Four Go cryptographic API misuse detectors vary substantially in coverage; a new taxonomy of 14 classes and 7,473 real misuses were identified across 328 security-critical projects.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
AFGNN detects API misuses in Java code more effectively than prior methods by representing usage as graphs and clustering learned embeddings from self-supervised training.
citing papers explorer
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Evaluating Cryptographic API Misuse Detectors for Go
Four Go cryptographic API misuse detectors vary substantially in coverage; a new taxonomy of 14 classes and 7,473 real misuses were identified across 328 security-critical projects.
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AFGNN: API Misuse Detection using Graph Neural Networks and Clustering
AFGNN detects API misuses in Java code more effectively than prior methods by representing usage as graphs and clustering learned embeddings from self-supervised training.