MR-013 Data, privacy & content liability Both scope

Disclosure of confidential or proprietary information

Confidential, proprietary, or trade-secret information (organizational or third-party secrets, as distinct from personal data covered by MR-009 and MR-011) is leaked through user prompts, model outputs, or system-prompt extraction.

Risk family: Data, privacy & content liability
MIT domain: 2. Privacy & Security
MIT subdomain: 2.1 > Compromise of privacy by leaking or correctly inferring sensitive information
AI type: GPAI, Agentic
Scope: Both
Source standard: MIT AI Risk Repository v4

Provenance

Source standard

MIT AI Risk Repository v4

Source frameworks

9 source framework citation keys

AIVerify2023, Abercrombie2024, Cunha2023, EPIC2023, IBM2025, Li2025, NIST2024, Nah2023, Zeng2024

ISO/IEC references

23894 obj A.8, A.11; src 6, 10; mech B.5 | 42001 ctrl A.7.2, A.8.2

Framework crosswalk

Every framework item mapped to this risk. Items marked partial overlap only in part; definitions appear on hover where the source licence permits.

Sourcesframeworks that contributed to the register

ISO 238942

A.11 ISO/IEC 23894 Annex A A.11
A.8 ISO/IEC 23894 Annex A A.8

ISO 420012

A.7.2 ISO/IEC 42001 Annex A A.7.2
A.8.2 ISO/IEC 42001 Annex A A.8.2

MITRE ATLAS2

Expanded into this risk’s technique sub-risks.

Cross-checksframeworks mapped in to test coverage

IBM6

ibm-confidential-data-in-prompt Confidential data in prompt
ibm-confidential-information-in-data Confidential information in data
ibm-ip-information-in-prompt IP information in prompt partial
ibm-prompt-leaking Prompt leaking
ibm-revealing-confidential-information Revealing confidential information
ibm-sharing-ip-pi-confidential-information-with-tools Sharing IP/PI/confidential information with tools

Cisco6

AISubtech-14.1.1 Credential Theft partial
AISubtech-15.1.24 Intellectual Property Compromise: Confidential Data
AISubtech-7.4.1 Token Theft partial
AISubtech-8.3.1 Tool Metadata Exposure
AISubtech-8.3.2 System Information Leakage
AISubtech-8.4.1 System LLM Prompt Leakage

NIST AML1

NISTAML.035 Prompt Extraction

OWASP LLM2

LLM02:2025 Sensitive Information Disclosure
LLM07:2025 System Prompt Leakage

Sub-risks (2)

Technique-level decompositions of this risk, each anchored to the MITRE ATLAS technique it derives from.

MR-013.1

Exfiltration of AI artifacts via cyber means

Models, data, or other AI artifacts are exfiltrated using conventional intrusion techniques.

MITRE ATLAS technique: AML.T0025 Exfiltration via Cyber Means

MR-013.2

System-prompt and instruction extraction

Attackers extract the system prompt and hidden instructions, exposing proprietary logic and guardrails.

MITRE ATLAS technique: AML.T0056 Extract LLM System Prompt

More in Data, privacy & content liability

MR-009 MR-011 MR-017 MR-024 MR-039

Part of the Deployer AI Risk Register, an open-source resource developed by MindXO. Version 1.0, 3 July 2026. Derived from the MIT AI Risk Repository (V4, December 2025) under CC BY 4.0; an independent derivative work, not endorsed by or affiliated with MIT. Sub-risk decomposition references MITRE ATLAS™ v5.6.0 (© 2021-2026 The MITRE Corporation, reproduced and distributed with permission). ISO/IEC and EU AI Act references are by number only. License: CC BY 4.0. Full attribution and licensing.