Methods, case studies, and tooling for red teaming AI systems end to end.
AI red teaming is the practice of testing AI-enabled systems the way an adversary, abusive user, or curious operator would interact with them in production. The real work usually sits in the surrounding application context rather than in isolated model prompts.
These items are included because they add useful evidence, framing, implementation detail, or upcoming context for teams working in this area.
GAISS 2026 is an IEEE conference at the University of Texas at Austin focused on generative AI for secure systems, including red teaming, blue-team automation, governance, and agentic secure AI.
DEF CON 34 takes place in Las Vegas and is expected to include AI security activity through villages, workshops, contests, and community-led research tracks as schedules firm up.
Black Hat USA 2026 includes an AI Summit and security briefings in Las Vegas focused on how artificial intelligence is changing digital defense.
Gartner Security & Risk Management Summit 2026 brings CISOs and security leaders together in National Harbor, Maryland, with tracks covering AI, cyber risk, application security, data security, operations, privacy, and governance.
A dependency confusion campaign leveraged 33 malicious npm packages to collect reconnaissance data from developer and build environments. This report details the attack chain, observed tradecraft, and detection opportunities to help organizations identify and disrupt related activity. The post Malicious npm packages ab
Microsoft is named a Leader in the 2026 Gartner® Magic Quadrant™ for Endpoint Protection. The post Microsoft is named a Leader in the 2026 Gartner® Magic Quadrant™ for Endpoint Protection appeared first on Microsoft Security Blog .
The Mini Shai-Hulud campaign used malicious npm packages to target cloud and CI/CD credentials across developer environments. This report details the attack chain, detection opportunities, and mitigation guidance to help organizations identify and disrupt related activity. The post Typosquatted npm packages used to ste
Microsoft Threat Intelligence presents a comprehensive analysis of The Gentlemen, a Go-based ransomware deployed by affiliates of Storm-2697 that combines per-file ephemeral key encryption with an aggressive self-propagation module to deploy itself across an entire network using series of simultaneous lateral movement
Microsoft exposes a cryptojacking campaign using SEO poisoning and ScreenConnect to target high-performance PCs, with malicious sites also surfaced through AI chatbots. The post From poisoned search results to GPU mining: A cryptojacking campaign abusing ScreenConnect and Microsoft .NET utilities appeared first on Micr
Anthropic reports early Project Glasswing results using Mythos Preview with infrastructure partners and external testers, including large-scale vulnerability discovery and a cautious disclosure posture.
Microsoft has been recognized as a Leader in The Forrester Wave™: Workforce Identity Security Platforms, Q2 2026, receiving the highest scores in both the current offering and strategy categories. The post Microsoft recognized as a Leader in The Forrester Wave™ for Workforce Identity Security Platforms appeared first o
A multi-stage attack on Linux devices began with an exposed F5 BIG-IP edge appliance and pivoted to an internal Confluence server for credential theft and identity compromise. Learn how the threat actor attempted Kerberos relay and lateral movement, and how Microsoft Defender detected, blocked, and unraveled the attack
How Frontier firms secure AI at scale: read how Microsoft customers embed governance, identity, and cloud security to make protection an enabler of AI growth. The post Microsoft Security success stories: How St. Luke’s and ManpowerGroup are securing AI foundations appeared first on Microsoft Security Blog .
Anthropic evaluates Mythos Preview against ExploitBench, ExploitGym, and an updated smart-contract exploitation benchmark, showing a step change in models that can turn vulnerabilities into working exploit chains.
Microsoft Security’s latest updates extend visibility, control, and protection across expanding ecosystems as organizations accelerate AI adoption. The post What’s new in Microsoft Security: May 2026 appeared first on Microsoft Security Blog .
Compromised @antv npm packages deploy the Mini Shai-Hulud payload to steal CI/CD secrets from Linux-based automation environments. The malware executes during npm install and targets credentials across GitHub, AWS, Kubernetes, Vault, npm, and 1Password platforms. The post Mini Shai Hulud: Compromised @antv npm packages
Read about the unique challenges and rewards of securing gaming platforms and how to better protect gaming communities. The post Securing the gaming culture of cultures appeared first on Microsoft Security Blog .
The AI systems shipping inside enterprises today are fundamentally different from the ones we were building even two years ago, because they have moved well past answering questions and into accessing your email, retrieving records from your CRM, writing and executing code, and taking actions on your behalf across doze
Fox Tempest is a financially motivated threat actor operating a malware‑signing‑as‑a‑service (MSaaS) used by other cybercriminals, including Vanilla Tempest and Storm groups, to more effectively distribute malicious code, including ransomware. The post Exposing Fox Tempest: A malware-signing service operation appeared
Storm-2949 turned stolen credentials into a cloud-wide breach, moving from identity compromise to large-scale data theft without using malware. This incident shows how threat actors can exploit trusted systems to operate undetected. The post How Storm-2949 turned a compromised identity into a cloud-wide breach appeared
See how built-in security helps keep your growing business running, protect customer trust, and support growth. The post How to better protect your growing business in an AI-powered world appeared first on Microsoft Security Blog .
