Tootfinder

The US holiday is a memory now, so time to check out today's Metacurity to get briefed on the most critical infosec developments you should know, including
--Italian cops arrest FBI-wanted Chinese hacker who tried to steal COVID-19 vaccine
--Brazilian cops bust IT worker connected to $100m banking systems hack,
--Call of Duty: WWII yanked offline after RCE rumors,
--OpenAI beefs up corporate spying protections,
--DragonForce battles RansomHub,
--Cambod…

Italian cops arrest FBI-wanted Chinese hacker who tried to steal the COVID-19 vaccine
Brazilian cops bust IT worker connected to $100m banking systems hack, Call of Duty: WWII yanked offline after RCE rumors, OpenAI beefs up corporate spying protections, DragonForce battles RansomHub, Cambodia accuses Thai hackers of attacks, Trump's tax bill contains cyber money, much more

Strong Rupert Holmes vibes here.
I love that Holmes couldn’t find a word that fit into his metre when he wrote Escape, so he inserted “pina colada”—he’d never had one, but thought it sounded exotic—only to taste one years later, shrug, and not think it particularly exciting.
https://comics.town/@roon…

Roonie the Rabbit (@rooniecomics@comics.town)
Attached: 1 image

Longer Lists Yield Better Matchings
Yuri Faenza, Aapeli Vuorinen
https://arxiv.org/abs/2506.06217 https://arxiv.org/pdf/2506.06217

Longer Lists Yield Better Matchings
Many centralized mechanisms for two-sided matching markets that enjoy strong theoretical properties assume that the planner solicits full information on the preferences of each participating agent. In particular, they expect that participants compile and communicate their complete preference lists over agents from the other side of the market. However, real-world markets are often very large and agents cannot always be expected to even produce a ranking of all options on the other side. It is t…

Single Block On
Paritosh Ranjan, Surajit Majumder, Prodip Roy
https://arxiv.org/abs/2507.06236 https://arxiv.org/pdf/2507.06236

Single Block On
In the digital age, individuals increasingly maintain active presences across multiple platforms ranging from social media and messaging applications to professional and communication tools. However, the current model for managing user level privacy and abuse is siloed, requiring users to block undesirable contacts independently on each platform. This paper introduces Single Block On (SBO) a unified and interoperable system enabling users to block an individual once and have that block propagat…

RADAR: Recall Augmentation through Deferred Asynchronous Retrieval
Amit Jaspal, Qian Dang, Ajantha Ramineni
https://arxiv.org/abs/2506.07261 https://

RADAR: Recall Augmentation through Deferred Asynchronous Retrieval
Modern large-scale recommender systems employ multi-stage ranking funnel (Retrieval, Pre-ranking, Ranking) to balance engagement and computational constraints (latency, CPU). However, the initial retrieval stage, often relying on efficient but less precise methods like K-Nearest Neighbors (KNN), struggles to effectively surface the most engaging items from billion-scale catalogs, particularly distinguishing highly relevant and engaging candidates from merely relevant ones. We introduce Recall A…

Prediction-Augmented Mechanism Design for Weighted Facility Location
Yangguang Shi, Zhenyu Xue
https://arxiv.org/abs/2507.06509 https://

Prediction-Augmented Mechanism Design for Weighted Facility Location
Facility location is fundamental in operations research, mechanism design, and algorithmic game theory, with applications ranging from urban infrastructure planning to distributed systems. Recent research in this area has focused on augmenting classic strategyproof mechanisms with predictions to achieve an improved performance guarantee against the uncertainty under the strategic environment. Previous work has been devoted to address the trade-off obstacle of balancing the consistency (near-opt…

CRED: Counterfactual Reasoning and Environment Design for Active Preference Learning
Yi-Shiuan Tung, Bradley Hayes, Alessandro Roncone
https://arxiv.org/abs/2507.05458

CRED: Counterfactual Reasoning and Environment Design for Active Preference Learning
For effective real-world deployment, robots should adapt to human preferences, such as balancing distance, time, and safety in delivery routing. Active preference learning (APL) learns human reward functions by presenting trajectories for ranking. However, existing methods often struggle to explore the full trajectory space and fail to identify informative queries, particularly in long-horizon tasks. We propose CRED, a trajectory generation method for APL that improves reward estimation by join…

MBFormer: A General Transformer-based Learning Paradigm for Many-body Interactions in Real Materials
Bowen Hou, Xian Xu, Jinyuan Wu, Diana Y. Qiu
https://arxiv.org/abs/2507.05480 …

MBFormer: A General Transformer-based Learning Paradigm for Many-body Interactions in Real Materials
Recently, radical progress in machine learning (ML) has revolutionized computational materials science, enabling unprecedentedly rapid materials discovery and property prediction, but the quantum many-body problem -- which is the key to understanding excited-state properties, ranging from transport to optics -- remains challenging due to the complexity of the nonlocal and energy-dependent interactions. Here, we propose a symmetry-aware, grid-free, transformer-based model, MBFormer, that is desi…

Diesem Kumpel bin ich auf einem Waldweg begegnet. Kann jemand die Art bestimmen? 🤔
Übrigens, #Wanderroutentipps in diesem Bundesland mit GPX-Track findet Ihr über https://www.oekologisch-unterwegs.…

This is kind of crazy
One in Three Australian Ransomware Victims Hit Multiple Times
https://australiancybersecuritymagazine.com.au/one-in-three-australian-ransomware-victims-hit-multiple-times/

One in Three Australian Ransomware Victims Hit Multiple Times - Australian Cyber Security Magazine
Barracuda Networks, Inc. has released new research showing one in three Australian organisations affected by ransomware have been hit multiple times in the last 12 months. The findings are detailed in the Ransomware Insights Report 2025, which also reveals the situation in Australia is particularly concerning, with 67% of repeat victims saying they are juggling