OWASP Top 10 for LLM

The OWASP Top 10 for Large Language Model Applications project aims to educate developers, designers, architects, managers, and organizations about the potential security risks when deploying and managing Large Language Models (LLMs). The project provides a list of the top 10 most critical vulnerabilities often seen in LLM applications, highlighting their potential impact, ease of exploitation, and prevalence in real-world applications. Examples of vulnerabilities include prompt injections, data leakage, inadequate sandboxing, and unauthorized code execution, among others. The goal is to raise awareness of these vulnerabilities, suggest remediation strategies, and ultimately improve the security posture of LLM applications.

1 Prompt Injection
2 Insecure Output Handling
3 Training Data Poisoning
4 Model Denial of Service
5 Supply Chain Vulnerabilities
6 Sensitive Information Disclosure
7 Insecure Plugin Design
8 Excessive Agency
9 Overreliance
10 Model Theft

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🦙 Lagent: A lightweight framework for building LLM-based agents

Lagent - это легковесный фреймворк с открытым исходным кодом, который позволяет легко и эффективно создавать агентов на основе больших языковых моделей (LLM). Он также предоставляет некоторые типовые инструменты для расширения возможностей LLM.

pip install lagent

▪Github

@data_analysis_ml