Actions Panel
Learn how to test, evaluate, and monitor LLMs for OWASP Top 10 security issues
By WhyLabsFollow
Date and time
Thursday, November 16 · 10 – 11am PST
Location
Online
About this event
- 1 hour
- Mobile eTicket
Join this hands-on workshop to implement ML monitoring on large language models (LLMs) for common security issues with WhyLabs LangKit.
The ability to effectively monitor and manage large language models (LLMs) like GPT from OpenAI has become essential in the rapidly advancing field of AI. WhyLabs, in response to the growing demand, has created a powerful new tool, LangKit, to ensure LLM applications are monitored continuously and operated responsibly.
Join our workshop designed to equip you with the knowledge and skills to use LangKit with Hugging Face models. Guided by our team of experienced AI practitioners, you’ll learn how to assess the security risks of your LLM application and how to protect your application from adversarial scenarios.
Once completed, you’ll also receive a certificate!
This workshop will cover how to tackle the OWASP Top 10 security challenges for Large Language Model Applications (version 1.1).
- LLM01: Prompt Injection
- LLM02: Insecure Output Handling
- LLM03: Training Data Poisoning
- LLM04: Model Denial of Service
- LLM05: Supply Chain Vulnerabilities
- LLM06: Sensitive Information Disclosure
- LLM07: Insecure Plugin Design
- LLM08: Excessive Agency
- LLM09: Overreliance
- LLM10: Model Theft
What you’ll need:
A free WhyLabs account (https://whylabs.ai/free)
A Google account (for saving a Google Colab)
Who should attend:
Anyone interested in building applications with LLMs, AI Observability, Model monitoring, MLOps, and DataOps! This workshop is designed to be approachable for most skill levels. Familiarity with machine learning and Python will be useful, but it’s not required to attend.
By the end of this workshop, you’ll be able to implement security techniques to your large language models (LLMs) .
Bring your curiosity and your questions. By the end of the workshop, you’ll leave with a new level of comfort and familiarity with LangKit and be ready to take your language model development and monitoring to the next level.
About WhyLabs:
WhyLabs.ai is an AI observability platform that prevents data & model performance degradation by allowing you to monitor and ensure the security of your LLM applications in production. https://whylabs.ai/
Check out our open-source data & ML monitoring project: https://github.com/whylabs/whylogs
Do you want to connect with the community, learn about WhyLabs, or get project support? Join the WhyLabs + Robust & Responsible AI community Slack: https://bit.ly/rsqrd-slack
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