🛡 TL;DR: an open-source red teaming framework that calls itself "penetration testing, but for LLMs." Title: confident-ai/deepteam URL: 📌 Highlights 🎯 50+ vulnerabilities across 6 categories: data privacy, bias, authorization bypass, agent-specific risks and more ⚔️ 20+ attack methods, from prompt injection to multi-turn crescendo jailbreaks 📋 Aligned with OWASP Top 10 for LLMs/Agents, NIST AI RMF, MITRE ATLAS and other industry standards 🔒 Evaluation runs entirely locally, no data sent externally 🚦 Ships 7 real-time guardrails like ToxicityGuard for production use ⭐ 2.8k GitHub stars, 1,187+ commits and active ongoing development Just `pip install` it and pass your model callback, that low barrier to entry makes it easy to actually adopt. #LLMSecurity# #RedTeaming#

Anthropic is partnering with Accenture to embed evaluators within Anthropic, including red teaming models and conducting alignment assessments (Anthropic) (Visit Techmeme dot com for the link and full context!)

AI-Infra-Guard is an open-source, self-hosted red-teaming platform for AI builders. • Scan AI infrastructure for fingerprints and CVEs • Audit MCP servers and Agent Skills • Red-team Agent workflows and LLMs • Run locally with Docker; integrate via Web UI or API Build with more visibility:

Catching agent bugs before deploy, not after they hit production. LangSmith just announced a new capability for exactly that. Title: LangSmith Engine v2: Red Teaming and Automated Testing URL: 📝 Overview LangSmith Engine automatically detects issues and generates fixes, and has analyzed over 70 million traces since its May launch. Version 2 adds two new capabilities: red teaming and automated fix validation. ❓ Problems Solved Developers used to face a tradeoff: ship an unverified fix or spend time on manual validation. Subtle degradations like rising latency or inefficient execution paths often slipped past human review entirely. 💡 Method & Approach Engine analyzes production traces and repositories to understand agent behavior, then systematically tests for weaknesses like hallucinations and prompt violations before they surface in production. It also reproduces failures in a sandbox, generates fixes, iteratively validates them against the original failing inputs, and surfaces only the validated solutions for human review. 📊 Results ・Issue detection improved more than 2x on IssueBench ・Generated fixes are 25% more effective per Terminal-Bench-style metrics 🌍 Use Cases Now available for LangSmith Plus and Enterprise SaaS users, with self-hosted support coming soon. Red teaming and automated testing are in private beta for Deployment users. #LangSmith# #AIAgents#

Let's be real, we are NOT going to 'uninvent' digital intelligence. Instead, we should focus on how to steer it. Better evals, harder red-teaming, stronger institutions, and more transparency. We should not 'stop everything' either.

I am thrilled to announce that @beaconholdings has acquired @haizelabs, with me joining as VP of AI Research. We started Haize in 2024 to enable anyone to build reliable and safe AI. Through our red-teaming and safeguards work with the frontier labs; our observability, guardrail, and evaluation platform serving the world’s largest enterprises; and our pro bono SMB work, any customer could build AI they trusted with Haize. Joining Beacon lets us deliver the same trustworthy AI to those who need it most, and those most overlooked by Silicon Valley: the essential Main Street businesses the real world depends upon. Transitioning these essential businesses through the AI revolution is one of the most consequential responsible AI problems of our time. We couldn’t be more honored to tackle it with Beacon. Thank you to our customers, investors, and team for the journey of a lifetime. And thank you to Nilam, Goutham, Mark, and the Beacon team for the trust and opportunity. It’s time to get to work.

my account is not eligible 😑 no matter what i will continue to make original comparisons , posting news and i will start a jailbreak live session on X soon free of cost however i was inactive last 5-6 days i am focusing more on ai red teaming

I resigned from nothing today. I’ve spent the last three years doing independent open-source AI R&D, red teaming, and advocacy. The labs are racing straight to self-improving superintelligence and gambling with our lives. Which is why I’ll spend the next three years doing exactly what I’ve been doing, just at greater scale and speed. And the next. And the next. For as long as it fucking takes. No more thoughts below.

Today we are releasing GPT-5.6-Cyber. The model is our first large-scale attempt at directly improving capabilities for advanced cybersecurity tasks such as exploit development. We are finding it to be really quite strong for accelerating defensive work. We are using it across our stack for red-teaming, and our security researchers have used it to find and patch a huge host of 0-day vulnerabilities in open-source software.