Llm torchchat recently released

[crystaloptik]

What does it mean for falconpy use?

https://github.com/pytorch/torchchat

[jshcodes]

Hi @crystaloptik -

Could you provide us more detail regarding the use case or scenario you're attempting to address?

Both libraries should be fine to include within the same project.

[crystaloptik]

Use Case: Vulnerability Management and CVE Detection Querying

Scenario:
A security engineer is responsible for managing vulnerabilities across an organization’s infrastructure. The engineer needs to quickly gather detailed information about specific vulnerabilities (identified by CVE numbers) and understand their potential impact on various assets within the organization.

Outcome:
Using the interactive chat application integrated with AWS Bedrock's LLaMA 3.1 model and FalconPy where Falcon Spotlight data exists:

1. CVE Impact Assessment:

   • The engineer can query the system with a specific CVE identifier, e.g., "What is the impact of CVE-2024-XXXX on our systems?"
   • The chat application utilizes the LLaMA 3.1 model to provide a concise description of the vulnerability, including its severity, affected systems, and potential exploitation vectors.
   • FalconPy retrieves real-time data from CrowdStrike to identify if any organization-owned assets have been flagged for this specific CVE, highlighting those that require immediate remediation.

2. Application Asset Inventory Querying:

   • The engineer can inquire about the vulnerability status of a specific application or asset group, e.g., "Which assets running Apache Tomcat are vulnerable to CVE-2023-XXXX?"
   • The system responds by listing all relevant assets from the organization's inventory that match the query, along with their current patch status and any active threat indicators from CrowdStrike.

Benefits:

• Efficiency: The engineer rapidly gathers actionable insights, allowing them to prioritize patching and remediation tasks effectively.
• Accuracy: Real-time data from CrowdStrike ensures that the engineer is working with the most current vulnerability information and asset statuses.
• Automation: By leveraging AI and automated queries, the engineer reduces manual research time and improves overall response time to potential threats.

This integrated solution significantly enhances the security engineer's ability to manage vulnerabilities and protect the organization's assets from exploitation.