{"@ID": "1446", "@Name": "Weaknesses That are Specific to AI/ML Technology", "@Status": "Incomplete", "Summary": "This category identifies weaknesses that are uniquely applicable to AI/ML technology.", "Relationships": {"Has_Member": [{"@CWE_ID": "1039", "@View_ID": "1448"}, {"@CWE_ID": "1426", "@View_ID": "1448"}, {"@CWE_ID": "1427", "@View_ID": "1448"}, {"@CWE_ID": "1434", "@View_ID": "1448"}]}, "References": {"Reference": [{"@External_Reference_ID": "REF-1522"}, {"@External_Reference_ID": "REF-1523"}, {"@External_Reference_ID": "REF-1525"}]}, "Mapping_Notes": {"Usage": "Prohibited", "Rationale": "This entry is a Grouping. Using groupings for mapping has been discouraged since 2019. They are informal organizational groupings of weaknesses that can help CWE users with data aggregation, navigation, and browsing. However, they are not weaknesses in themselves.", "Comments": "CWE users might be tempted to use this CWE for mapping, but it is a category (see Reasons). Mappers should consider whether a weakness is unique to AI/ML (in which case a high-level Pillar or class might still apply), or if it is a general software weakness that happens to appear in AI/ML related software.", "Reasons": {"Reason": [{"@Type": "Grouping"}, {"@Type": "Frequent Misuse"}]}}, "Notes": {"Note": [{"@Type": "Maintenance", "#text": "This category is likely to be updated frequently in future versions. See Research Gaps."}, {"@Type": "Research Gap", "#text": "As of CWE 4.20, it is still difficult to distinguish common AI/ML related attacks from the underlying weaknesses. The CWE AI Working Group has had many discussions about this general topic. Much of the latest research has focused on the attacks, and/or characterizing the underlying design and implementation of AI/ML related systems. From a CWE perspective, the distinction between \"control\" and \"data\" is not necessarily as deep as currently considered within the AI/ML community, since most weaknesses are characterized in terms of potentially insecure \"behavior\" - whether that behavior occurred due to design, insecure code, insecure configuration, or data-driven behaviors such as AI/ML. Since AI/ML is frequently derived from repositories of software that consume AI/ML components - many public reports of AI/ML vulnerabilities ultimately result from commonly-occurring weaknesses that appear in most kinds of software. There are several weakness-focused research efforts within the industry, but these efforts are still in the early stages."}]}, "Content_History": {"Submission": {"Submission_Name": "CWE Content Team", "Submission_Organization": "MITRE", "Submission_Date": "2026-04-27", "Submission_Version": "4.20", "Submission_ReleaseDate": "2026-04-30"}, "Modification": {"Modification_Name": "CWE Content Team", "Modification_Organization": "MITRE", "Modification_Date": "2026-10-28", "Modification_Version": "5.0", "Modification_ReleaseDate": "2026-10-28", "Modification_Comment": "updated Mapping_Notes, Type"}}, "entry_type": "Grouping"}