drel
Legal

Third-party notices

The frameworks, standards and regulations below are the ones Drel's Framework library shows from a pinned copy of the publisher's document, and the items it added to MITRE ATLAS and the EU AI Act. They belong to their publishers. Each is shown as its license allows: below, the license, the attribution it asks for, and what Drel changed. Where a license doesn't let Drel quote a text, Drel shows its ids and titles and describes each item in its own words, marked “Drel's wording”. No publisher endorses Drel.

  • Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations

    National Institute of Standards and Technology (NIST) · E2025 (NIST AI 100-2e2025) · 2025-03 · source

    License
    US Government work (NIST Technical Series Publication)
    Attribution
    Vassilev A, Oprea A, Fordyce A, Anderson H, Davies X, Hamin M (2025) Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations. NIST Trustworthy and Responsible AI, NIST AI 100-2e2025. https://doi.org/10.6028/NIST.AI.100-2e2025. Republished courtesy of the National Institute of Standards and Technology.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by National Institute of Standards and Technology.

  • Agentic AI - Threats and Mitigations

    OWASP Top 10 for LLM Apps & Gen AI, Agentic Security Initiative · Version 1.1 · 2025-12 · source

    License
    CC BY-SA 4.0
    Copyright
    This document is licensed under Creative Commons, CC BY-SA 4.0
    Attribution
    OWASP Top 10 for LLM Apps & Gen AI, Agentic Security Initiative, "Agentic AI - Threats and Mitigations", Version 1.1 (December 2025), genai.owasp.org, licensed under CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). Threat descriptions reproduced unmodified.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by OWASP Top 10 for LLM Apps & Gen AI, Agentic Security Initiative.

  • AI Cloud Service Compliance Criteria Catalogue (AIC4)

    Federal Office for Information Security · 2021-02-02 · source

    License
    BSI Nutzungsbedingungen (terms of use): commercial use, including promotional use, requires a licence agreement with BSI; free downloads only for non-commercial purposes; verbatim quotation in quotation marks with a source reference is allowed without consent (Drel shows ids and its own wording until the publisher licenses more)
    Copyright
    © Federal Office for Information Security 2021
    Attribution
    Source: Federal Office for Information Security (BSI), "AI Cloud Service Compliance Criteria Catalogue (AIC4)", 2021, https://www.bsi.bund.de/SharedDocs/Downloads/EN/BSI/CloudComputing/AIC4/AI-Cloud-Service-Compliance-Criteria-Catalogue_AIC4.html
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by Federal Office for Information Security.

  • AI Data Security: Best Practices for Securing Data Used to Train & Operate AI Systems

    National Security Agency's Artificial Intelligence Security Center (AISC); Cybersecurity and Infrastructure Security Agency (CISA); Federal Bureau of Investigation (FBI); Australian Signals Directorate's Australian Cyber Security Centre (ASD's ACSC); New Zealand's Government Communications Security Bureau's National Cyber Security Centre (NCSC-NZ); United Kingdom's National Cyber Security Centre (NCSC-UK) · Ver. 1.0 · 2025-05 · source

    License
    TLP:CLEAR (US Government and partner-agency work; no open licence)
    Copyright
    This information is marked TLP:CLEAR. TLP:CLEAR information may be distributed without restriction. For more information on the Traffic Light Protocol, see cisa.gov/tlp/. — Disclaimer of Endorsement: The information and opinions contained in this document are provided “as is” and without any warranties or guarantees. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement, recommendation, or favoring by the United States Government, and this guidance shall not be used for advertising or product endorsement purposes.
    Attribution
    AI Data Security: Best Practices for Securing Data Used to Train & Operate AI Systems, Joint Cybersecurity Information, NSA AISC, CISA, FBI, ASD's ACSC, NCSC-NZ and NCSC-UK, May 2025, Ver. 1.0 (U/OO/157249-25 | PP-25-2301). Not an endorsement.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by National Security Agency's Artificial Intelligence Security Center.

