[SECURITY] Fedora 42 Update: valkey-8.0.3-3.fc42

Valkey is an advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets. You can run atomic operations on these types, like appending to a string; incrementing the value in a hash; pushing to a list; computing s...

[SECURITY] Fedora 41 Update: valkey-8.0.3-3.fc41

Valkey is an advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets. You can run atomic operations on these types, like appending to a string; incrementing the value in a hash; pushing to a list; computing s...

TimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based Systems

Federated Learning has emerged as a privacy-oriented alternative to centralized Machine Learning, enabling collaborative model training without direct data sharing. While extensively studied for neural networks, the security and privacy implications of tree-based models remain underexplored. This...

From IOCs to Group Profiles: on the Specificity of Threat Group Behaviors in CTI Knowledge Bases

Indicators of Compromise IOCs such as IP addresses, file hashes, and domain names are commonly used for threat detection and attribution. However, IOCs tend to be short-lived as they are easy to change. As a result, the cybersecurity community is shifting focus towards more persistent behavioral...

TED-LaST: Towards Robust Backdoor Defense against Adaptive Attacks

Deep Neural Networks DNNs are vulnerable to backdoor attacks, where attackers implant hidden triggers during training to maliciously control model behavior. Topological Evolution Dynamics TED has recently emerged as a powerful tool for detecting backdoor attacks in DNNs. However, TED can be...

Assessing the Resilience of Automotive Intrusion Detection Systems to Adversarial Manipulation

The security of modern vehicles has become increasingly important, with the controller area network CAN bus serving as a critical communication backbone for various Electronic Control Units ECUs. The absence of robust security measures in CAN, coupled with the increasing connectivity of vehicles,...

LLMail-Inject: a Dataset from a Realistic Adaptive Prompt Injection Challenge

Indirect Prompt Injection attacks exploit the inherent limitation of Large Language Models LLMs to distinguish between instructions and data in their inputs. Despite numerous defense proposals, the systematic evaluation against adaptive adversaries remains limited, even when successful attacks ca...

AI-Based Software Vulnerability Detection: a Systematic Literature Review

Software vulnerabilities in source code pose serious cybersecurity risks, prompting a shift from traditional detection methods e.g., static analysis, rule-based matching to AI-driven approaches. This study presents a systematic review of software vulnerability detection SVD research from 2018 to...

Empirical Quantification of Spurious Correlations in Malware Detection

End-to-end deep learning exhibits unmatched performance for detecting malware, but such an achievement is reached by exploiting spurious correlations -- features with high relevance at inference time, but known to be useless through domain knowledge. While previous work highlighted that deep...

Mono: Is Your "Clean" Vulnerability Dataset Really Solvable? Exposing and Trapping Undecidable Patches and Beyond

The quantity and quality of vulnerability datasets are essential for developing deep learning solutions to vulnerability-related tasks. Due to the limited availability of vulnerabilities, a common approach to building such datasets is analyzing security patches in source code. However, existing...

ContextBuddy: AI-Enhanced Contextual Insights for Security Alert Investigation (Applied to Intrusion Detection)

Modern Security Operations Centres SOCs integrate diverse tools, such as SIEM, IDS, and XDR systems, offering rich contextual data, including alert enrichments, flow features, and similar case histories. Yet, analysts must still manually determine which of these contextual cues are most relevant...

LLMs Caught in the Crossfire: Malware Requests and Jailbreak Challenges

The widespread adoption of Large Language Models LLMs has heightened concerns about their security, particularly their vulnerability to jailbreak attacks that leverage crafted prompts to generate malicious outputs. While prior research has been conducted on general security capabilities of LLMs,...

Towards Generalized Source Tracing for Codec-Based Deepfake Speech

Recent attempts at source tracing for codec-based deepfake speech CodecFake, generated by neural audio codec-based speech generation CoSG models, have exhibited suboptimal performance. However, how to train source tracing models using simulated CoSG data while maintaining strong performance on re...

Profiling Electric Vehicles Via Early Charging Voltage Patterns

Electric Vehicles EVs are rapidly gaining adoption as a sustainable alternative to fuel-powered vehicles, making secure charging infrastructure essential. Despite traditional authentication protocols, recent results showed that attackers may steal energy through tailored relay attacks. One...

STAMP Your Content: Proving Dataset Membership Via Watermarked Rephrasings

Given how large parts of publicly available text are crawled to pretrain large language models LLMs, data creators increasingly worry about the inclusion of their proprietary data for model training without attribution or licensing. Their concerns are also shared by benchmark curators whose...

CVE-2025-4966

The WP Online Users Stats plugin for WordPress is vulnerable to Cross-Site Request Forgery in all versions up to, and including, 1.0.0. This is due to missing nonce validation within the hkdatasetresults function. This makes it possible for unauthenticated attackers to inject malicious web script...

Obfuscation-Resilient Binary Code Similarity Analysis Using Dominance Enhanced Semantic Graph

Binary code similarity analysis BCSA serves as a core technique for binary analysis tasks such as vulnerability detection. While current graph-based BCSA approaches capture substantial semantics and show strong performance, their performance suffers under code obfuscation due to the unstable...

Rethinking Machine Unlearning in Image Generation Models

With the surge and widespread application of image generation models, data privacy and content safety have become major concerns and attracted great attention from users, service providers, and policymakers. Machine unlearning MU is recognized as a cost-effective and promising means to address...

Incentivizing Collaborative Breach Detection

Decoy passwords, or "honeywords," alert a site to its breach if they are ever entered in a login attempt on that site. However, an attacker can identify a user-chosen password from among the decoys, without risk of alerting the site to its breach, by performing credential stuffing, i.e., entering...

Sentinel: SOTA Model to Protect against Prompt Injections

Large Language Models LLMs are increasingly powerful but remain vulnerable to prompt injection attacks, where malicious inputs cause the model to deviate from its intended instructions. This paper introduces Sentinel, a novel detection model, qualifire/prompt-injection-sentinel, based on the...