45 matches found
CVE-2025-69048
creationtimestamp| type| source ---|---|--- 2026-01-27 17:25:57+00:00| seen| Telegram/zQovba3jq34R8mOIwo4UQbXIwilVvhjiGRRMMjnKXHFewE...
JLSEC-2025-174 An issue was discovered in GNU gettext 0.19.8
An issue was discovered in GNU gettext 0.19.8. There is a double free in defaultaddmessage in read-catalog.c, related to an invalid free in pogramparse in po-gram-gen.y, as demonstrated by lt-msgfmt...
NewStart CGSL MAIN 6.06 : gettext Vulnerability (NS-SA-2025-0218)
The remote NewStart CGSL host, running version MAIN 6.06, has gettext packages installed that are affected by a vulnerability: - An issue was discovered in GNU gettext 0.19.8. There is a double free in defaultaddmessage in read- catalog.c, related to an invalid free in pogramparse in po-gram-gen....
MAL-2025-47061 Malicious code in gram-utilz (npm)
The package gram-utilz was found to contain malicious code. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware f7c772fd2d6b9f919249def32fb96f26a08cf5bf3ebf008ab12736e774021864 Any computer that has this package installed or running should be considered fully compromise...
Malicious Package
Overview gram-utilz is a malicious package. This package contains malicious code, and its content was removed from the official package manager. While this package might be attempting to impersonate a valid organization, there is no connection between that organization and this package authorship...
Malicious code in gram-utilz (npm)
The package gram-utilz was found to contain malicious code. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware f7c772fd2d6b9f919249def32fb96f26a08cf5bf3ebf008ab12736e774021864 Any computer that has this package installed or running should be considered fully compromise...
FedGraM: Defending against Untargeted Attacks in Federated Learning Via Embedding Gram Matrix
Federated Learning FL enables geographically distributed clients to collaboratively train machine learning models by sharing only their local models, ensuring data privacy. However, FL is vulnerable to untargeted attacks that aim to degrade the global model's performance on the underlying data...
MalVis: a Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification
As technology advances, Android malware continues to pose significant threats to devices and sensitive data. The open-source nature of the Android OS and the availability of its SDK contribute to this rapid growth. Traditional malware detection techniques, such as signature-based, static, and...
Residual-Evasive Attacks on ADMM in Distributed Optimization
This paper presents two attack strategies designed to evade detection in ADMM-based systems by preventing significant changes to the residual during the attacked iteration. While many detection algorithms focus on identifying false data injection through residual changes, we show that our attacks...
Scalable APT Malware Classification Via Parallel Feature Extraction and GPU-Accelerated Learning
This paper presents an underlying framework for both automating and accelerating malware classification, more specifically, mapping malicious executables to known Advanced Persistent Threat APT groups. The main feature of this analysis is the assembly-level instructions present in executables whi...
Malicious Code Detection in Smart Contracts Via Opcode Vectorization
With the booming development of blockchain technology, smart contracts have been widely used in finance, supply chain, Internet of things and other fields in recent years. However, the security problems of smart contracts become increasingly prominent. Security events caused by smart contracts...
OpCode-Based Malware Classification Using Machine Learning and Deep Learning Techniques
This technical report presents a comprehensive analysis of malware classification using OpCode sequences. Two distinct approaches are evaluated: traditional machine learning using n-gram analysis with Support Vector Machine SVM, K-Nearest Neighbors KNN, and Decision Tree classifiers; and a deep...
[SECURITY] Fedora 40 Update: jglobus-2.1.0-35.fc40
jglobus is a collection of Java client libraries for Globus Toolkit security, GRAM, GridFTP and MyProxy...
CVE-2023-48848
creationtimestamp| type| source ---|---|--- 2023-12-20 08:01:58+00:00| seen| https://t.me/ctinow/156791...
ALSA-2023:4570 Important: iperf3 security update
Iperf is a tool which can measure maximum TCP bandwidth and tune various parameters and UDP characteristics. Iperf reports bandwidth, delay jitter, and data-gram loss. Security Fixes: iperf3: memory allocation hazard and crash CVE-2023-38403 For more details about the security issues, including t...
SUSE CVE-2018-18751
An issue was discovered in GNU gettext 0.19.8. There is a double free in defaultaddmessage in read-catalog.c, related to an invalid free in pogramparse in po-gram-gen.y, as demonstrated by lt-msgfmt...
OESA-2022-1767 bison security update
Bison is a general-purpose parser generator that converts an annotated context-free grammar into a deterministic LR or generalized LR GLR parser employing LALR1 parser tables. As an experimental feature, Bison can also generate IELR1 or canonical LR1 parser tables. Once you are proficient with...
ALPINE-CVE-2020-24240
GNU Bison before 3.7.1 has a use-after-free in obstackfree in lib/obstack.c called from gramlex when a '\0' byte is encountered. NOTE: there is a risk only if Bison is used with untrusted input, and the observed bug happens to cause unsafe behavior with a specific compiler/architecture. The bug...
gettext: double free in default_add_message in read-catalog.c
An issue was discovered in GNU gettext 0.19.8. There is a double free in defaultaddmessage in read-catalog.c, related to an invalid free in pogramparse in po-gram-gen.y, as demonstrated by lt-msgfmt...
gettext: double free in default_add_message in read-catalog.c
An issue was discovered in GNU gettext 0.19.8. There is a double free in defaultaddmessage in read-catalog.c, related to an invalid free in pogramparse in po-gram-gen.y, as demonstrated by lt-msgfmt...