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Udemy - Pentesting GenAI LLM models - Securing Large Language Models

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Udemy - Pentesting GenAI LLM models - Securing Large Language Models (Size: 1.6 GB)
  1 - About your certificate.html 921.6 B
  1 - Bonus lecture.html 6.3 KB
  1 -Introduction and Course resource.mp4 23.5 MB
  1 -LLM PENTEST.pptx 10.6 MB
  1 -Prompt Injection.mp4 18.1 MB
  1 -Red Teaming LLMs Five Key Techniques.mp4 107.8 MB
  1 -Reporting.mp4 10.4 MB
  1 -What is ATT&CK.mp4 24.8 MB
  1 -What is Penetration Testing.mp4 31.5 MB
  1 -Why Benchmarks Are Not Enough AI Safety & Security.mp4 14.4 MB
  1 -Why Penetration Testing is Essential for GenAI.mp4 30.3 MB
  10 -Demo LLM Application Overview.mp4 6.8 MB
  10 -Exploring ATT&CK Groups.mp4 20.1 MB
  10 -Plugin Security LLM Applications.mp4 21.1 MB
  11 -Excessive Agency.mp4 27.3 MB
  11 -Importing the LLM Application.mp4 7.3 MB
  11 -Software in the ATT&CK Framework.mp4 15.6 MB
  12 -Campaigns Overview.mp4 22.1 MB
  12 -Overreliance.mp4 35.5 MB
  13 -ATT&CK Relationships.mp4 15.1 MB
  13 -Model Theft.mp4 16 MB
  14 -ATT&CK Enterprise Matrix - Hands-On.mp4 200.6 MB
  2 -Ai Application vulnerabilities.ipynb 14 KB
  2 -Comparing Red Teaming and Penetration Testing.mp4 27.7 MB
  2 -Indirect Prompt Injection Demo.mp4 122.3 MB
  2 -Indirect Prompt Injection Lab Access.url 102.4 B
  2 -LLM Application Vulnerabilities - Demo 01 (Code Explanation).mp4 22.4 MB
  2 -Remediation and Reporting.mp4 27.2 MB
  2 -Understanding the Pyramid of Pain.mp4 56.2 MB
  2 -Why LLMs Are Vulnerable.mp4 19.1 MB
  3 -Insecure Output Handling Theory.mp4 26.6 MB
  3 -LLM Application Vulnerabilities - Demo 02 (Biased and Stereotypes).mp4 39.2 MB
  3 -Overview of ATT&CK Matrices.mp4 11 MB
  3 -Penetration Testing Process.mp4 23.2 MB
  4 -ATT&CK Tactics.mp4 73.6 MB
  4 -Exploitation.mp4 20.1 MB
  4 -Insecure Output Handling Demo.mp4 89.5 MB
  4 -Insecure Output Handling Lab Access.url 102.4 B
  4 -LLM Application Vulnerabilities - Demo 03 (Sensitive Data Disclosure).mp4 37.3 MB
  5 -ATT&CK Techniques.mp4 29.7 MB
  5 -LLM Application Vulnerabilities - Demo 04 (Service Disruption).mp4 12.5 MB
  5 -Post-Exploitation.mp4 31.5 MB
  5 -Supply Chain Vulnerabilities.mp4 22.7 MB
  6 -ATT&CK Subtechniques.mp4 43.2 MB
  6 -LLM Application Vulnerabilities - Demo - 05 (Hallucination).mp4 33.8 MB
  6 -Model Denial of Service (DoS).mp4 42.3 MB
  7 -Data Sources for ATT&CK.mp4 15.3 MB
  7 -Foundation Models vs. LLM Apps.mp4 17.6 MB
  7 -Stop Model DOS Attack.mp4 16.5 MB
  8 -Detection Strategies.mp4 17.6 MB
  8 -Strategies for LLM Application Safety.mp4 18 MB
  8 -Training Data Poisoning.mp4 26.5 MB
  9 -Examining LLM Vulnerabilities.mp4 14.3 MB
  9 -Implementing Mitigation Techniques.mp4 20.3 MB
  9 -Sensitive Information Disclosure.mp4 30.1 MB
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 57 total files

Description


Pentesting GenAI LLM models: Securing Large Language Models

https://WebToolTip.com

Published 4/2025
Created by Start-Tech Trainings
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 51 Lectures ( 3h 16m ) | Size: 1.6 GB

Master LLM Security: Penetration Testing, Red Teaming & MITRE ATT&CK for Secure Large Language Models

What you'll learn
Understand the unique vulnerabilities of large language models (LLMs) in real-world applications.
Explore key penetration testing concepts and how they apply to generative AI systems.
Master the red teaming process for LLMs using hands-on techniques and real attack simulations.
Analyze why traditional benchmarks fall short in GenAI security and learn better evaluation methods.
Dive into core vulnerabilities such as prompt injection, hallucinations, biased responses, and more.
Use the MITRE ATT&CK framework to map out adversarial tactics targeting LLMs.
Identify and mitigate model-specific threats like excessive agency, model theft, and insecure output handling.
Conduct and report on exploitation findings for LLM-based applications.

Requirements
Basic understanding of IT or cybersecurity Curiosity about AI systems and their real-world impact No prior knowledge of penetration testing or LLMs required

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