A Collaborative Intrusion Detection System Using Snort IDS Nodes

Intrusion Detection Systems IDSs are integral to safeguarding networks by detecting and responding to threats from malicious traffic or compromised devices. However, standalone IDS deployments often fall short when addressing the increasing complexity and scale of modern cyberattacks. This paper...

On the Price of Differential Privacy for Hierarchical Clustering

Hierarchical clustering is a fundamental unsupervised machine learning task with the aim of organizing data into a hierarchy of clusters. Many applications of hierarchical clustering involve sensitive user information, therefore motivating recent studies on differentially private hierarchical...

AESHA3: Efficient and Secure Sub-Key Generation for AES Using SHA-3

Advanced Encryption Standard AES is one of the most widely used symmetric cipher for the confidentiality of data. Also it is used for other security services, viz. integrity, authentication and key establishment. However, recently, authors have shown some weakness in the generation of sub-keys in...

FLARE: Feature-Based Lightweight Aggregation for Robust Evaluation of IoT Intrusion Detection

The proliferation of Internet of Things IoT devices has expanded the attack surface, necessitating efficient intrusion detection systems IDSs for network protection. This paper presents FLARE, a feature-based lightweight aggregation for robust evaluation of IoT intrusion detection to address the...

Multi-Stage Retrieval for Operational Technology Cybersecurity Compliance Using Large Language Models: a Railway Casestudy

Operational Technology Cybersecurity OTCS continues to be a dominant challenge for critical infrastructure such as railways. As these systems become increasingly vulnerable to malicious attacks due to digitalization, effective documentation and compliance processes are essential to protect these...

Everything You Wanted to Know about LLM-Based Vulnerability Detection but Were Afraid to Ask

Large Language Models are a promising tool for automated vulnerability detection, thanks to their success in code generation and repair. However, despite widespread adoption, a critical question remains: Are LLMs truly effective at detecting real-world vulnerabilities? Current evaluations, which...

Benchmarking Differentially Private Tabular Data Synthesis

Differentially private DP tabular data synthesis generates artificial data that preserves the statistical properties of private data while safeguarding individual privacy. The emergence of diverse algorithms in recent years has introduced challenges in practical applications, such as inconsistent...

PYSEC-2025-177

Pycel through 1.0b30, when operating on an untrusted spreadsheet, allows code execution via a crafted formula in a cell, such as one beginning with the =IFA1=200, eval"import'os'.system substring...

Attack-Defense Trees with Offensive and Defensive Attributes (With Appendix)

Effective risk management in cybersecurity requires a thorough understanding of the interplay between attacker capabilities and defense strategies. Attack-Defense Trees ADTs are a commonly used methodology for representing this interplay; however, previous work in this domain has only focused on...

Adversary-Augmented Simulation for Fairness Evaluation and Defense in Hyperledger Fabric

This paper presents an adversary model and a simulation framework specifically tailored for analyzing attacks on distributed systems composed of multiple distributed protocols, with a focus on assessing the security of blockchain networks. Our model classifies and constrains adversarial actions...

The Digital Cybersecurity Expert: How Far Have We Come?

The increasing deployment of large language models LLMs in the cybersecurity domain underscores the need for effective model selection and evaluation. However, traditional evaluation methods often overlook specific cybersecurity knowledge gaps that contribute to performance limitations. To addres...

Secure Transfer Learning: Training Clean Models against Backdoor in (Both) Pre-Trained Encoders and Downstream Datasets

Transfer learning from pre-trained encoders has become essential in modern machine learning, enabling efficient model adaptation across diverse tasks. However, this combination of pre-training and downstream adaptation creates an expanded attack surface, exposing models to sophisticated backdoor...

Firmware Version Change Detected (Low)

Changes in the controller firmware represent a major change in the behavior of the device and usually cause a temporary interruption of operations. An attacker could use firmware changes to add malicious code to the controller, causing it to perform harmful operations which are hard to detect. Th...

CVE-2025-32435

CVE-2025-32435 affects Hydra, a CI service for Nix-based projects. The issue arises from evaluating untrusted non-flake nix code, which could allow access to secrets owned by hydra user/group. The description notes that signing keys owned by hydra-queue-runner and hydra-www are not affected. Publ...

Delta Electronics COMMGR (Update A)

RISK EVALUATION Successful exploitation of this vulnerability could allow for an attacker to remotely access the AS3000Simulator family in the COMMGR software and execute arbitrary code. 2. RECOMMENDED PRACTICES CISA recommends users take defensive measures to minimize the risk of exploitation...

tomcat:ELEvaluationFuzzer: Security exception in org.apache.el.parser.AstLambdaExpression.setNestedState

Project: https://github.com/apache/tomcat.git Detailed Report: https://oss-fuzz.com/testcase?key=5768153378652160 Project: tomcat Fuzzing Engine: libFuzzer Fuzz Target: ELEvaluationFuzzer Job Type: libfuzzerasantomcat Platform Id: linux Crash Type: Security exception Crash Address: Crash State:...

Can LLMs Handle WebShell Detection? Overcoming Detection Challenges with Behavioral Function-Aware Framework

WebShell attacks, in which malicious scripts are injected into web servers, are a major cybersecurity threat. Traditional machine learning and deep learning methods are hampered by issues such as the need for extensive training data, catastrophic forgetting, and poor generalization. Recently, Lar...

Rockwell Automation Arena

RISK EVALUATION Successful exploitation of these vulnerabilities could disclose information to an attacker or allow execution of arbitrary code on the system. 2. RECOMMENDED PRACTICES CISA recommends users take defensive measures to minimize the risk of exploitation of these vulnerabilities...

CVE-2025-32461

wikipluginincludetpl in lib/wiki-plugins/wikipluginincludetpl.php in Tiki before 28.3 mishandles input to an eval. The fixed versions are 21.12, 24.8, 27.2, and 28.3...

Cross-site Scripting (XSS)

Vega is vulnerable to Cross-site Scripting XSS. The vulnerability is due to unsafe evaluation of JavaScript code due to the lack of an expression interpreter when processing Vega/Vega-lite JSON definitions...