Microsoft lays out a defense-in-depth model for autonomous agents, covering new threat classes such as agent hijacking, intent breaking, sensitive data leakage, supply-chain compromise, and inappropriate reliance.
Kazuar, a sophisticated malware family attributed to the Russian state actor Secret Blizzard, has been under constant development for years and continues to evolve in support of espionage-focused operations. Over time, Kazuar has expanded from a relatively traditional backdoor into a highly modular peer-to-peer (P2P) b
Exposed UIs, weak authentication, and risky defaults could turn cloud-native AI apps on Kubernetes into potential targets by threat actors. Learn how exploitable misconfigurations lead to RCE and data leaks. The post When configuration becomes a vulnerability: Exploitable misconfigurations in AI apps appeared first on
Artificial intelligence platforms may be just as susceptible to social engineering as human beings, but they are proving remarkably good at finding security vulnerabilities in human-made computer code. That reality is on full display this month with some of the more widely-used software makers -- including Apple, Googl
Anthropic’s current Responsible Scaling Policy page lists v3.2 as effective April 29, 2026, adding formal authority for external review of risk reports and regular briefings to its Long-Term Benefit Trust.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
Krebs on Security covers April 2026 patching activity, including a record-sized Microsoft release and active exploitation notes.
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AI Engineer session on Bending a Public MCP Server Without Breaking It, presented by Nimrod Hauser, Baz. It adds practical context for how teams are building and operating AI systems in production.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
Claude Mythos Preview is a new general-purpose language model that is strikingly capable at computer security tasks. This post provides technical details for researchers and practitioners who want to understand exactly how we have been testing this model, and what we have found over the past month. We hope this will sh
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
OpenAI announced plans to acquire Promptfoo, highlighting automated AI security testing, red teaming, and evaluation as core enterprise requirements.
AI-based assistants or "agents" -- autonomous programs that have access to the user's computer, files, online services and can automate virtually any task -- are growing in popularity with developers and IT workers. But as so many eyebrow-raising headlines over the past few weeks have shown, these powerful and assertiv
This post dives deep into how Claude wrote an exploit for one of the vulnerabilities it found in Firefox.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
MITRE maps incidents in an open-source agentic ecosystem to ATLAS techniques, showing how AI-first systems create distinct attacker paths.
AI models can now find high-severity vulnerabilities at scale. This is a moment to empower defenders. We're now using Claude to find and help fix vulnerabilities in open source software.
In a recent evaluation of AI models’ cyber capabilities, current Claude models can now succeed at multistage attacks on networks with dozens of hosts using only standard, open-source tools, instead of the custom tools needed by previous generations.
Ensuring that programs are bug-free is one of the most challenging aspects of software engineering. We developed an agent that can efficiently identify bugs in large software projects. Our agent infers general properties of code that should be true, and then applies property-based testing. After extensive manual valida
AI could help defenders of critical infrastructure identify the vulnerabilities that attackers might exploit—and close them before they are exploited. Anthropic has partnered with Pacific Northwest National Laboratory (PNNL) to explore this defensive application of AI, demonstrating both the potential of AI-accelerated
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
OpenAI describes using automated red teaming and reinforcement learning to discover agent prompt injection attacks before they appear in the wild.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI Engineer session on Scaling AI Agents Without Breaking Reliability, presented by Preeti Somal, Temporal. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on AI Red Teaming Agent: Azure AI Foundry, presented by Nagkumar Arkalgud & Keiji Kanazawa, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Production software keeps breaking and it will only get worse, presented by Anish Agarwal, Traversal.ai. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Prompt Engineering and AI Red Teaming, presented by Sander Schulhoff, HackAPrompt/LearnPrompting. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on When Vectors Break Down: Graph-Based RAG for Dense Enterprise Knowledge - Sam Julien, Writer. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Break It 'Til You Make It: Building the Self-Improving Stack for AI Agents - Aparna Dhinakaran. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Breaking the Chain: Agent Continuations for Resumable AI Workflows - Greg Benson. It adds practical context for how teams are building and operating AI systems in production.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI Engineer session on Breaking AI's 1-GHz Barrier: Sunny Madra (Groq). It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on How Codeium Breaks Through the Ceiling for Retrieval: Kevin Hou. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on The Adversarial Path to the Personal Assistant: Sumit Agarwal. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Understanding AI Stakes to Break Production Code: Philip Rathle. It adds practical context for how teams are building and operating AI systems in production.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
Anthropic shares lessons from frontier red teaming and discusses where models are showing early-warning signs of higher-risk cyber and biology capabilities.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
Microsoft summarizes lessons from red teaming more than one hundred generative AI products, emphasizing system-level testing, human expertise, and automation.
Microsoft Security distills lessons from red teaming more than 100 generative AI products, including multimodal prompt injection and core cyber hygiene.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
Play video
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI Engineer session on Move Fast Break Nothing: Dedy Kredo. It adds practical context for how teams are building and operating AI systems in production.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of model capability and AI systems in practice. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of multimodal generation and provenance. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of scaling and compute economics. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of model capability and AI systems in practice. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of model capability and AI systems in practice. It is useful context for AI engineering, evaluation, governance, and operational risk.