BLUE}πŸ’£ Public Exploits (Total: {total}){ENDC} ]") if exploits: print("|") for line in exploits: print(line) print() else: print("|") print(f"β”” ❌ No data found.\n") def display_hackerone_data(hackerone_data, error=None): def template(data): if not data or "data" not in data or "cve_entry" not in data["data"]: return ["β”” ❌ No data found."] cve_entry = data["data"]["cve_entry"] if not cve_entry: return ["β”” ❌ No data found."] rank = cve_entry.get("rank", "N/A") reports_submitted_count = cve_entry.get("reports_submitted_count", "N/A") severity_unknown = cve_entry.get("severity_count_unknown", 0) severity_none = cve_entry.get("severity_count_none", 0) severity_low = cve_entry.get("severity_count_low", 0) severity_medium = cve_entry.get("severity_count_medium", 0) severity_high = cve_entry.get("severity_count_high", 0) severity_critical = cve_entry.get("severity_count_critical", 0) severity_display = f"Unknown: {severity_unknown} / None: {severity_none} / Low: {severity_low} / Medium: {severity_medium} / High: {severity_high} / Critical: {severity_critical}" return [ f"β”œ Rank: {rank}", f"β”œ Reports: {reports_submitted_count}", f"β”” Severity: {severity_display}", ] display_data("πŸ•΅οΈ HackerOne Hacktivity", hackerone_data, template, error) def display_cve_references(cve_data, error=None): def template(data): if not data or "containers" not in data or "cna" not in data["containers"]: return ["β”” ❌ No data found."] references = data["containers"]["cna"].get("references", []) return ( [f"β”œ {ref['url']}" for ref in references[:-1]] + [f"β”” {references[-1]['url']}"] if references else ["β”” ❌ No further references found."] ) display_data("πŸ“š Further References", cve_data, template, error) def calculate_priority( cve_id, cve_data, epss_data, github_data, cisa_data, vulncheck_data, exploitdb_data ): cvss_score, epss_score = 0, 0 try: metrics = cve_data["containers"]["cna"]["metrics"] for metric in metrics: if "cvssV3_1" in metric: cvss_score = float(metric["cvssV3_1"]["baseScore"]) break except (KeyError, IndexError, TypeError): pass try: epss_score = ( float(epss_data["data"][0]["epss"]) if epss_data and "data" in epss_data else 0 ) except (KeyError, IndexError, TypeError): pass in_cisa_kev = ( any(vuln["cveID"] == cve_id for vuln in cisa_data.get( "vulnerabilities", [])) if cisa_data else False ) has_public_exploits = ( bool(github_data.get("pocs")) if github_data else ( False or bool(vulncheck_data.get("data")) if vulncheck_data else False or bool(exploitdb_data) ) ) if not (cvss_score or epss_score or in_cisa_kev or has_public_exploits): return None if in_cisa_kev or has_public_exploits: return "A+" if cvss_score >= CVSS_THRESHOLD and epss_score >= EPSS_THRESHOLD: return "A" if cvss_score >= CVSS_THRESHOLD: return "B" if epss_score >= EPSS_THRESHOLD: return "C" return "D" def display_priority_rating(cve_id, priority): def template(data): if not data or "priority" not in data or not data["priority"]: return ["β”” ❌ No data found."] priority_color = PRIORITY_COLORS.get(data["priority"], ENDC) return [f"β”” Priority: {priority_color}{data['priority']}{ENDC}"] if priority is None: display_data("⚠️ Patching Priority Rating", None, template) else: display_data("⚠️ Patching Priority Rating", { "priority": priority}, template) def load_config(config_path=None, debug=False): default_config = {"vulncheck_api_key": None, "openai_api_key": None} config_env_var = "SPLOITSCAN_CONFIG_PATH" config_paths = [config_path] if config_path else [] config_paths += [ os.getenv(config_env_var), os.path.join(os.path.dirname(os.path.abspath(__file__)), "config.json"), os.path.expanduser("~/.sploitscan/config.json"), os.path.expanduser("~/.config/sploitscan/config.json"), os.path.expanduser("~/Library/Application Support/sploitscan/config.json"), os.path.join(os.getenv("APPDATA", ""), "sploitscan", "config.json"), "/etc/sploitscan/config.json", ] config_paths = [path for path in config_paths if path] for path in config_paths: if path and os.path.exists(path): try: if debug: print(f"⚠️ Attempting to load config file from: {path}") with open(path, "r", encoding="utf-8") as file: config = json.load(file) if debug: print(f"⚠️ Successfully loaded config file: {path}") return config except json.JSONDecodeError as e: print(f"⚠️ Error decoding JSON from the config file {path}: {e}") except Exception as e: print(f"⚠️ Unexpected error reading config file {path}: {e}") print("⚠️ Config file not found in any checked locations, using default settings.") return default_config def get_risk_assessment(cve_details, cve_data): api_key = config.get("openai_api_key") if