[github-actions]

IEEE S&P 2026 DOI-only candidates.
Source: https://sp2026.ieee-security.org/accepted-papers.html
Summary: {'cycles': {'cycle1': 5, 'cycle2': 11}, 'statuses': {'verified': 14, 'pending_scope': 2}, 'additions': 14}
Only verified DOI records are proposed. Pending candidates are not added.
Review scope and bibliographic matches before merging. No automatic merge.

• Camveil: Unveiling Security Camera Vulnerabilities through Multi-Protocol Coordinated Fuzzing (cycle1, verified): https://doi.org/10.1109/sp63933.2026.00002
• SmuFuzz: Enable Deep System Management Mode Fuzzing in Fully Featured UEFI Runtime Environment (cycle1, verified): https://doi.org/10.1109/sp63933.2026.00011
• zkFuzz: Foundation and Framework for Effective Fuzzing of Zero-Knowledge Circuits (cycle1, verified): https://doi.org/10.1109/sp63933.2026.00049
• deepSURF: Detecting Memory Safety Vulnerabilities in Rust Through Fuzzing LLM-Augmented Harnesses (cycle1, verified): https://doi.org/10.1109/sp63933.2026.00060
• Fizzle: A Framework for Deterministic and Reproducible Network Fuzzing (cycle1, verified): https://doi.org/10.1109/sp63933.2026.00091
• StepStone: LLM-Based GPU Kernel Driver Fuzzing via User-Space Libraries (cycle2, verified): https://doi.org/10.1109/sp63933.2026.00124
• Jazzer: Coverage-Guided Fuzzing for Semantic Vulnerabilities in the Java Ecosystem (cycle2, verified): https://doi.org/10.1109/sp63933.2026.00134
• xDup: Privacy-Preserving Deduplication for Humanitarian Organizations using Fuzzy PSI (cycle2, pending_scope): Keyword occurs only in Fuzzy; maintainer scope review required
• Stop Starving or Stuffing Me: Boosting Firmware Fuzzing Efficiency with On-demand Input Delivery (cycle2, verified): https://doi.org/10.1109/sp63933.2026.00155
• TrigFuzz: Triggering Conditions Guided Directed Fuzzing (cycle2, verified): https://doi.org/10.1109/sp63933.2026.00156
• Efficient Fuzzy Private Set Intersection from Secret-shared OPRF (cycle2, pending_scope): Keyword occurs only in Fuzzy; maintainer scope review required
• Fuzzing the Physical Space: Physics-Aware Testing of Black-Box Industrial Control Systems (cycle2, verified): https://doi.org/10.1109/sp63933.2026.00178
• Specializing Language Models for Textual Fuzzing via Reinforcement Learning (cycle2, verified): https://doi.org/10.1109/sp63933.2026.00184
• Batch Me If You Can: Coverage-guided RPKI Fuzzing at Scale (cycle2, verified): https://doi.org/10.1109/sp63933.2026.00188
• PILOT: Command-line Interface Fuzzing via Path-Guided, Iterative Large Language Model Prompting (cycle2, verified): https://doi.org/10.1109/sp63933.2026.00211
• Web Application Vulnerability Repair via Context-Aware Fault Localization and Directed Differential Fuzzing (cycle2, verified): https://doi.org/10.1109/sp63933.2026.00237