111 matches found
EUVD-2021-31502
Malicious code in bioql PyPI...
NVIDIA Megatron-LM msdp preprocessing script code injection vulnerability
NVIDIA Megatron-LM is a PyTorch-based distributed training framework from NVIDIA that specializes in training large Transformer language models. A code injection vulnerability exists in the NVIDIA Megatron-LM msdp preprocessing script, which can be exploited by attackers to cause code execution,...
CVE-2025-23353
NVIDIA Megatron-LM for all platforms contains a vulnerability in the msdp preprocessing script where malicious data created by an attacker may cause an injection. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, Information disclosure, and data...
CVE-2025-23353
NVIDIA Megatron-LM for all platforms contains a vulnerability in the msdp preprocessing script where malicious data created by an attacker may cause an injection. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, Information disclosure, and data...
Arbitrary Code Injection
Overview megatron-core is a Megatron Core - a library for efficient and scalable training of transformer based models Affected versions of this package are vulnerable to Arbitrary Code Injection via the msdp\preprocessing script. An attacker can execute arbitrary code and escalate privileges...
CVE-2025-23353
NVIDIA Megatron-LM for all platforms contains a vulnerability in the msdp preprocessing script where malicious data created by an attacker may cause an injection. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, Information disclosure, and data...
CVE-2025-23353
NVIDIA Megatron-LM for all platforms contains a vulnerability in the msdp preprocessing script where malicious data created by an attacker may cause an injection. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, Information disclosure, and data...
CVE-2025-23353
CVE-2025-23353 affects NVIDIA Megatron-LM across platforms due to a vulnerability in the msdp preprocessing script. The issue enables code injection that can lead to code execution, privilege escalation, information disclosure, and data tampering. Public details identify the affected component as...
[SECURITY] Fedora 42 Update: tcpreplay-4.5.2-1.fc42
Tcpreplay is a tool to replay captured network traffic. Currently, tcpreplay supports pcap tcpdump and snoop capture formats. Also included, is tcpprep a tool to pre-process capture files to allow increased performance under certain conditions as well as capinfo which provides basic information...
Developing a Transferable Federated Network Intrusion Detection System
Intrusion Detection Systems IDS are a vital part of a network-connected device. In this paper, we develop a deep learning based intrusion detection system that is deployed in a distributed setup across devices connected to a network. Our aim is to better equip deep learning models against unknown...
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...
SecONNds: Secure Outsourced Neural Network Inference on ImageNet
The widespread adoption of outsourced neural network inference presents significant privacy challenges, as sensitive user data is processed on untrusted remote servers. Secure inference offers a privacy-preserving solution, but existing frameworks suffer from high computational overhead and...
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...
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...
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...
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...