Incidente 571: translated-es-Accidental Exposure of 38TB of Data by Microsoft's AI Research Team
Descripción: translated-es-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.
Entidades
Ver todas las entidadesAlleged: Microsoft's AI Research Division developed an AI system deployed by Microsoft, which harmed Microsoft , Microsoft employees y Third parties relying on the confidentiality of the exposed data.
Estadísticas de incidentes
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
Informes del Incidente
Cronología de Informes

- El equipo de investigación de IA de Microsoft, mientras publicaba un conjunto de datos de capacitación de código abierto en GitHub, expuso accidentalmente 38 terabytes de datos privados adicionales, incluida una copia de seguridad en disco…
Variantes
Una "Variante" es un incidente de IA similar a un caso conocido—tiene los mismos causantes, daños y sistema de IA. En lugar de enumerarlo por separado, lo agrupamos bajo el primer incidente informado. A diferencia de otros incidentes, las variantes no necesitan haber sido informadas fuera de la AIID. Obtenga más información del trabajo de investigación.
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