news • Aug 5, 2026
The 100 BTC Dare Misses the Real Agent-Security Lesson
Why the 100 BTC dare matters less than the security boundary around AI agents and how to control egress, tools, approvals and runtime actions.
Read more →Insights on AI security, agentic systems, and emerging threats.
Why the 100 BTC dare matters less than the security boundary around AI agents and how to control egress, tools, approvals and runtime actions.
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Hugging Face's July 2026 incident shows what happens when the model supply chain itself is compromised. Scope-based identity isn't enough — agentic security needs zero-trust, intent-based identity and a physically separate guardrail engine.
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A practical checklist for securing MCP-connected AI agents, covering tool access, permissions, third-party servers, runtime controls, and trust boundaries.
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AI agent harnesses turn models into operational systems. Learn where agentic trust boundaries fail and how to secure inputs, memory, tools, and actions.
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dwaar red teaming helps teams test AI agents before deployment by mapping workflows, running adversarial attacks, identifying vulnerabilities, and generating reproducible security findings.
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For decades, enterprise security has been built around a simple question: who is the user, and what are they allowed to access? Identity and Access Management has solved ...
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How dwaar.ai used layered reconnaissance and multi-turn prompt injection to turn an AI test-failure analyzer into a remote-code-execution...
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Why Enterprise AI Needs an Intent-Aware Policy Plane? Learn why logs and visibility alone cannot secure enterprise AI—and how adversarial testing, intent-aware policies, and runtime enforcement can keep agents within their authorized boundaries.
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AI red teaming and VAPT test different security risks. Learn how AI red teaming goes beyond traditional VAPT to test prompts, context, tools, guardrails, and agent behavior.
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The real risk is no longer just that a model may produce an unsafe answer. The bigger risk is that an agent may take an unsafe action — using real tools, permissions, data, and business workflows. That is why the Model Context Protocol...
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Model guardrails and cloud controls are useful, but agentic applications need prompt-based red teaming, evidence-backed posture reports, and runtime policy enforcement.
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Why the future of AI agent security is about trajectories, not just prompts.
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The Agentic AI Security market is projected to grow from $1.65B in 2026 to $13.52B by 2032.
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