  • Artificial intelligence — Data quality for analytics and machine learning (ML) (ISO/IEC 5259 series, parts 1–6)

    ISO/IEC · Edition 1 (every part) · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publications)
    Copyright
    Per part, as printed on its pages: © ISO/IEC 2024 – All rights reserved (parts 1–3), © ISO/IEC 2024 — All rights reserved (part 4, as printed in the SIS edition), © ISO/IEC 2025 – All rights reserved (part 5), © ISO/IEC 2026 – All rights reserved (part 6)
    Attribution
    ISO/IEC 5259 series, Artificial intelligence — Data quality for analytics and machine learning (ML), parts 1–6. © ISO/IEC. Part and clause titles only, as listed in each part's contents; the texts are available from ISO and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Artificial intelligence — Functional safety and AI systems

    ISO/IEC · Edition 1 · 2024-01-08 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2024 – All rights reserved
    Attribution
    ISO/IEC TR 5469:2024, Artificial intelligence — Functional safety and AI systems. © ISO/IEC 2024. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/81283.html) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Artificial Intelligence (AI) — Assessment of the robustness of neural networks — Part 1: Overview

    ISO/IEC · Edition 1 · 2021-03-10 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2021 – All rights reserved
    Attribution
    ISO/IEC TR 24029-1:2021, Artificial Intelligence (AI) — Assessment of the robustness of neural networks — Part 1: Overview. © ISO/IEC 2021. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/77609.html) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Artificial intelligence (AI) — Assessment of the robustness of neural networks — Part 2: Methodology for the use of formal methods

    ISO/IEC · Edition 1 · 2023-08-01 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2023 – All rights reserved
    Attribution
    ISO/IEC 24029-2:2023, Artificial intelligence (AI) — Assessment of the robustness of neural networks — Part 2: Methodology for the use of formal methods. © ISO/IEC 2023. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/79804.html) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile

    National Institute of Standards and Technology (NIST) · 2024-07 · source

    License
    US Government work (NIST Technical Series Publication)
    Attribution
    NIST AI 600-1, Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (July 2024), https://doi.org/10.6028/NIST.AI.600-1. Republished courtesy of the National Institute of Standards and Technology.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by National Institute of Standards and Technology.

  • Artificial Intelligence Security Verification Standard 1.01

    OWASP · 1.01 · 2026-10 · source

    License
    CC BY-SA 4.0
    Copyright
    Copyright © 2025-2026 The AISVS Project. Released under the Creative Commons Attribution-ShareAlike 4.0 International License. For any reuse or distribution, you must clearly communicate the license terms of this work to others.
    Attribution
    OWASP Artificial Intelligence Security Verification Standard (AISVS) 1.01, © 2025-2026 The AISVS Project, licensed under CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). Requirement text reproduced unmodified.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by OWASP.

  • Careful adoption of agentic AI services

    Australian Signals Directorate's Australian Cyber Security Centre (ASD's ACSC); United States Cybersecurity and Infrastructure Security Agency (CISA); National Security Agency (NSA); Canadian Centre for Cyber Security (Cyber Centre); New Zealand National Cyber Security Centre (NCSC-NZ); United Kingdom National Cyber Security Centre (NCSC-UK) · 2026-05-01 · source

    License
    CC BY 4.0
    Copyright
    © Commonwealth of Australia 2026. With the exception of the Coat of Arms and where otherwise stated, all material presented in this publication is provided under a Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/. For the avoidance of doubt, this means this license only applies to material as set out in this document.
    Attribution
    "Careful adoption of agentic AI services", ASD's ACSC with CISA, NSA, Canadian Centre for Cyber Security, NCSC-NZ and NCSC-UK, 2026. © Commonwealth of Australia 2026, licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Quoted unmodified; ids are Drel's references. Not an endorsement.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by Australian Signals Directorate's Australian Cyber Security Centre.

