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PyFEX: Uncovering Evasive Python-based Threats via Resilient and Exhaustive Path Exploration
arXiv:2606.02196v1 Announce Type: new Abstract: The rapid expansion of the Python ecosystem has fueled two distinct but converging threats: adversaries increasingly target the software supply chain via the Python Package Index (PyPI), while also building evasive, cross-platform malicious binaries compiled from source code written in Python. Current program analysis techniques struggle to address this dual threat. Static analysis based tools are often blinded by runtime obfuscation and...
GitHub nukes 70+ Microsoft repos, breaks CI/CD pipelines, following suspected worm infections
Microsoft’s GitHub has disabled over 70 repositories after they were reportedly compromised by a worm in the latest open source supply chain attack. The code shack took down 73 repos within the space of 105 seconds after its alarms were tripped on Friday, June 5, after detecting signs of the Miasma worm infecting its projects, according to StepSecurity’s co-founder and CTO, Ashish Kurmi. Users reported issues quickly on Friday, after visits to those repos all resulted in the same message...
Is Python Becoming Pinyin?
I just got back from PyCon US. It was delightful; I saw old friends, met new ones, gave a tutorial on decorators, and spoke at the education summit. I’m a PyCon US sponsor, which means that I also had a booth, giving out T-shirts, books, stickers, and flyers about the LernerPython platform.
Running Python code in a sandbox with MicroPython and WASM
Running Python code in a sandbox with MicroPython and WASM 6th June 2026 I’ve been experimenting with different approaches to running code in a sandbox for several years now, but my latest attempt feels like it might finally have all of the characteristics I’ve been looking for. I’ve released it as an alpha package called micropython-wasm, and I’m using it for a code execution sandbox plugin for Datasette Agent called datasette-agent-micropython. - Why do I want a sandbox? -
MOLOT System Card: Malicious Operational Logic Observation Transformer
arXiv:2606.07792v1 Announce Type: new Abstract: MOLOT (Malicious Operational Logic Observation Transformer) is a static malicious-code detection system designed for SAST setup where package metadata, maintainer history, and dynamic execution traces may be unavailable or unreliable. The system represents source code as behavior sequences derived from static call graphs, includes an explanation stage that ranks suspicious behavior activities and maps them back to source-code locations.
A Fast Methane Detection Pipeline on Board Satellites Based on Mag1c-SAS and LinkNet
Announce Type: new Abstract: Methane is a potent greenhouse gas, and detecting leaks early via hyperspectral satellite imagery can help climate change mitigation efforts. Meanwhile, many existing hyperspectral missions only capture areas manually targeted by operators, thus missing potential events of interest.
Bundesrecht: An Open Library and Corpus for German Statutory Reference Processing
arXiv:2605.31338v1 Announce Type: new Abstract: Statutory references are central to legal language understanding, but are difficult to process automatically, as they appear in compact and variable surface forms, may combine multiple targets, use special abbreviations, and often point to lower-level units. Existing tools for German focus either on parsing references from legal documents or accessing statutory text once citations are explicit. This paper introduces bundesrecht, an open...
Devs know AI code is riddled with holes, but ship it anyway
Research by AppSec biz Checkmarx finds that 70 percent of developers believe AI-generated code has more vulnerabilities, and 30 percent knowingly ship vulnerable code into production. The report is based on responses from 2,350 global developers, CISOs, and AppSec managers, and follows similar annual surveys since 2023. The number of respondents is 54 percent higher this year than last, and the increased sample size may account for a somewhat surprising statistic: the reported proportion of...
TorchKM: A GPU-Oriented Library for Kernel Learning and Model Selection
Announce Type: new Abstract: TorchKM is an open-source library for kernel machines, including support vector machines, kernel logistic regression, and kernel quantile regression, with GPU acceleration. The library features a scikit-learn-style API and is designed to exploit GPU-friendly linear algebra, accelerating the full training and model-selection pipeline through intelligent reuse of matrix operations. Benchmarks show competitive predictive performance together with substantial...
Fast-Vollib: A Fast Implied Volatility Library for Pythonwith PyTorch, JAX, and CUDA Fused-Kernel Backends
arXiv:2604.27210v2 Announce Type: replace-cross Abstract: We present fast-vollib, an open-source Python library that provides high-performance European option pricing, implied volatility (IV) computation, and Greeks under the Black-76, Black-Scholes, and Black-Scholes-Merton models. The library is designed as a drop-in alternative to the de-facto-standard py_vollib and py_vollib_vectorized packages, with pluggable PyTorch and JAX execution backends, a CUDA fused-kernel Triton contribution...