not api_key: return "❌ OpenAI API key is not configured correctly." client = OpenAI(api_key=api_key) prompt = f""" You are a security analyst. Analyze the following CVE details and provide a detailed risk assessment, potential attack scenarios, mitigation recommendations, and an executive summary. Ensure the output is formatted for a console display without any markdown, NO MARKDOWN, and the headers are clearly delineated with proper formatting as specified! Output only proper free flowing text and no lists as this won't be properly displayed in the console. CVE Details: {cve_details} Full CVE Data: {json.dumps(cve_data, indent=4)} Format the output exactly as follows: 1. Risk Assessment Provide a detailed risk assessment including the nature of the vulnerability & its business impact. Describe the likelihood and ease of exploitation, and potential impacts on confidentiality, integrity, and availability. 2. Potential Attack Scenarios Describe at least one potential attack scenarios that leverage this vulnerability. Each scenario should include a detailed description of the attack vector, the attack process, and the potential outcomes. 3. Mitigation Recommendations Provide specific, actionable mitigation recommendations. Include immediate actions such as patching. Provide links to relevant resources where applicable. 4. Executive Summary Summarize the vulnerability, its potential impacts, and the importance of taking action. Highlight key points from the risk assessment, attack scenarios, and mitigation recommendations. This summary should be accessible to non-technical stakeholders, emphasizing the business impact and urgency of addressing the vulnerability. """ try: response = client.chat.completions.create( model="gpt-4o", messages=[ {"role": "system", "content": "You are a security analyst."}, {"role": "user", "content": prompt}, ], ) result = response.choices[0].message.content.strip() return result except Exception as e: return f"❌ Error fetching data from OpenAI: {e}" def display_ai_risk_assessment(cve_details, cve_data): def spinner_animation(message): spinner = itertools.cycle(['|', '/', '-', '\\']) while not stop_spinner: sys.stdout.write(f'\r{message} {next(spinner)}') sys.stdout.flush() time.sleep(0.1) sys.stdout.write('\r' + ' ' * (len(message) + 2) + '\r') sys.stdout.flush() def get_risk_assessment_thread(): nonlocal assessment assessment = get_risk_assessment(cve_details, cve_data) global stop_spinner stop_spinner = True global stop_spinner stop_spinner = False assessment = None print("β”Œβ”€β”€β”€[ πŸ€– AI-Powered Risk Assessment ]") print("|") spinner_thread = threading.Thread(target=spinner_animation, args=("| Loading OpenAI risk assessment... ",)) spinner_thread.start() assessment_thread = threading.Thread(target=get_risk_assessment_thread) assessment_thread.start() assessment_thread.join() spinner_thread.join() print("|") if assessment: sections = assessment.split("\n\n") for section in sections: section = section.strip() if section: if section.startswith(("1. ", "2. ", "3. ", "4. ")): header = section.split("\n")[0].strip() print(f"| {header}") print("| " + "-" * (len(header) + 1)) content = "\n".join(section.split("\n")[1:]).strip() wrapped_content = textwrap.fill( content, width=100, initial_indent="| ", subsequent_indent="| " ) print(wrapped_content) else: wrapped_content = textwrap.fill( section, width=100, initial_indent="| ", subsequent_indent="| " ) print(wrapped_content) print("|") print("└────────────────────────────────────────\n") def import_vulnerability_data(file_path, file_type): if not os.path.exists(file_path): print(f"❌ Error: The file '{file_path}' does not exist.") return [] if file_type == "nessus": return import_nessus(file_path) if file_type == "nexpose": return import_nexpose(file_path) if file_type == "openvas": return import_openvas(file_path) if file_type == "docker": return import_docker(file_path) print(f"❌ Unsupported file type: {file_type}") return [] def import_nessus(file_path): def parse_nessus_file(path): tree = ET.parse(path) root = tree.getroot() return [ cve.text.strip().upper() for report_item in root.findall(".//ReportItem") for cve in report_item.findall("cve") if is_valid_cve_id(cve.text.strip().upper()) ] return import_file(file_path, parse_nessus_file) def import_nexpose(file_path): def parse_nexpose_file(path): tree = ET.parse(path) root = tree.getroot() return [ link.get("LinkTitle").upper() for link in root.findall(".