  • CIS Critical Security Controls v8.1 companion guides: Artificial Intelligence (AI) and Large Language Models (LLM) Companion Guide v1.0; Artificial Intelligence (AI) Agents Companion Guide v1.0; Model Context Protocol (MCP) Companion Guide v1.0

    Center for Internet Security, Inc. (CIS) · Companion Guide v1.0 (each guide), CIS Critical Security Controls v8.1 · 2026-04-20 · source

    License
    CC BY-NC-ND 4.0, with commercial use subject to CIS prior approval (Drel shows ids and its own wording until the publisher licenses more)
    Copyright
    This work is licensed under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 International Public License (the link can be found at https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode). To further clarify the Creative Commons license related to the CIS Controls® content, you are authorized to copy and redistribute the content as a framework for use by you, within your organization and outside of your organization for non-commercial purposes only, provided that (i) appropriate credit is given to CIS, and (ii) a link to the license is provided. Additionally, if you remix, transform, or build upon the CIS Controls, you may not distribute the modified materials. Users of the CIS Controls framework are also required to refer to (http://www.cisecurity.org/controls/) when referring to the CIS Controls in order to ensure that users are employing the most up-to-date guidance. Commercial use of the CIS Controls is subject to the prior approval of the Center for Internet Security, Inc. (CIS).
    Attribution
    CIS Critical Security Controls® v8.1 AI companion guides (AI and LLM; AI Agents; MCP), Companion Guide v1.0, Center for Internet Security, Inc., April 2026. Licensed under CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode). See https://www.cisecurity.org/controls/.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by Center for Internet Security, Inc..

  • CoSAI Risk Map (CoSAI-RM)

    Coalition for Secure AI (CoSAI), an OASIS Open Project · 2026-10-20 · source

    License
    Apache License 2.0
    Copyright
    Copyright 2025 Google LLC Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
    Attribution
    CoSAI Risk Map, risk-map/yaml/controls.yaml and risks.yaml, github.com/cosai-oasis/secure-ai-tooling at commit 622605a13faf. Copyright 2025 Google LLC. Licensed under the Apache License, Version 2.0. Titles and descriptions quoted unmodified; YAML paragraphs joined with blank lines by Drel.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by Coalition for Secure AI.

  • Cybersecurity — Artificial intelligence (AI) — Addressing security threats and compromises to AI systems

    ISO/IEC · Edition 1 · 2026-10-14 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2026 – All rights reserved
    Attribution
    ISO/IEC 27090:2026, Cybersecurity — Artificial intelligence (AI) — Addressing security threats and compromises to AI systems. © ISO/IEC 2026. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/27090) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Deploying AI Systems Securely: Best Practices for Deploying Secure and Resilient AI Systems

    U.S. National Security Agency's Artificial Intelligence Security Center (AISC); Cybersecurity and Infrastructure Security Agency (CISA); Federal Bureau of Investigation (FBI); Australian Signals Directorate's Australian Cyber Security Centre (ACSC); Canadian Centre for Cyber Security (CCCS); New Zealand National Cyber Security Centre (NCSC-NZ); United Kingdom's National Cyber Security Centre (NCSC-UK) · Ver. 1.0 · 2024-04 · source

    License
    TLP:CLEAR (US Government and partner-agency work; no open licence)
    Copyright
    This document is marked TLP:CLEAR. Recipients may share this information without restriction. Information is subject to standard copyright rules. For more on the Traffic Light Protocol, see cisa.gov/tlp/. — Disclaimer of endorsement: The information and opinions contained in this document are provided "as is" and without any warranties or guarantees. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement, recommendation, or favoring by the United States Government, and this guidance shall not be used for advertising or product endorsement purposes.
    Attribution
    Deploying AI Systems Securely: Best Practices for Deploying Secure and Resilient AI Systems, Joint Cybersecurity Information, NSA AISC, CISA, FBI, ASD's ACSC, CCCS, NCSC-NZ and NCSC-UK, April 2024, Ver. 1.0 (U/OO/143395-24 | PP-24-1538). Not an endorsement.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by U.S. National Security Agency's Artificial Intelligence Security Center.

  • Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML)

    ISO/IEC · Edition 1 · 2022-06-20 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2022 – All rights reserved
    Attribution
    ISO/IEC 23053:2022, Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML). © ISO/IEC 2022. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/74438.html) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Guidelines for secure AI system development

    UK National Cyber Security Centre (NCSC); US Cybersecurity and Infrastructure Security Agency (CISA); National Security Agency (NSA); Federal Bureau of Investigation (FBI); Australian Signals Directorate’s Australian Cyber Security Centre (ACSC); Canadian Centre for Cyber Security (CCCS); New Zealand National Cyber Security Centre (NCSC-NZ); Chile’s Government CSIRT; National Cyber and Information Security Agency of the Czech Republic (NUKIB); Information System Authority of Estonia (RIA); National Cyber Security Centre of Estonia (NCSC-EE); French Cybersecurity Agency (ANSSI); Germany’s Federal Office for Information Security (BSI); Israeli National Cyber Directorate (INCD); Italian National Cybersecurity Agency (ACN); Japan’s National center of Incident readiness and Strategy for Cybersecurity (NISC); Japan’s Secretariat of Science, Technology and Innovation Policy, Cabinet Office; Nigeria’s National Information Technology Development Agency (NITDA); Norwegian National Cyber Security Centre (NCSC-NO); Poland Ministry of Digital Affairs; Poland’s NASK National Research Institute (NASK); Republic of Korea National Intelligence Service (NIS); Cyber Security Agency of Singapore (CSA) · 1.0 · 2023-11-27 · source

    License
    Open Government Licence v3.0
    Copyright
    © Crown copyright 2023. Photographs and infographics may include material under licence from third parties and are not available for re-use. Text content is licenced for re-use under the Open Government Licence v3.0. (https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/)
    Attribution
    Contains public sector information licensed under the Open Government Licence v3.0 (https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/). Source: NCSC, CISA and partners, "Guidelines for secure AI system development", version 1.0, 27 November 2023, https://www.ncsc.gov.uk/collection/guidelines-secure-ai-system-development. Text reproduced unmodified.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by UK National Cyber Security Centre.

  • Information technology — Artificial intelligence — AI system life cycle processes

    ISO/IEC · Edition 1 · 2023-12-20 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2023 – All rights reserved
    Attribution
    ISO/IEC 5338:2023, Information technology — Artificial intelligence — AI system life cycle processes. © ISO/IEC 2023. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/81118.html) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Information technology — Artificial intelligence — Artificial intelligence concepts and terminology

    ISO/IEC · Edition 1 · 2022-07-19 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2022 – All rights reserved
    Attribution
    ISO/IEC 22989:2022, Information technology — Artificial intelligence — Artificial intelligence concepts and terminology. © ISO/IEC 2022. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/74296.html) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Information technology — Artificial intelligence — Guidance on risk management

    ISO/IEC · Edition 1 · 2023-02-06 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2023 – All rights reserved
    Attribution
    ISO/IEC 23894:2023, Information technology — Artificial intelligence — Guidance on risk management. © ISO/IEC 2023. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/77304.html) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Information technology — Artificial intelligence — Objectives and approaches for explainability and interpretability of machine learning (ML) models and artificial intelligence (AI) systems

    ISO/IEC · Edition 1 · 2025-09-05 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2025 – All rights reserved
    Attribution
    ISO/IEC TS 6254:2025, Information technology — Artificial intelligence — Objectives and approaches for explainability and interpretability of machine learning (ML) models and artificial intelligence (AI) systems. © ISO/IEC 2025. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/82148.html) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Information technology — Artificial intelligence — Overview of trustworthiness in artificial intelligence

