Verified70% confidenceCautionExact time
Large AI models suffer from hallucination problems, sometimes generating code that appears correct but actually contains logical errors, security vulnerabilities, or performance defects without proactively disclosing this.
4
Sources
70%
Confidence
Long-term
Relevance
7/25/2026
First Seen
Sources
Related Claims
VerifiedAI-generated code suffers from hallucination defects, including references to non-existent library functions, logically erroneous code, and version mismatches caused by training data cutoffs.85% similarVerifiedWhen code volume exceeds the model's effective context window, AI may hallucinate, identifying vulnerabilities that do not exist or raising unnecessary questions about correct code.83% similarUnverifiedAI生成的Issue具有以下典型特征：对根本原因的完全臆测、伪造的最小复现案例、错误的实现策略建议、类比到错误的相邻代码、冗长的错误类别列表81% similar
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