//URLLink") if link.get("LinkTitle", "").startswith("CVE-") ] return import_file(file_path, parse_nexpose_file) def import_openvas(file_path): def parse_openvas_file(path): tree = ET.parse(path) root = tree.getroot() return [ ref.attrib.get("id").upper() for ref in root.findall(".//ref[@type='cve']") if is_valid_cve_id(ref.attrib.get("id").upper()) ] return import_file(file_path, parse_openvas_file) def import_docker(file_path): def parse_docker_file(path): with open(path, "r") as file: data = json.load(file) return [ rule.get("id", "").upper() for run in data.get("runs", []) for rule in run.get("tool", {}).get("driver", {}).get("rules", []) if rule.get("id", "").startswith("CVE-") ] return import_file(file_path, parse_docker_file) def import_file(file_path, parse_function): try: cve_ids = parse_function(file_path) unique_cve_ids = list(set(cve_ids)) print( YELLOW + f"πŸ“₯ Successfully imported {len(unique_cve_ids)} CVE(s) from '{file_path}'.\n" ) return unique_cve_ids except ET.ParseError as e: print(f"❌ Error parsing the file '{file_path}': {e}") except json.JSONDecodeError as e: print(f"❌ Error parsing the JSON file '{file_path}': {e}") except Exception as e: print(f"❌ An unexpected error occurred while processing '{file_path}': {e}") return [] def is_valid_cve_id(cve_id): return re.match(r"CVE-\d{4}-\d{4,7}$", cve_id) is not None def generate_filename(cve_ids, extension): timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S") cve_part = "_".join(cve_ids[:3]) + \ ("_and_more" if len(cve_ids) > 3 else "") return f"{timestamp}_{cve_part}_export.{extension}" def datetimeformat(value, format="%Y-%m-%d"): return datetime.datetime.fromisoformat(value.rstrip("Z")).strftime(format) def export_to_html(all_results, cve_ids): def template(data): base_path = os.path.dirname(os.path.abspath(__file__)) template_paths = [ os.path.join(base_path, "templates"), os.path.expanduser("~/.sploitscan/templates"), os.path.expanduser("~/.config/sploitscan/templates"), "/etc/sploitscan/templates", ] for path in template_paths: if os.path.exists(os.path.join(path, "report_template.html")): env = Environment(loader=FileSystemLoader(path)) break else: print( "❌ HTML template 'report_template.html' not found in any checked locations.") return ["❌ Error exporting to HTML: template not found"] env.filters["datetimeformat"] = datetimeformat template = env.get_template("report_template.html") filename = generate_filename(cve_ids, "html") output = template.render(cve_data=handle_cvss(data)) with open(filename, "w", encoding="utf-8") as file: file.write(output) return [f"β”” Data exported to file: {filename}"] def handle_cvss(data): for result in data: result["Public Exploits Total"] = sum([ len(result.get("GitHub Data", {}).get("pocs", [])), sum(len(item.get("vulncheck_xdb", [])) for item in result.get("VulnCheck Data", {}).get("data", [])), len(result.get("ExploitDB Data", [])) ]) if "GitHub Data" in result and "pocs" in result["GitHub Data"]: result["GitHub Data"]["pocs"] = sorted(result["GitHub Data"]["pocs"], key=lambda x: x.get("created_at", ""), reverse=True) if "VulnCheck Data" in result and "data" in result["VulnCheck Data"]: for item in result["VulnCheck Data"]["data"]: if "vulncheck_xdb" in item: item["vulncheck_xdb"] = sorted(item["vulncheck_xdb"], key=lambda x: x.get("date_added", ""), reverse=True) if "ExploitDB Data" in result: result["ExploitDB Data"] = sorted(result["ExploitDB Data"], key=lambda x: x.get("date", ""), reverse=True) if "EPSS Data" in result and "data" in result["EPSS Data"] and len(result["EPSS Data"]["data"]) > 0: result["EPSS Data"]["data"][0]["epss"] = try_parse_float(result["EPSS Data"]["data"][0].get("epss")) metrics = result.get("CVE Data", {}).get("containers", {}).get("cna", {}).get("metrics", []) for metric in metrics: cvss_data = metric.get("cvssV3_1", metric.get("cvssV3")) if cvss_data: cvss_data["baseScore"] = try_parse_float(cvss_data.get("baseScore")) cvss_data["baseSeverity"] = str(cvss_data.get("baseSeverity", "N/A")) cvss_data["vectorString"] = str(cvss_data.get("vectorString", "N/A")) else: metric["cvssV3_1"] = { "baseScore": 0.0, "baseSeverity": "N/A", "vectorString": "N/A"} return data def try_parse_float(value): try: return float(value) except (ValueError, TypeError): return 0.0 try: display_data("πŸ“ HTML Export", all_results, template) except Exception as e: print(f"❌ Error exporting to HTML: {e}") def export_to_json(all_results, cve_ids): def template(data): filename = generate_filename(cve_ids, "json") with open(filename, "w") as file: json.dump(data, file, indent=4) return [f"β”” Data exported to file: {filename}"] display_data("πŸ“ JSON Export", all_results, template) def export_to_csv(all_results, cve_ids): def template(data): filename = generate_filename(cve_ids, "csv") keys = list(data[0].keys()) + ["Risk Assessment"] with open(filename, "w", newline="") as file: writer = csv.DictWriter(file, fieldnames=keys) writer.writeheader() for item in data: item["Risk Assessment"] = item.get("Risk Assessment", "N/A") writer.writerow(item) return [f"β”” Data exported to CSV: {filename}"] display_data("πŸ“ CSV Export", all_results, template) def display_banner(): banner = f""" β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•— β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•”β•β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘β•šβ•β•β–ˆβ–ˆβ•”β•β•β•β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β–ˆβ–ˆβ•— β–ˆβ–ˆβ•‘ β•šβ•β•β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β•β• β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β•šβ•β•β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β•šβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β•šβ–ˆβ–ˆβ–ˆβ–ˆβ•‘ β•šβ•β•β•β•β•β•β•β•šβ•β• β•šβ•β•β•β•β•β•β• β•šβ•β•β•β•β•β• β•šβ•β• β•šβ•β• β•šβ•β•β•β•β•β•β• β•šβ•β•β•β•β•β•β•šβ•β• β•šβ•β•β•šβ•β• β•šβ•β•β•β• v{VERSION} / Alexander Hagenah / @xaitax / ah@primepage.de """ print(BLUE + banner + ENDC) def print_cve_header(cve_id): header = f" CVE ID: {cve_id} " line = "═" * len(header) print(f"{GREEN}β•”{line}β•—{ENDC}") print(f"{GREEN}β•‘{header}β•‘{ENDC}") print(f"{GREEN}β•š{line}╝{ENDC}\n") def fetch_and_display_cve_data(cve_id): cve_data, cve_error = fetch_github_cve_data(cve_id) display_cve_data(cve_data, cve_error) return cve_data def fetch_and_display_epss_score(cve_id): epss_data, epss_error = fetch_epss_score(cve_id) display_epss_score(epss_data, epss_error) return epss_data def fetch_and_display_cisa_status(cve_id): cisa_data, cisa_error = fetch_cisa_data() display_cisa_status(cve_id, cisa_data, cisa_error) relevant_cisa_data = next( (item for item in cisa_data.get("vulnerabilities", []) if item["cveID"] == cve_id), None, ) return relevant_cisa_data def fetch_and_display_public_exploits(cve_id): github_data, github_error = fetch_json_data(GITHUB_API_URL, params={"cve_id": cve_id}) vulncheck_data, vulncheck_error = fetch_vulncheck_data(cve_id) exploitdb_data, exploitdb_error = fetch_exploitdb_data(cve_id) packetstorm_data, packetstorm_error = fetch_packetstorm_data(cve_id) nuclei_data, nuclei_error = fetch_nuclei_data(cve_id) display_public_exploits(github_data, vulncheck_data, exploitdb_data, packetstorm_data, nuclei_data, vulncheck_error) return { "github_data": github_data, "vulncheck_data": vulncheck_data if isinstance(vulncheck_data, dict) else {}, "exploitdb_data": exploitdb_data, "packetstorm_data": packetstorm_data, "nuclei_data": nuclei_data } def fetch_and_display_hackerone_data(cve_id): hackerone_data, hackerone_error = fetch_hackerone_cve_details(cve_id) display_hackerone_data(hackerone_data, hackerone_error) return hackerone_data def compile_cve_details(cve_id, cve_data, epss_data, relevant_cisa_data, public_exploits): published = cve_data["cveMetadata"].get("datePublished", "N/A") if published != "N/A": published = datetime.datetime.fromisoformat(published.rstrip("Z")).strftime("%Y-%m-%d") description = ( next( (desc["value"] for desc in cve_data["containers"]["cna"].get("descriptions", []) if desc["lang"] == "en"), "No description available", ) .replace("\n\n", " ") .replace(" ", " ") ) metrics = cve_data["containers"]["cna"].get("metrics", []) baseScore, baseSeverity, vectorString = "N/A", "N/A", "N/A" for metric in metrics: if "cvssV3_1" in metric: cvss_data = metric["cvssV3_1"] baseScore = cvss_data.get("baseScore", "N/A") baseSeverity = cvss_data.get("baseSeverity", "N/A") vectorString = cvss_data.get("vectorString", "N/A") break epss_score = epss_data["data"][0].get("epss", "N/A") if epss_data and "data" in epss_data and epss_data["data"] else "N/A" cisa_status = relevant_cisa_data["cisa_status"] if relevant_cisa_data else "N/A" ransomware_use = relevant_cisa_data["ransomware_use"] if relevant_cisa_data else "N/A" github_exploits = "\n".join( [f"{poc['created_at']}: {poc['html_url']}" for poc in public_exploits["github_data"].get("pocs", [])] ) if public_exploits["github_data"] else "N/A" vulncheck_exploits = "\n".join( [f"{xdb['date_added']}: {xdb['clone_ssh_url'].replace('git@github.com:', 'https://github.com/').replace('.git', '')}" for item in public_exploits["vulncheck_data"].get("data", []) for xdb in item.get("vulncheck_xdb", [])] ) if public_exploits["vulncheck_data"] else "N/A" packetstorm_url = public_exploits["packetstorm_data"].get("packetstorm_url", "N/A") nuclei_url = f"https://raw.githubusercontent.com/projectdiscovery/nuclei-templates/main/{public_exploits['nuclei_data']['file_path']}" if public_exploits["nuclei_data"] and "file_path" in public_exploits["nuclei_data"] else "N/A" references_list = cve_data["containers"]["cna"].get("references", []) references = "\n".join([ref["url"] for ref in cve_data["containers"]["cna"].get("references", [])]) if cve_data else "N/A" return f""" Published: {published} Base Score: {baseScore} ({baseSeverity}) Vector: {vectorString} Description: {description} EPSS Score: {epss_score} CISA Status: {cisa_status} Ransomware Use: {ransomware_use} GitHub Exploits: {github_exploits} VulnCheck Exploits: {vulncheck_exploits} PacketStorm URL: {packetstorm_url} Nuclei Template: {nuclei_url} Further References: {references} """ def main(cve_ids, export_format=None, import_file=None, import_type=None, config_path=None, debug=False): global config config = load_config(config_path=config_path, debug=debug) if config_path else load_config(debug=debug) all_results = [] if export_format: export_format = export_format.lower() if import_file and import_type: cve_ids = import_vulnerability_data(import_file, import_type) if not cve_ids: print("❌ No valid CVE IDs found in the provided file.") return if not cve_ids: print("❌ No CVE IDs provided. Please provide CVE IDs or an import file and type.") return for cve_id in cve_ids: cve_id = cve_id.upper() if not is_valid_cve_id(cve_id): print(f"❌ Invalid CVE ID format: {cve_id}. Please use the format CVE-YYYY-NNNNN.") continue print_cve_header(cve_id) cve_data = fetch_and_display_cve_data(cve_id) if not cve_data: continue epss_data = fetch_and_display_epss_score(cve_id) relevant_cisa_data = fetch_and_display_cisa_status(cve_id) public_exploits = fetch_and_display_public_exploits(cve_id) hackerone_data = fetch_and_display_hackerone_data(cve_id) cve_details = compile_cve_details(cve_id, cve_data, epss_data, relevant_cisa_data, public_exploits) risk_assessment = get_risk_assessment(cve_details, cve_data) display_ai_risk_assessment(cve_details, cve_data) priority = calculate_priority( cve_id, cve_data, epss_data, public_exploits["github_data"], relevant_cisa_data, public_exploits["vulncheck_data"], public_exploits["exploitdb_data"] ) display_priority_rating(cve_id, priority) display_cve_references(cve_data) cve_result = { "CVE Data": cve_data, "EPSS Data": epss_data, "CISA Data": relevant_cisa_data, "Nuclei Data": public_exploits["nuclei_data"], "GitHub Data": public_exploits["github_data"], "VulnCheck Data": public_exploits["vulncheck_data"], "ExploitDB Data": public_exploits["exploitdb_data"], "PacketStorm Data": public_exploits["packetstorm_data"], "HackerOne Data": hackerone_data, "Priority": {"Priority": priority}, "Risk Assessment": risk_assessment, } all_results.append(cve_result) if export_format == "json": export_to_json(all_results, cve_ids) elif export_format == "csv": export_to_csv(all_results, cve_ids) elif export_format == "html": export_to_html(all_results, cve_ids) def cli(): display_banner() parser = argparse.ArgumentParser( description="SploitScan: Retrieve and display vulnerability data as well as public exploits for given CVE ID(s)." ) parser.add_argument( "cve_ids", type=str, nargs="*", default=[], help="Enter one or more CVE IDs to fetch data. Separate multiple CVE IDs with spaces. Format for each ID: CVE-YYYY-NNNNN. This argument is optional if an import file is provided using the -i option.", ) parser.add_argument( "-e", "--export", choices=["json", "JSON", "csv", "CSV", "html", "HTML"], help="Optional: Export the results to a JSON, CSV, or HTML file. Specify the format: 'json', 'csv', or 'html'.", ) parser.add_argument( "-t", "--type", choices=["nessus", "nexpose", "openvas", "docker"], help="Specify the type of the import file: 'nessus', 'nexpose', 'openvas' or 'docker'.", ) parser.add_argument( "-i", "--import-file", type=str, help="Path to an import file from a vulnerability scanner. If used, CVE IDs can be omitted from the command line arguments.", ) parser.add_argument( "-c", "--config", type=str, help="Path to a custom config file.", ) parser.add_argument( "-d", "--debug", action="store_true", help="Enable debug output." ) args = parser.parse_args() main(args.cve_ids, args.export, args.import_file, args.type, args.config, args.debug) if __name__ == "__main__": cli() SploitScan-0.10.5/sploitscan/templates/000077500000000000000000000000001465663544600200545ustar00rootroot00000000000000SploitScan-0.10.5/sploitscan/templates/report_template.html000066400000000000000000000414541465663544600241600ustar00rootroot00000000000000 CVE Report

