Autonomous AI systems that plan, decide, and act across workflows are transforming how organisations deliver mission-critical services. This session shares security-first architecture best practices for designing, deploying, and governing agentic AI in high-assurance environments, drawing from Australia's Information Security Manual (ISM) and AWS security frameworks. Discover practical patterns for architecting proactive, intelligent services while maintaining security, transparency, and operational resilience through defense-in-depth strategies and purpose-built AWS capabilities.
What this session is about
Playbook
Editorial commentary · what to actually do about this on Monday
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- cybersecurity-insiders.com Agent safety & prompt injection
cybersecurity-insiders.com
Security Risk Analysis: A report from Cybersecurity Insiders outlines that autonomous AI agents are presenting new security challenges that many Chief Information Security Officers (CISOs) were not prepared for. Risk: Rapidly evolving autonomous agent capabilities that act withou
- agentplace.io high confidence AI agent regulation & policy
Agent Liability Frameworks: Legal and Compliance ...
OWASP released the 'Top 10 for Agentic Applications 2026', establishing the first dedicated security framework for autonomous AI agents to address vulnerabilities and risks associated with agentic AI systems.
- builder.aws.com high confidence Multi-agent collaboration patterns
Enterprise Swarm Intelligence: Building Resilient Multi- ...
ADK-TS has been released as a TypeScript-native AI agent framework that supports the construction of sophisticated multi-agent systems using hierarchical, parallel, and sequential agent architectures for enterprise-grade applications.
- microsoft.github.io high confidence Agent identity & delegation
Data Provenance Model - Agent Governance Toolkit
The 'Agent Provenance' pattern (also known as Agent Attribution or Authorship Provenance) has been published in the Encyclopedia of Agentic Coding Patterns. It defines a method for recording the full lineage of an artifact—including the agent, model, harness, instruction file, pe
- varonis.com high confidence Agent safety & prompt injection
Phishing for Lobsters: How We Tricked OpenClaw into ... - Varonis
Policy/Funding Proposal: Google DeepMind and partners (including Schmidt Sciences) announced a $10 million technical research funding call to strengthen multi-agent AI safety. Risk: The potential for unsafe autonomous interactions and long-term systemic risks associated with the
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