Semantic Preprocessing for LLM-Based Malware Analysis

In a context of malware analysis, numerous approaches rely on Artificial Intelligence to handle a large volume of data. However, these techniques focus on data view images, sequences and not on an expert's view. Noticing this issue, we propose a preprocessing that focuses on expert knowledge to...

SAVANT: Vulnerability Detection in Application Dependencies through Semantic-Guided Reachability Analysis

The integration of open-source third-party library dependencies in Java development introduces significant security risks when these libraries contain known vulnerabilities. Existing Software Composition Analysis SCA tools struggle to effectively detect vulnerable API usage from these libraries d...

Efficient Blockchain-Based Steganography Via Backcalculating Generative Adversarial Network

Blockchain-based steganography enables data hiding via encoding the covert data into a specific blockchain transaction field. However, previous works focus on the specific field-embedding methods while lacking a consideration on required field-generation embedding. In this paper, we propose a...

Symbolic Generation and Modular Embedding of High-Quality Abc-Triples

We present a symbolic identity for generating integer triples $a, b, c$ satisfying $a + b = c$, inspired by structural features of the \emphabc conjecture. The construction uses powers of $2$ and $3$ in combination with modular inversion in $\mathbbZ/3^p\mathbbZ$, leading to a parametric identity...

A Threat Intelligence Event Extraction Conceptual Model for Cyber Threat Intelligence Feeds

In response to the escalating cyber threats, the efficiency of Cyber Threat Intelligence CTI data collection has become paramount in ensuring robust cybersecurity. However, existing works encounter significant challenges in preprocessing large volumes of multilingual threat data, leading to...

MAL-2025-4441 Malicious code in ml-preprocessing (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 449fa18004b9f5016f86ea6f5c97358b4ca5263d4649325b946379ca51610f63 Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

Malicious code in ml-preprocessing (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 449fa18004b9f5016f86ea6f5c97358b4ca5263d4649325b946379ca51610f63 Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

Engineering Trustworthy Machine-Learning Operations with Zero-Knowledge Proofs

As Artificial Intelligence AI systems, particularly those based on machine learning ML, become integral to high-stakes applications, their probabilistic and opaque nature poses significant challenges to traditional verification and validation methods. These challenges are exacerbated in regulated...

Is Artificial Intelligence Generated Image Detection a Solved Problem?

The rapid advancement of generative models, such as GANs and Diffusion models, has enabled the creation of highly realistic synthetic images, raising serious concerns about misinformation, deepfakes, and copyright infringement. Although numerous Artificial Intelligence Generated Image AIGI...

Cryptanalysis of a Lattice-Based PIR Scheme for Arbitrary Database Sizes

Private Information Retrieval PIR schemes enable users to securely retrieve files from a server without disclosing the content of their queries, thereby preserving their privacy. In 2008, Melchor and Gaborit proposed a PIR scheme that achieves a balance between communication overhead and...

Advancing Email Spam Detection: Leveraging Zero-Shot Learning and Large Language Models

Email spam detection is a critical task in modern communication systems, essential for maintaining productivity, security, and user experience. Traditional machine learning and deep learning approaches, while effective in static settings, face significant limitations in adapting to evolving spam...

CVE-2025-46560 vLLM phi4mm: Quadratic Time Complexity in Input Token Processing​ leads to denial of service

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.8.0 and prior to 0.8.5 are affected by a critical performance vulnerability in the input preprocessing logic of the multimodal tokenizer. The code dynamically replaces placeholder tokens...

vLLM 安全漏洞

vLLM is a high throughput and memory efficient inference and service engine for LLM from the vLLM open source. A security vulnerability exists in vLLM versions prior to 0.8.0 through 0.8.5, which stems from inefficiencies in the input preprocessing logic that could lead to resource exhaustion...

GHSA-VC6M-HM49-G9QG vLLM: Quadratic Time Complexity in Input Token Processing​ leads to denial of service

Summary A critical performance vulnerability has been identified in the input preprocessing logic of the multimodal tokenizer. The code dynamically replaces placeholder tokens e.g., , with repeated tokens based on precomputed lengths. Due to ​​inefficient list concatenation operations​​, the...

Optimized Approaches to Malware Detection: a Study of Machine Learning and Deep Learning Techniques

Digital systems find it challenging to keep up with cybersecurity threats. The daily emergence of more than 560,000 new malware strains poses significant hazards to the digital ecosystem. The traditional malware detection methods fail to operate properly and yield high false positive rates with l...

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...

How to Enhance Downstream Adversarial Robustness (Almost) without Touching the Pre-Trained Foundation Model?

With the rise of powerful foundation models, a pre-training-fine-tuning paradigm becomes increasingly popular these days: A foundation model is pre-trained using a huge amount of data from various sources, and then the downstream users only need to fine-tune and adapt it to specific downstream...

Malicious code in kera-preprocessing (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: kam193 973d4eb03e9256234b20a9fd346a83f5ddced04587ffbf9a7b9762fbe15a1231 A campaign of probably pentest packages flooding PYPI. Installing the package or importing the module triggers reporting basic info like hostname, path and the...

MAL-2024-10648 Malicious code in kera-preprocessing (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: kam193 973d4eb03e9256234b20a9fd346a83f5ddced04587ffbf9a7b9762fbe15a1231 A campaign of probably pentest packages flooding PYPI. Installing the package or importing the module triggers reporting basic info like hostname, path and the...

AZL-33896 CVE-2023-51258 affecting package yasm for versions less than 1.3.0-16

A memory leak issue discovered in YASM v.1.3.0 allows a local attacker to cause a denial of service via the newToken function in the modules/preprocs/nasm/nasm-pp:1512...