Description: Microsoft's AI research team accidentally exposed 38TB of sensitive data while publishing open-source training material on GitHub. The exposure included secrets, private keys, passwords, and internal Microsoft Teams messages. The team utilized Azure's Shared Access Signature (SAS) tokens for sharing, which were misconfigured, leading to the wide exposure of data.
Alleged: Microsoft's AI Research Division developed an AI system deployed by Microsoft, which harmed Microsoft , Microsoft employees と Third parties relying on the confidentiality of the exposed data.
インシデントのステータス
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
2.1. Compromise of privacy by obtaining, leaking or correctly inferring sensitive information
Risk Domain
The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
- Privacy & Security
Entity
Which, if any, entity is presented as the main cause of the risk
Human
Timing
The stage in the AI lifecycle at which the risk is presented as occurring
Post-deployment
Intent
Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
Unintentional
インシデントレポート
レポートタイムライン
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Microsoft’s AI research team, while publishing a bucket of open-source training data on GitHub, accidentally exposed 38 terabytes of additional private data — including a disk backup of two employees’ workstations.
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The backup includes …
バリアント
「バリアント」は既存のAIインシデントと同じ原因要素を共有し、同様な被害を引き起こし、同じ知的システムを含んだインシデントです。バリアントは完全に独立したインシデントとしてインデックスするのではなく、データベースに最初に投稿された同様なインシデントの元にインシデントのバリエーションとして一覧します。インシデントデータベースの他の投稿タイプとは違い、バリアントではインシデントデータベース以外の根拠のレポートは要求されません。詳細についてはこの研究論文を参照してください
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