SymTEE combines AST slicing with LLM-generated KLEE harnesses and mock TEE environments to detect missing input validation, reporting 100% precision and 92.3% recall on 26 vulnerabilities at $0.05 average cost.
arXiv:2502.15281 [cs.CR]
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.SE 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
TEERepair uses a DSL to define repair templates and LLMs to create context-specific patches for TEE partitioning issues, reporting 87.6% success on a new benchmark and merged fixes in real projects.
citing papers explorer
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Finding Missing Input Validation in TEEs via LLM-Assisted Symbolic Execution
SymTEE combines AST slicing with LLM-generated KLEE harnesses and mock TEE environments to detect missing input validation, reporting 100% precision and 92.3% recall on 26 vulnerabilities at $0.05 average cost.
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Automated Repair of TEE Partitioning Issues via DSL-Guided and LLM-Assisted Patching
TEERepair uses a DSL to define repair templates and LLMs to create context-specific patches for TEE partitioning issues, reporting 87.6% success on a new benchmark and merged fixes in real projects.