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todaySeptember 3, 2025

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Agentic AI Security + Agentic AI Security Digest admin

Top Agentic AI Security Resources — September 2025

Explore the Top Agentic AI Resources to stay informed about the most pressing risks and defenses in the field. As autonomous agents gain new capabilities—reasoning, memory, tool use—they also introduce unique security challenges. This collection covers the latest research, real-world exploits, and AI red teaming strategies exposing how Agentic AI ...

todayMay 5, 2025

  • 168
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Secure AI Weekly admin

Towards Secure AI Week 17 — AI Guardrails Under Pressure as Jailbreaking Techniques Advance

Enterprise use of generative AI is expanding, but so is the sophistication of attacks targeting these systems. New jailbreak methods are achieving nearly 100% success rates, even on well-aligned models like GPT-4 and Llama3, while recent research exposes vulnerabilities in memory, prompt interpretation, and cross-tool coordination protocols like MCP. At ...

todayApril 28, 2025

  • 154
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Secure AI Weekly admin

Towards Secure AI Week 16 — Can Your AI Agents Really Coordinate Safely?

As generative AI adoption accelerates, so do the security challenges that come with it. New research shows that even advanced large language models (LLMs) can be jailbroken with evolving techniques, while multi-agent AI systems introduce fresh risks at the communication and coordination layers. Cybercriminals are also scaling attacks using GenAI ...

todayApril 9, 2025

  • 49
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Secure AI Weekly admin

Towards Secure AI Week 13 – Don’t Trust AI Blindly

Critical AI Security Guidelines v1.1 – Now Available SANS The SANS Institute has released the Critical AI Security Guidelines v1.0, offering a structured framework for protecting AI technologies across their lifecycle. The guidelines stress that securing AI is not just a technical issue but a strategic imperative—one that requires tight ...

todayApril 2, 2025

  • 54
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Secure AI Weekly admin

Towards Secure AI Week 12 – New NIST AI Security Efforts

NIST AI 100-2 E2025. Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations NIST, March, 2025 The National Institute of Standards and Technology (NIST) has released a report titled “Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations” (NIST AI 100-2 E2025). The report categorizes AML ...