    ISO/IEC · Edition 1 · 2020-05-28 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2020 – All rights reserved
    Attribution
    ISO/IEC TR 24028:2020, Information technology — Artificial intelligence — Overview of trustworthiness in artificial intelligence. © ISO/IEC 2020. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/77608.html) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Information technology — Artificial intelligence (AI) — Bias in AI systems and AI aided decision making

    ISO/IEC · Edition 1 · 2021-11-05 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2021 – All rights reserved
    Attribution
    ISO/IEC TR 24027:2021, Information technology — Artificial intelligence (AI) — Bias in AI systems and AI aided decision making. © ISO/IEC 2021. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/77607.html) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Information technology — Governance of IT — Governance implications of the use of artificial intelligence by organizations

    ISO/IEC · Edition 1 · 2022-04-08 · source

    License
    ISO/IEC copyright, all rights reserved (paywalled publication)
    Copyright
    © ISO/IEC 2022 – All rights reserved
    Attribution
    ISO/IEC 38507:2022, Information technology — Governance of IT — Governance implications of the use of artificial intelligence by organizations. © ISO/IEC 2022. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/56641.html) and national standards bodies.
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ISO/IEC.

  • Multilayer Framework for Good Cybersecurity Practices for AI

    European Union Agency for Cybersecurity (ENISA) · 2023-06-07 · source

    License
    CC BY 4.0
    Copyright
    COPYRIGHT NOTICE © European Union Agency for Cybersecurity (ENISA), 2023 This publication is licenced under CC-BY 4.0. Unless otherwise noted, the reuse of this document is authorised under the Creative Commons Attribution 4.0 International (CC-BY 4.0) licence (https://creativecommons.org/licenses/by/4.0/). This means that reuse is allowed, provided that appropriate credit is given and any changes are indicated. For any use or reproduction of photos or other material that is not under the ENISA copyright, permission must be sought directly from the copyright holders.
    Attribution
    Source: ENISA, "Multilayer Framework for Good Cybersecurity Practices for AI", June 2023, doi:10.2824/588830 (https://www.enisa.europa.eu/publications/multilayer-framework-for-good-cybersecurity-practices-for-ai). © European Union Agency for Cybersecurity (ENISA), 2023, licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). No changes made to the headings reproduced.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by European Union Agency for Cybersecurity.

  • OWASP AI Exchange

    OWASP Foundation · 2026-10-28 · source

    License
    CC0 1.0
    Copyright
    OWASP AI Exchange by The AI security community is marked with CC0 1.0 meaning you can use any part freely without copyright and without attribution. If possible, it would be nice if the OWASP AI Exchange is credited and/or linked to, for readers to find more information.
    Attribution
    OWASP AI Exchange (owaspai.org) by The AI security community, marked with CC0 1.0 (http://creativecommons.org/publicdomain/zero/1.0), read at commit 21d54f2 on 2026-10-29. Text reproduced unmodified.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by OWASP Foundation.

  • OWASP AI Testing Guide

    OWASP Foundation · Version 1.0 · 2025-11-26 · source

    License
    CC BY-SA 4.0
    Copyright
    The OWASP AI Testing Guide is published under the CC BY-SA 4.0 license.
    Attribution
    OWASP AI Testing Guide, Version 1.0 (November 2025), OWASP Foundation, licensed under CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). Test summaries reproduced unmodified.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by OWASP Foundation.

  • OWASP Large Language Model Security Verification Standard

    OWASP Foundation · 2.0 · 2026 · source

    License
    CC BY-SA 4.0
    Copyright
    Copyright © 2008–2026 The OWASP Foundation. This document is released under the Creative Commons Attribution-ShareAlike 4.0 International License. For any reuse or distribution, you must make clear to others the license terms of this work.
    Attribution
    OWASP Large Language Model Security Verification Standard (LLMSVS) v2.0, © The OWASP Foundation, licensed under CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). Requirement text reproduced unmodified.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by OWASP Foundation.

