Tootfinder

Synthesis of Sound and Precise Leakage Contracts for Open-Source RISC-V Processors
Zilong Wang, Gideon Mohr, Klaus von Gleissenthall, Jan Reineke, Marco Guarnieri
https://arxiv.org/abs/2509.06509

Synthesis of Sound and Precise Leakage Contracts for Open-Source RISC-V Processors
Leakage contracts have been proposed as a new security abstraction at the instruction set architecture level. Leakage contracts aim to capture the information that processors may leak via microarchitectural side channels. Recently, the first tools have emerged to verify whether a processor satisfies a given contract. However, coming up with a contract that is both sound and precise for a given processor is challenging, time-consuming, and error-prone, as it requires in-depth knowledge of the ti…

If you use Duplicati on your Linux server via Docker to perform backups to an external USB drive, this must be mounted before the container starts up. Otherwise, Duplicati will throw an error ("missing files") when it tries to perform the backup because it cannot verify the files on the external drive, even though it tells you that it can detect that external drive.
The quickest solution in this case is to restart the Duplicati container.

rStar2-Agent: Agentic Reasoning Technical Report
Ning Shang, Yifei Liu, Yi Zhu, Li Lyna Zhang, Weijiang Xu, Xinyu Guan, Buze Zhang, Bingcheng Dong, Xudong Zhou, Bowen Zhang, Ying Xin, Ziming Miao, Scarlett Li, Fan Yang, Mao Yang
https://arxiv.org/abs/2508.20722

rStar2-Agent: Agentic Reasoning Technical Report
We introduce rStar2-Agent, a 14B math reasoning model trained with agentic reinforcement learning to achieve frontier-level performance. Beyond current long CoT, the model demonstrates advanced cognitive behaviors, such as thinking carefully before using Python coding tools and reflecting on code execution feedback to autonomously explore, verify, and refine intermediate steps in complex problem-solving. This capability is enabled through three key innovations that makes agentic RL effective at…

SIExVulTS: Sensitive Information Exposure Vulnerability Detection System using Transformer Models and Static Analysis
Kyler Katz, Sara Moshtari, Ibrahim Mujhid, Mehdi Mirakhorli, Derek Garcia
https://arxiv.org/abs/2508.19472

SIExVulTS: Sensitive Information Exposure Vulnerability Detection System using Transformer Models and Static Analysis
Sensitive Information Exposure (SIEx) vulnerabilities (CWE-200) remain a persistent and under-addressed threat across software systems, often leading to serious security breaches. Existing detection tools rarely target the diverse subcategories of CWE-200 or provide context-aware analysis of code-level data flows. Aims: This paper aims to present SIExVulTS, a novel vulnerability detection system that integrates transformer-based models with static analysis to identify and verify sensitive inf…