@mylifcc: The ultimate AI security red teaming tool is here! I just discovered an incredibly hardcore open-source project — DeepTeam! Produced by Confident AI, it is an LLM Red Teaming framework built on DeepEval, specifically designed to 'hack' your own large models: 50+ real-world vulnerabilities…
Summary
Confident AI has released DeepTeam, an open-source LLM red teaming framework that supports 50+ vulnerability detections and 20+ adversarial attacks, aimed at helping developers safely test large language models.
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@DailyDoseOfDS_: OpenAI paid $500k for this! > A Kaggle contest to find LLM vulnerabilities DeepTeam does it for free. It implements 20+…
DeepTeam is a free, open-source tool that implements 20+ state-of-the-art attacks to detect over 50 LLM vulnerabilities, including bias and PII leakage, running locally without a dataset.
@AdamShao: Officially open-sourcing my vulnerability discovery tool: http://flounders.xyz This is an AI Agent-based fully automated vulnerability discovery workflow. You just tell the AI which project's vulnerabilities you want to find, and it will automatically download code and documentation, deeply audit the code, discover suspicious vulnerabilities, automatically verify them locally and online…
Flounder is an open-source AI agent-based tool that automates vulnerability discovery in codebases. Users describe the target and the tool autonomously downloads code, conducts deep code audits, tests vulnerabilities locally and online, and generates reports.
A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation
This paper presents a red teaming framework for LLMs that uses a multi-role architecture to systematically uncover vulnerabilities, particularly in faithfulness. The framework demonstrated a 7.9% increase in attack success rate in QA tasks and highlights the impact of architectural choices over parameter scaling on model safety.
@FinanceYF5: AI was previously used more for writing code, but it is now beginning to systematically protect code. OpenAI has launched Daybreak, targeting network defense teams by combining models, Codex, and the security ecosystem to help continuously discover, fix, and fortify software. This is a step towards the future: enabling security teams to act at the speed required for defense.
OpenAI has launched a new product called Daybreak, designed to help network defense teams continuously discover, fix, and fortify software by combining models, Codex, and the security ecosystem.
@shaogefenhao: Recently set up E2E, AI automatically creates E2E test cases then completes development and debugging, passing acceptance in one go. Yesterday the team worked on a requirement, AI completed it end-to-end, passed acceptance in one go, everyone was amazed. And it's only using the cheap model DeepSeek V4 Flash.
Team members shared their experience of using AI (DeepSeek V4 Flash) to automatically create E2E test cases and complete development and debugging, passing acceptance in one go, demonstrating the potential of AI-assisted development.