  • OWASP Machine Learning Security Top Ten

    OWASP Foundation · 2023 edition, Draft release v0.3 · 2023 · source

    License
    CC BY-SA 4.0
    Attribution
    OWASP Machine Learning Security Top Ten (2023 edition, draft release v0.3), OWASP Foundation, licensed under CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). Descriptions reproduced unmodified.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by OWASP Foundation.

  • Secure Software Development Practices for Generative AI and Dual-Use Foundation Models: An SSDF Community Profile

    National Institute of Standards and Technology (NIST) · 2024-07 · source

    License
    US Government work (NIST Technical Series Publication)
    Attribution
    NIST SP 800-218A, Secure Software Development Practices for Generative AI and Dual-Use Foundation Models: An SSDF Community Profile (July 2024), https://doi.org/10.6028/NIST.SP.800-218A. Republished courtesy of the National Institute of Standards and Technology.
    Changes
    Nothing: quoted unmodified.
    Endorsement
    Drel is not affiliated with or endorsed by National Institute of Standards and Technology.

  • Securing Artificial Intelligence (SAI); Baseline Cyber Security Requirements for AI Models and Systems

    ETSI · V2.1.1 · 2025-12 · source

    License
    ETSI copyright, all rights reserved (free PDF download; no reproduction without ETSI's written permission)
    Copyright
    Copyright Notification No part may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying and microfilm except as authorized by written permission of ETSI. The content of the PDF version shall not be modified without the written authorization of ETSI. The copyright and the foregoing restriction extend to reproduction in all media. © ETSI 2025. All rights reserved.
    Attribution
    ETSI EN 304 223 V2.1.1 (2025-12), "Securing Artificial Intelligence (SAI); Baseline Cyber Security Requirements for AI Models and Systems". © ETSI 2025. All rights reserved. Provision ids and phase and principle titles cite ETSI; provision summaries are Drel's wording. Full text: https://www.etsi.org/deliver/etsi_en/304200_304299/304223/02.01.01_60/en_304223v020101p.pdf
    Changes
    Ids and titles as published; descriptions in Drel's wording.
    Endorsement
    Drel is not affiliated with or endorsed by ETSI.

  • Securing Artificial Intelligence (SAI); Guide to Cyber Security for AI Models and Systems

    ETSI · V1.1.1 · 2025-05 · source

    License
    ETSI copyright, all rights reserved (free PDF download; no reproduction without ETSI's written permission)
    Copyright
    Copyright Notification No part may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying and microfilm except as authorized by written permission of ETSI. The content of the PDF version shall not be modified without the written authorization of ETSI. The copyright and the foregoing restriction extend to reproduction in all media. © ETSI 2025. All rights reserved.
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    ETSI TR 104 128 V1.1.1 (2025-05), "Securing Artificial Intelligence (SAI); Guide to Cyber Security for AI Models and Systems". © ETSI 2025. All rights reserved. Full text: https://www.etsi.org/deliver/etsi_tr/104100_104199/104128/01.01.01_60/tr_104128v010101p.pdf
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  • Securing Machine Learning Algorithms

    European Union Agency for Cybersecurity (ENISA) · 2021-12-14 · source

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    Copyright
    COPYRIGHT NOTICE © European Union Agency for Cybersecurity (ENISA), 2021 Reproduction is authorised provided the source is acknowledged. Copyright for the image on the cover: © Shutterstock For any use or reproduction of photos or other material that is not under the ENISA copyright, permission must be sought directly from the copyright holders.
    Attribution
    Source: ENISA, "Securing Machine Learning Algorithms", December 2021, DOI 10.2824/874249 (https://www.enisa.europa.eu/publications/securing-machine-learning-algorithms). © European Union Agency for Cybersecurity (ENISA), 2021. Reproduction is authorised provided the source is acknowledged. Reproduced unmodified.
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  • Software Bill of Materials for AI – Minimum Elements

