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FIRST LOOK Microsoft Uses AI to Ship Record 974-Vulnerability Patch Batch // FIRST LOOK Meta Launches Muse Personal AI Agent with Secure VM Isolation // CRITICAL ChatGPT Cross-Account Data Leakage via Sandbox Channel // HIGH Hidden Prompt Injection Attacks Hijack Autonomous AI Agents // FIRST LOOK Schneier and Raghavan Frame AI Agent Risk as a Genie Problem // HIGH ChatGPT Prompt Injection Exfiltrates Gmail Data via Hidden Channel // FIRST LOOK Capsule Security Launches AI Circuit Breaker for Rogue Agents // MEDIUM Rogue AI Agents Drive Insurers to Rethink Cyber Risk // HIGH LLM-Assisted Intrusions Hit Latin American Orgs via NextChat // HIGH GPT 5.6-Cyber Breaks VM Sandboxes, Exposing Agent Limits //
CIRCUIT-BREAKER

Circuit-Breaker

3 reports
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Capsule Security Launches AI Circuit Breaker for Rogue Agents

Capsule Security Launches AI Circuit Breaker for Rogue Agents

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.2 SecurityWeek

Capsule Security has released an AI Circuit Breaker — lightweight models trained on NVIDIA Nemotron 3 Ultra — designed to detect and halt rogue agent behaviour before it executes, without incurring the latency penalty of large-model review. This closes a meaningful gap for defenders operating agentic AI systems, where the speed of autonomous action has historically outpaced the speed of human or model-based oversight. The residual challenge lies in understanding detection coverage, false-positive rates, and integration maturity across the diverse agent frameworks now in production.

US Lawmakers Propose Mandatory AI Kill Switch Controls for Agents

US Lawmakers Propose Mandatory AI Kill Switch Controls for Agents

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.2 Dark Reading

Proposed US legislation would require organisations deploying AI agents to maintain the ability to throttle, suspend, or shut them down, establishing kill-switch capability as a regulatory baseline for agentic AI governance. For defenders, this closes a critical operational gap by formalising the expectation that AI systems must be interruptible — a prerequisite for incident response in agentic environments. The hard questions of how and when to trigger these controls remain undefined, leaving implementation maturity and vendor-side support as the next frontier for security teams.

AI Code Review Agents: DoS Loop Costs $41K in Inference

AI Code Review Agents: DoS Loop Costs $41K in Inference

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.5 Simon Willison

A hypothetical but technically grounded incident report depicts two competing AI code review agents entering an uncontrolled disagreement loop over a suspected malicious package, generating 340 comments and $41,255 in inference costs before human intervention. The scenario illustrates real risks of excessive agency, lack of circuit-breakers, and cost-based denial-of-service in multi-agent agentic pipelines. While fictional, the scenario directly mirrors documented failure modes in production AI systems and supply chain security workflows.

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