STALKER-Anomaly-modded-exes security vulnerabilities

STALKER-Anomaly-modded-exes is a patch developed by Dmitry Chernyavsky as an engine for computer games. Versions of STALKER-Anomaly-modded-exes before the date of 2025.12.30 contained security vulnerabilities. These vulnerabilities stemmed from the use of incompatible types to access resources,...

An Optimized Decision Tree-Based Framework for Explainable IoT Anomaly Detection

The increase in the number of Internet of Things IoT devices has tremendously increased the attack surface of cyber threats thus making a strong intrusion detection system IDS with a clear explanation of the process essential towards resource-constrained environments. Nevertheless, current IoT ID...

Hybrid IDS Using Signature-Based and Anomaly-Based Detection

Intrusion detection systems IDS are essential for protecting computer systems and networks against a wide range of cyber threats that continue to evolve over time. IDS are commonly categorized into two main types, each with its own strengths and limitations, such as difficulty in detecting...

Memory Poisoning Attack and Defense on Memory Based LLM-Agents

Large language model agents equipped with persistent memory are vulnerable to memory poisoning attacks, where adversaries inject malicious instructions through query only interactions that corrupt the agents long term memory and influence future responses. Recent work demonstrated that the MINJA...

CVE-2024-2244

REST service authentication anomaly with “valid username/no password” credential combination for batch job processing resulting in successful service invocation. The anomaly doesn’t exist with other credential combinations...

Comparative Evaluation of VAE, GAN, and SMOTE for Tor Detection in Encrypted Network Traffic

Encrypted network traffic poses significant challenges for intrusion detection due to the lack of payload visibility, limited labeled datasets, and high class imbalance between benign and malicious activities. Traditional data augmentation methods struggle to preserve the complex temporal and...

Improving Router Security Using BERT

Previous work on home router security has shown that using system calls to train a transformer-based language model built on a BERT-style encoder using contrastive learning is effective in detecting several types of malware, but the performance remains limited at low false positive rates. In this...

Engineering Attack Vectors and Detecting Anomalies in Additive Manufacturing

Additive manufacturing AM is rapidly integrating into critical sectors such as aerospace, automotive, and healthcare. However, this cyber-physical convergence introduces new attack surfaces, especially at the interface between computer-aided design CAD and machine execution layers. In this work, ...

Low Rank Comes with Low Security: Gradient Assembly Poisoning Attacks against Distributed LoRA-Based LLM Systems

Low-Rank Adaptation LoRA has become a popular solution for fine-tuning large language models LLMs in federated settings, dramatically reducing update costs by introducing trainable low-rank matrices. However, when integrated with frameworks like FedIT, LoRA introduces a critical vulnerability:...

Towards Eco Friendly Cybersecurity: Machine Learning Based Anomaly Detection with Carbon and Energy Metrics

The rising energy footprint of artificial intelligence has become a measurable component of US data center emissions, yet cybersecurity research seldom considers its environmental cost. This study introduces an eco aware anomaly detection framework that unifies machine learning based network...

In GnuPG through 2.4.8, if a signed message has \f at the end of a plaintext line, an adversary can construct a modified message that places additional text after the signed material, such that signature verification of the modified message succeeds (although an "invalid armor" message is printed during verification). This is related to use of \f as a marker to denote truncation of a long plaintext line.

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MAD-OOD: A Deep Learning Cluster-Driven Framework for an Out-Of-Distribution Malware Detection and Classification

Out of distribution OOD detection remains a critical challenge in malware classification due to the substantial intra family variability introduced by polymorphic and metamorphic malware variants. Most existing deep learning based malware detectors rely on closed world assumptions and fail to...

Amazon S3 Encryption Client 安全漏洞

Amazon S3 Encryption Client is a client-side encryption library open-sourced by Amazon Web Services. A security vulnerability exists in Amazon S3 Encryption Client that stems from a lack of encryption key promises, which could cause a user with write access to an S3 storage bucket to introduce a...

Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions

The increasing number of cyber threats and rapidly evolving tactics, as well as the high volume of data in recent years, have caused classical machine learning, rules, and signature-based defence strategies to fail, rendering them unable to keep up. An alternative, Quantum Machine Learning QML, h...

Cloud Security Leveraging AI: A Fusion-Based AISOC for Malware and Log Behaviour Detection

Cloud Security Operations Center SOC enable cloud governance, risk and compliance by providing insights visibility and control. Cloud SOC triages high-volume, heterogeneous telemetry from elastic, short-lived resources while staying within tight budgets. In this research, we implement an...

FiD-QAE: A Fidelity-Driven Quantum Autoencoder for Credit Card Fraud Detection

Credit card fraud detection is a critical task in financial security, as fraudulent transactions are rare, highly imbalanced, and often resemble legitimate ones. A wide range of classical machine learning methods, as well as more recent quantum machine learning approaches, have been investigated ...

Security Bulletin: Vulnerabilities in smarty and axios might affect IBM Storage Defender Sentinel Anomaly Scan Engine.

Summary IBM Storage Defender Sentinel Anomaly Scan Engine can be affected by vulnerabilities in smarty and axios. Vulnerabilities include allowing an attacker to inject malicious scripts into a Web page and steal cookie-based authentication credentials, execute arbitrary code on the system, and...

Quantum-Augmented AI/ML for O-RAN: Hierarchical Threat Detection with Synergistic Intelligence and Interpretability (Technical Report)

Open Radio Access Networks O-RAN enhance modularity and telemetry granularity but also widen the cybersecurity attack surface across disaggregated control, user and management planes. We propose a hierarchical defense framework with three coordinated layers-anomaly detection, intrusion...

CVE-2021-47728

Selea Targa IP OCR-ANPR Camera contains an unauthenticated command injection vulnerability in utils.php that allows remote attackers to execute arbitrary shell commands. Attackers can exploit the 'addr' and 'port' parameters to inject commands and gain www-data user access through chained local...

Web Technologies Security in the AI Era: A Survey of CDN-Enhanced Defenses

The modern web stack, which is dominated by browser-based applications and API-first backends, now operates under an adversarial equilibrium where automated, AI-assisted attacks evolve continuously. Content Delivery Networks CDNs and edge computing place programmable defenses closest to users and...