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Daniel Song

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2 published item(s)

preprint2026arXiv

Code World Model Preparedness Report

This report documents the preparedness assessment of Code World Model (CWM), a model for code generation and reasoning about code from Meta. We conducted pre-release testing across domains identified in our Frontier AI Framework as potentially presenting catastrophic risks, and also evaluated the model's misaligned propensities. Our assessment found that CWM does not pose additional frontier risks beyond those present in the current AI ecosystem. We therefore release it as an open-weight model.

preprint2015arXiv

Finding Tizen security bugs through whole-system static analysis

Tizen is a new Linux-based open source platform for consumer devices including smartphones, televisions, vehicles, and wearables. While Tizen provides kernel-level mandatory policy enforcement, it has a large collection of libraries, implemented in a mix of C and C++, which make their own security checks. In this research, we describe the design and engineering of a static analysis engine which drives a full information flow analysis for apps and a control flow analysis for the full library stack. We implemented these static analyses as extensions to LLVM, requiring us to improve LLVM's native analysis features to get greater precision and scalability, including knotty issues like the coexistence of C++ inheritance with C function pointer use. With our tools, we found several unexpected behaviors in the Tizen system, including paths through the system libraries that did not have inline security checks. We show how our tools can help the Tizen app store to verify important app properties as well as helping the Tizen development process avoid the accidental introduction of subtle vulnerabilities.