Exploiting CPython's Just-In-Time Optimization: StencilLeak Attack

Python 3.13/3.14 introduces a new copy-and-patch JIT that reuses stencil templates. Despite its performance benefits, we find that it enlarges the Python attack surface. Specifically,we perform a systematic security analysis of this stencil-based architecture and uncover a new class of attack vectors, which we term StencilLeak. Unlike prior JIT exploits that rely on attacker-injected data or dynamic recompilation, StencilLeak exploits the inherent determinism of legitimate stencil templates. In a standard Python environment with active defenses (ASLR, AppArmor) enabled, we show that our pure Python code with user privilege can successfully execute arbitrary binary code on x86_64. Across 500 attack attempts, the StencilLeak attack succeeds in 50.2% of single attempts, reaches 99.2% within 7 attempts, and completes as fast as 4.6 seconds. These results demonstrate that although CPython’s JIT is now an experimental feature, the structural predictability of copy-and-patch architectures warrants rigorous security evaluation.