    G7 Cybersecurity Working Group: Germany's Federal Office for Information Security (BSI), Italy's National Cybersecurity Agency (ACN), France's National Cybersecurity Agency (ANSSI), Canada's Communications Security Establishment (CSE), the US Cybersecurity and Infrastructure Security Agency (CISA), UK's National Cyber Security Centre (NCSC) and Japan's National Cybersecurity Office (NCO), in collaboration with the EU Commission · 2026-05-12 · source

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    No licence statement (multi-government work)
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    Software Bill of Materials for AI – Minimum Elements, G7 Cybersecurity Working Group (BSI, ACN, ANSSI, CSE, CISA, NCSC, NCO, in collaboration with the EU Commission), 2026. Not an endorsement.
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  • Software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Quality model for AI systems

    ISO/IEC · Edition 1 · 2023-06-28 · source

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    ISO/IEC copyright, all rights reserved (paywalled publication)
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    © ISO/IEC 2023 – All rights reserved
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    ISO/IEC 25059:2023, Software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Quality model for AI systems. © ISO/IEC 2023. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/80655.html) and national standards bodies.
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  • Systems and software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Guidance for quality evaluation of artificial intelligence (AI) systems

    ISO/IEC · Edition 1 · 2024-01-24 · source

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    ISO/IEC copyright, all rights reserved (paywalled publication)
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    © ISO/IEC 2024 – All rights reserved
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    ISO/IEC TS 25058:2024, Systems and software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Guidance for quality evaluation of artificial intelligence (AI) systems. © ISO/IEC 2024. Clause numbers and titles only, as listed in the document's contents; the text is available from ISO (https://www.iso.org/standard/82570.html) and national standards bodies.
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  • Taxonomy of Failure Modes in Agentic AI Systems, Version 2.0

    Microsoft AI Red Team · 2.0 · 2026-04 · source

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    Microsoft AI Red Team, "Taxonomy of Failure Modes in Agentic AI Systems, Version 2.0", April 2026. Failure-mode names quoted; descriptions are Drel's wording. Not an endorsement.
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  • The NIST Cybersecurity Framework (CSF) 2.0

    National Institute of Standards and Technology (NIST) · 2.0 · 2024-02-26 · source

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    US Government work (NIST Technical Series Publication)
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    NIST Cybersecurity Framework (CSF) 2.0, NIST CSWP 29 (February 26, 2024), https://doi.org/10.6028/NIST.CSWP.29. Republished courtesy of the National Institute of Standards and Technology.
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  • Threat Modeling AI/ML Systems and Dependencies; Failure Modes in Machine Learning

    Microsoft · 2019-11 · source

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    Microsoft, "Threat Modeling AI/ML Systems and Dependencies" and "Failure Modes in Machine Learning" (Microsoft Learn, November 2019, updated 2025-03-12). Names quoted; descriptions are Drel's wording. Not an endorsement.
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  • EU AI Act

    European Union · 2024-07-12 · source

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    Reuse of Commission documents, Commission Decision 2011/833/EU (EUR-Lex legal notice)
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    © European Union, https://eur-lex.europa.eu/
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    Regulation (EU) 2024/1689 (Artificial Intelligence Act), OJ L, 2024/1689, 12.7.2024, ELI: http://data.europa.eu/eli/reg/2024/1689/oj. © European Union. Reuse authorised under Commission Decision 2011/833/EU. Only the Official Journal of the European Union is authentic.
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  • MITRE ATLAS

    MITRE · 2026.09 · 2026-09-15 · source

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    Copyright 2021-2026 MITRE
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    MITRE ATLAS™ data, release 2026.09, github.com/mitre-atlas/atlas-data (tag v2026.09, commit 3259f388d19c). Copyright 2021-2026 MITRE. Licensed under the Apache License, Version 2.0. Names and descriptions quoted unmodified.
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