CodeQL detected 171 CVEs total, with 83 caught by a prior version before the fix; detections were often actionable within the vulnerable file but not stable across tool versions.
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4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
RealVuln benchmark finds security-specialized scanners outperform general-purpose LLMs and rule-based SAST tools on hand-labeled vulnerable Python code under F3 scoring, with all artifacts released.
PoisonCap uses a new poison capability format to deliver strict use-after-free and initialization safety for CHERI systems with no fundamental overhead over Cornucopia baselines.
Text fine-tuning of 8B LLMs on C/C++ vulnerability data inflates cross-language false-positive rates through surface-cue memorization, which an AST inference probe can partially reverse while direct AST fine-tuning cannot.
citing papers explorer
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Longitudinal Analyses of SAST Tools: A CodeQL Case Study
CodeQL detected 171 CVEs total, with 83 caught by a prior version before the fix; detections were often actionable within the vulnerable file but not stable across tool versions.
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RealVuln: Benchmarking Rule-Based, General-Purpose LLM, and Security-Specialized Scanners on Real-World Code
RealVuln benchmark finds security-specialized scanners outperform general-purpose LLMs and rule-based SAST tools on hand-labeled vulnerable Python code under F3 scoring, with all artifacts released.
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PoisonCap: Efficient Hierarchical Temporal Safety for CHERI
PoisonCap uses a new poison capability format to deliver strict use-after-free and initialization safety for CHERI systems with no fundamental overhead over Cornucopia baselines.
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How Code Representation Shapes False-Positive Dynamics in Cross-Language LLM Vulnerability Detection
Text fine-tuning of 8B LLMs on C/C++ vulnerability data inflates cross-language false-positive rates through surface-cue memorization, which an AST inference probe can partially reverse while direct AST fine-tuning cannot.