Add section 2.3.3 Cross-context data leakage through shared account reuse#103
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macsplit wants to merge 1 commit intoOWASP:mainfrom
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Add section 2.3.3 Cross-context data leakage through shared account reuse#103macsplit wants to merge 1 commit intoOWASP:mainfrom
macsplit wants to merge 1 commit intoOWASP:mainfrom
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…ount reuse Adds a new threat definition under "2. Threats through use" describing cross-context data leakage caused by sharing AI/LLM accounts or API keys across multiple environments or devices. Includes: - Definition and impact of account-level data crossover - Clarification on implicit leakage via cloud-level credential scope - Controls (#SEPARATE API KEYS) and detection guidance - Reference to ISO/IEC 42001 and ENISA Annex C This contribution documents an emerging, low-prevalence but realistic risk where pooling credits or contexts across tools can lead to unintended prompt or data exposure between environments.
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Add section 2.3.3 Cross-context data leakage through shared account reuse
🧩 Summary
This PR adds a new subsection (2.3.3) under “2. Threats through use” in the OWASP AI Security & Privacy Guide.
It introduces the emerging risk of cross-context data leakage that can occur when users share an AI or LLM account (or API credentials) across multiple devices, environments, or applications.
🔍 Details
🧱 Files Changed
content/docs/2_threats_through_use.md— added section 2.3.3 Cross-context data leakage through shared account reuse🎯 Impact
This contribution improves the guide’s coverage of runtime confidentiality risks in AI model usage.
It documents a subtle but realistic scenario where shared credentials or account contexts create unintended data exposure between environments, helping practitioners design safer credential-scoping and deployment patterns for LLM-based systems.