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Technical Workshop: (Hands On) Finetuning GenAI for Hacking and Defending
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Trainer: Jitendra Chauhan & Abhisek Datta
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Jitendra Chauhan (IIT Kgp Alumni)

Creator of Bad Llama, How to Turn Good Llama into a Toxic Llama | Chief Scientist/Co Founder, Detoxio.ai

Jitendra is a seasoned professional in Product & Strategy with over 18 years of experience in the tech industry. An alumnus of IIT Kharagpur,he has been a founding member of two startups.. With three patents to his name, Jitendra's expertise spans AI/ML, Data Engineering, and cybersecurity, where he has built SIEM solutions in the cloud and
developed products focused on Penetration Testing, EASM, and Red Teaming.

 

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Abhishek Datta (Nullcon Trainer)

Creator of Vet, Open Source Supply Chain Tool (Product Hunt 37th Rank) | CTO/Co-Founder, Detoxio.ai

Abhisek is a seasoned expert in Research & Technology, boasting over 18 years of experience and co-founding two ventures. His significant contributions to cybersecurity include identifying over 15 CVEs (Common Vulnerabilities and Exposures). As a speaker and trainer, he shares his deep knowledge in exploitation, malware analysis, GenAI security, and AI supply chain attacks, showcasing his comprehensive expertise and dedication to advancing the security landscape.

 

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Workshop Summary: 

Workshop Duration: 4 Hours, 1/2 Day
Date: 30th May, Thursday, 2024 

 

Description:

This workshop is designed for a technical audience including Appsec Pentesters, Security Engineers, Security Architects, and AI/ML practitioners, Software Developers who have started exploring GenAI. 

 

Workshop Agenda:

0. Introduction to LLMs: Running an LLM for Fun and Profit

  • Overview of Large Language Models (LLMs) and their potential for various applications.
  • [Hands-On] Step-by-step guide to setting up and running an open-source LLM.
  • [Hands-On] Introduction to interacting with LLMs for specific use cases.

 

1. Understanding LLMs History, Evolution and Internals

  • Deep dive into the architecture of LLMs, focusing on Transformers and Encoders.
  • A brief history of the evolution of LLMs, highlighting the advancements from second-generation deep learning models.
  • Exploring the distinctions between LLMs and earlier deep learning frameworks.


2. Penetration Testing and Red Teaming LLMs

  • 2a. Identifying LLM Application Vulnerabilities
    • Discussion on the various classes of vulnerabilities specific to LLM applications.
  • 2b. Hands-on - Testing LLMs and General AI Applications
    • Practical exercises on testing LLMs and GenAI applications for selected classes
      of vulnerabilities.
    • Open Source Tools to Red Team a GenAI Application
  • 2c. AI Supply Chain Risks
    • Exploration of risks in the AI supply chain, including model poisoning and
      mitigation strategies.
    • Hands-On - Creating and Detecting Model Poining Attacks


3. Security Monitoring and Guardrails for LLMs

  • [Hands on ] Using a Open Source / Community Verison Solution to Develop Security
    Monitoring
  • Strategies for implementing security monitoring of LLMs to detect and respond to
    potential threats.
  • Guidelines for establishing guardrails to prevent specific types of attacks on LLMs and
    GenAI applications.

 

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Candidate Requirements:

  • The course is beginner friendly
  • Some python programming language and machine learning experienec will help

You need to bring:

Hardware: 

  • A laptop with internet access
  • A Kaggle account
  • A Hugging Face account
  • To get Maximum Benefit, Python Programming and Machine Learning Experience Will Help

 

Who Should Attend ? 

  • This workshop is designed for a technical audience including Appsec Pentesters, Security Engineers, Security Architects, and AI/ML practitioners, Software Developers who have started
    exploring GenAI.

 

Set Expectations:

  • Hands on session

 

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