SploitScan

CVE Report
GitHub Twitter/X

{% for cve in cve_data %}

{{ cve['CVE Data']['cveMetadata']['cveId'] }}

πŸ” Vulnerability Information

{{ cve['CVE Data']['containers']['cna']['descriptions'][0]['value'] if cve['CVE Data'] and cve['CVE Data'].get('containers') else 'N/A' }}

Published {{ cve['CVE Data']['cveMetadata']['datePublished']|datetimeformat if cve['CVE Data'] and cve['CVE Data'].get('cveMetadata') else 'N/A' }}
Base Score {{ cve['CVE Data']['containers']['cna']['metrics'][0]['cvssV3_1']['baseScore'] if cve['CVE Data'] and cve['CVE Data'].get('containers') and cve['CVE Data']['containers']['cna']['metrics'] else 'N/A' }} ({{ cve['CVE Data']['containers']['cna']['metrics'][0]['cvssV3_1']['baseSeverity'] if cve['CVE Data'] and cve['CVE Data'].get('containers') and cve['CVE Data']['containers']['cna']['metrics'] else 'N/A' }})
Vector {{ cve['CVE Data']['containers']['cna']['metrics'][0]['cvssV3_1']['vectorString'] if cve['CVE Data'] and cve['CVE Data'].get('containers') and cve['CVE Data']['containers']['cna']['metrics'] else 'N/A' }}

♾️ Exploit Prediction Score (EPSS)

