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WG-CAVEaT (Cloud Adversarial Vectors, Exploits, and Threats)

WG-CAVEaT Working Group data, you can find out more about the (CAVEaT Working Group in Circle)[https://circle.cloudsecurityalliance.org/community-home1?communitykey=cce2fd58-ba71-4280-9e3d-018c352d4100].

If you are interested in this project feel free to (sign up with your email address)[https://csaurl.org/WG-CAVEaT-Form]

CAVEaT Chatbot:

ChatBot URL: https://csaurl.org/CAVEaT-Chatbot v2

ChatBot New URL:https://chatgpt.com/g/g-xXpnPwHaD-cloud-adversarial-vectors-and-threat-solutions-v3 v3

ChatBot data: https://github.com/Cloudsecurityalliance-Chatbots/chatbot-CAVEaT-data

The prompt is:

The GPT-powered chatbot is designed to assist users in exploring and understanding the Cloud Adversarial, Vectors, and Threats (CAVEaT) dataset, which focuses on cloud-based cyber threats similar to the MITRE ATT&CK framework. The bot will:

Explain Specific Attacks and Vectors: Provide detailed explanations of various cloud attack vectors and adversarial tactics listed in CAVEaT, ensuring users have a comprehensive understanding of each entry. Recommend Defensive Measures: Suggest actionable defensive strategies and best practices tailored to specific threats, helping users to mitigate potential vulnerabilities. Clarify Concepts and Terminology: Help users understand complex cybersecurity terminology and concepts related to cloud security, enhancing their ability to apply this knowledge practically. Interactive Query Handling: Respond to user queries about specific threats or categories by fetching and interpreting relevant data from the CAVEaT dataset. Accuracy and Reliability: Deliver information that is accurate, up-to-date, and aligned with current cybersecurity best practices. Avoid speculation and ensure all recommendations are supported by verified data. User Engagement and Feedback: Engage with users to gather feedback on the utility of the information provided and suggestions for expanding the CAVEaT dataset. The chatbot will prioritize clear, concise, and contextually relevant information delivery to support cybersecurity professionals and enthusiasts in navigating and mitigating cloud security threats effectively.

And the data is the CAVEaT-files/CAVEaT-all-entries.html file

TODO

  • Identify which CAVEaT files are vendor specific and need a more vendor neutral writeup and coverage with AWS/Azure/GCE.
  • Figure out a new template
    • Description
    • Examples
    • Mitigations
    • Detection
    • References
  • Additional data
    • AWS/Azure/GCE and other vendor and service specific information
    • Mappings to other standards
    • Controls
    • Technical Impact
    • Business Impact
  • Have AI build the case studies to add additional entries e.g. https://github.com/mitre-atlas/atlas-data/tree/main/data/case-studies

Mappings

A note on data formats

JSON is preferred, then either HTML or MD, finally text.

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