Tootfinder

Zensec has a good article on the Akira ransomware group's tactics taken directly from their DFIR experience on 16 incidents. A few key take-aways:
- Initial Access: Please, please please patch your Internet-facing VPN and firewall devices including your Sonicwall, Cisco ASA and Watchguard devices.
- Patch our Veeam software. They used vulnerable Veeam installs to perform privilege escalation
- Block access to Anydesk.com and remotedesktop.google.com if you don't use…

Unmasking Akira: The ransomware tactics you can’t afford to ignore - Zensec
If you are reading this because you have experienced a ransomware incident and are unsure how to deal with it, contact Zensec immediately.

Graph Neural Diffusion via Generalized Opinion Dynamics
Asela Hevapathige, Asiri Wijesinghe, Ahad N. Zehmakan
https://arxiv.org/abs/2508.11249 https://arxi…

Graph Neural Diffusion via Generalized Opinion Dynamics
There has been a growing interest in developing diffusion-based Graph Neural Networks (GNNs), building on the connections between message passing mechanisms in GNNs and physical diffusion processes. However, existing methods suffer from three critical limitations: (1) they rely on homogeneous diffusion with static dynamics, limiting adaptability to diverse graph structures; (2) their depth is constrained by computational overhead and diminishing interpretability; and (3) theoretical understandi…

Verifying Graph Neural Networks with Readout is Intractable
Artem Chernobrovkin, Marco S\"alzer, Fran\c{c}ois Schwarzentruber, Nicolas Troquard
https://arxiv.org/abs/2510.08045

Verifying Graph Neural Networks with Readout is Intractable
We introduce a logical language for reasoning about quantized aggregate-combine graph neural networks with global readout (ACR-GNNs). We provide a logical characterization and use it to prove that verification tasks for quantized GNNs with readout are (co)NEXPTIME-complete. This result implies that the verification of quantized GNNs is computationally intractable, prompting substantial research efforts toward ensuring the safety of GNN-based systems. We also experimentally demonstrate that quan…

Configuration spaces and peak representations
Marcelo Aguiar, Sarah Brauner, Victor Reiner
https://arxiv.org/abs/2508.09898 https://arxiv.org/pdf/2508.0989…

Configuration spaces and peak representations
Within the group algebras of the symmetric and hyperoctahedral groups, one has their descent algebras and families of Eulerian idempotents. These idempotents are known to generate group representations with topological interpretations, as the cohomology of configuration spaces of types A and B. We provide an analogous cohomological interpretation for the representations generated by idempotents in the peak algebra, called the peak representations. We describe the peak representations as sums of…

A set of master variables for the two-star random graph
Pawat Akara-pipattana, Oleg Evnin
https://arxiv.org/abs/2509.07423 https://arxiv.org/pdf/2509.07423…

A set of master variables for the two-star random graph
The two-star random graph is the simplest exponential random graph model with nontrivial interactions between the graph edges. We propose a set of auxiliary variables that control the thermodynamic limit where the number of vertices N tends to infinity. Such 'master variables' are usually highly desirable in treatments of 'large N' statistical field theory problems. For the dense regime when a finite fraction of all possible edges are filled, this construction recovers the mean field solution o…

Attention over Scene Graphs: Indoor Scene Representations Toward CSAI Classification
Artur Barros, Carlos Caetano, Jo\~ao Macedo, Jefersson A. dos Santos, Sandra Avila
https://arxiv.org/abs/2509.26457 …

Attention over Scene Graphs: Indoor Scene Representations Toward CSAI Classification
Indoor scene classification is a critical task in computer vision, with wide-ranging applications that go from robotics to sensitive content analysis, such as child sexual abuse imagery (CSAI) classification. The problem is particularly challenging due to the intricate relationships between objects and complex spatial layouts. In this work, we propose the Attention over Scene Graphs for Sensitive Content Analysis (ASGRA), a novel framework that operates on structured graph representations inste…

Interplay of sync and swarm: Theory and application of swarmalators
Gourab Kumar Sar, Kevin O'Keeffe, Joao U. F. Lizarraga, Marcus A. M. de Aguiar, Christian Bettstetter, Dibakar Ghosh
https://arxiv.org/abs/2510.09819

Interplay of sync and swarm: Theory and application of swarmalators
Swarmalators, entities that combine the properties of swarming particles with synchronized oscillations, represent a novel and growing area of research in the study of collective behavior. This review provides a comprehensive overview of the current state of swarmalator research, focusing on the interplay between spatial organization and temporal synchronization. After a brief introduction to synchronization and swarming as separate phenomena, we discuss the various mathematical models that hav…

Reinforcement Learning for Clinical Reasoning: Aligning LLMs with ACR Imaging Appropriateness Criteria
Anni Tziakouri, Filippo Menolascina
https://arxiv.org/abs/2510.05194 https…

Reinforcement Learning for Clinical Reasoning: Aligning LLMs with ACR Imaging Appropriateness Criteria
Medical imaging has revolutionized diagnosis, yet unnecessary procedures are rising, exposing patients to radiation and stress, limiting equitable access, and straining healthcare systems. The American College of Radiology Appropriateness Criteria, developed through extensive multidisciplinary review, provide evidence-based guidance but remain underutilized. Leveraging advances in LLM reasoning, we introduce a Reasoning Agent trained with Reinforcement Learning (RL), specifically Group Relative…

Fault Tolerant Zero Forcing
Asher Brown, Mark Hunnell, Za'Kiyah Toomer-Sanders, Sarah Weber
https://arxiv.org/abs/2509.07854 https://arxiv.org/pdf/2509…

Fault Tolerant Zero Forcing
Zero forcing is an iterative graph coloring process studied for its wide array of applications. In this process the vertices of the graph are initially designated as filled or unfilled, and a zero forcing set is a set of initially filled vertices that results in all vertices filled after repeated application of a color change rule. The zero forcing number of a graph is the minimum cardinality of a zero forcing set. The zero forcing number has motivated the introduction of a host of variants def…

Explaining Fine Tuned LLMs via Counterfactuals A Knowledge Graph Driven Framework
Yucheng Wang, Ziyang Chen, Md Faisal Kabir
https://arxiv.org/abs/2509.21241 https://

Explaining Fine Tuned LLMs via Counterfactuals A Knowledge Graph Driven Framework
The widespread adoption of Low-Rank Adaptation (LoRA) has enabled large language models (LLMs) to acquire domain-specific knowledge with remarkable efficiency. However, understanding how such a fine-tuning mechanism alters a model's structural reasoning and semantic behavior remains an open challenge. This work introduces a novel framework that explains fine-tuned LLMs via counterfactuals grounded in knowledge graphs. Specifically, we construct BioToolKG, a domain-specific heterogeneous knowled…