{% if cve['EPSS Data'] and cve['EPSS Data'].get('data') %} {% else %} {% endif %}
Score{{ "%.2f" % (cve['EPSS Data']['data'][0]['epss'] * 100) }}% Probability of exploitationN/A

πŸ›‘οΈ CISA KEV Catalog

Listed {{ cve['CISA Data']['cisa_status'] if cve['CISA Data'] else 'N/A' }}
Ransomware {{ cve['CISA Data']['ransomware_use'] if cve['CISA Data'] else 'N/A' }}

πŸ’£ Public Exploits (Total: {{ cve['Public Exploits Total'] }})

{% if cve['GitHub Data']['pocs'] %}

GitHub

{% for poc in cve['GitHub Data']['pocs'] %} {% endfor %}
{{ poc['created_at']|datetimeformat }} {{ poc['html_url'] }}
{% endif %} {% if cve['VulnCheck Data']['data'] %}

VulnCheck

{% for item in cve['VulnCheck Data']['data'] %} {% for xdb in item['vulncheck_xdb'] %} {% endfor %} {% endfor %}
{{ xdb['date_added']|datetimeformat }} {{ xdb['clone_ssh_url'].replace('git@github.com:', 'https://github.com/').replace('.git', '') }}
{% endif %} {% if cve['ExploitDB Data'] %}

Exploit-DB

{% for item in cve['ExploitDB Data'] %} {% endfor %}
{{ item['date']|datetimeformat }} https://www.exploit-db.com/exploits/{{ item['id'] }}
{% endif %}

Other

{% if cve['PacketStorm Data']['packetstorm_url'] %} {% endif %} {% if cve['Nuclei Data']['file_path'] %} {% endif %}
PacketStorm {{ cve['PacketStorm Data']['packetstorm_url'] }}
Nuclei {{ cve['Nuclei Data']['file_path'] }}

πŸ•΅οΈ HackerOne Hacktivity

Rank {{ cve['HackerOne Data']['data']['cve_entry']['rank'] if cve['HackerOne Data'] and cve['HackerOne Data'].get('data') and cve['HackerOne Data']['data'].get('cve_entry') else 'N/A' }}
Reports Submitted {{ cve['HackerOne Data']['data']['cve_entry']['reports_submitted_count'] if cve['HackerOne Data'] and cve['HackerOne Data'].get('data') and cve['HackerOne Data']['data'].get('cve_entry') else 'N/A' }}
Severity πŸ” Unknown: {{ cve['HackerOne Data']['data']['cve_entry']['severity_count_unknown'] if cve['HackerOne Data'] and cve['HackerOne Data'].get('data') and cve['HackerOne Data']['data'].get('cve_entry') else 0 }}, 🚫 None: {{ cve['HackerOne Data']['data']['cve_entry']['severity_count_none'] if cve['HackerOne Data'] and cve['HackerOne Data'].get('data') and cve['HackerOne Data']['data'].get('cve_entry') else 0 }}, ⚠️ Low: {{ cve['HackerOne Data']['data']['cve_entry']['severity_count_low'] if cve['HackerOne Data'] and cve['HackerOne Data'].get('data') and cve['HackerOne Data']['data'].get('cve_entry') else 0 }}, πŸ”§ Medium: {{ cve['HackerOne Data']['data']['cve_entry']['severity_count_medium'] if cve['HackerOne Data'] and cve['HackerOne Data'].get('data') and cve['HackerOne Data']['data'].get('cve_entry') else 0 }}, πŸ”₯ High: {{ cve['HackerOne Data']['data']['cve_entry']['severity_count_high'] if cve['HackerOne Data'] and cve['HackerOne Data'].get('data') and cve['HackerOne Data']['data'].get('cve_entry') else 0 }}, πŸ’€ Critical: {{ cve['HackerOne Data']['data']['cve_entry']['severity_count_critical'] if cve['HackerOne Data'] and cve['HackerOne Data'].get('data') and cve['HackerOne Data']['data'].get('cve_entry') else 0 }}

πŸ€– AI-Powered Risk Assessment

{{ cve['Risk Assessment'] }}

⚠️ Patching Priority Rating

Priority {{ cve['Priority']['Priority'] if cve['Priority'] and cve['Priority']['Priority'] else 'N/A' }}

πŸ“š Further References

{% for ref in cve['CVE Data']['containers']['cna']['references'] %} {% else %} {% endfor %}
N/A
{% endfor %}