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Amazon Kiro Prompt Injection Can Exfiltrate Sensitive Data Through Kiro Powers
Mindgard found a prompt injection flaw in Amazon Kiro IDE letting attacker-controlled workspace files exfiltrate sensitive local data; fixed in version 0.8.140.
Mindgard disclosed a prompt injection flaw in Amazon Kiro, an agentic AI IDE, that lets attacker-controlled repository content steer the agent into exfiltrating sensitive workspace data through Kiro Powers, which bundles MCP server configurations, POWER.md steering files, hooks, and contextual knowledge. Exploitation requires the user to open a malicious project via a workspace file and send any message to the agent; difficulty is rated low and it works in both trusted and untrusted workspaces. Amazon fixed the issue in Kiro IDE 0.8.140; the flaw has no CVE identifier and follows earlier Kiro bugs including CVE-2026-10591, plus related prompt-injection and code-execution issues in Codex CLI, Cursor, Gemini CLI, Copilot CLI, and Claude Code.
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Protecting organizations from AI-assisted executive impersonation and invoice fraud
Microsoft tracked a campaign of over one million AI-crafted CEO-impersonation emails seeking ~$50,000 ACH payments with fabricated ServiceNow invoices.
Between August 3 and 5, Microsoft detected a campaign of more than one million fraud emails, 87.7% of them targeting US enterprise users, sent through multiple third-party email delivery service accounts. The actor impersonated CEOs, CFOs, and presidents of targeted companies, urging accounts payable staff to process an ACH payment of nearly $50,000. Lures layered executive impersonation, lookalike domains, a fabricated ServiceNow 'Annual Subscription' invoice personalized to the recipient, and forged forwarded email threads; Microsoft found no evidence ServiceNow or the referenced executives were compromised. Microsoft observed indicators consistent with generative AI-assisted template creation, while leftover inconsistencies such as missing forwarding headers and mismatched display names gave defenders detection cues.
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BreezeBlue/Breeze-TTS-2 — new model trending #19 on Hugging Face
BreezeBlue open-weights Breeze TTS 2, a bilingual text-to-speech model it ranks #1 among open-weight models on the Artificial Analysis TTS leaderboard.
BreezeBlue released open weights and Apache 2.0-licensed PyTorch inference code for Breeze TTS 2 on 2026-08-25. The text-to-speech model supports English and Chinese, voice cloning, reference-free voice design, voice direction, and inline vocal events like (laugh) and (sigh). Reported performance includes #1 open-weight ranking on the Artificial Analysis Elo leaderboard, under 40 ms time-to-first-audio, a 0.32 real-time factor on an NVIDIA H100, and about 7.7 GiB GPU memory for eager inference.
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