Malicious code in browser-client-neptune (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector b9ad0cf7ca8faf91e654dc6ceb89ca235f191edc099334e5d8cf1a070bfb128a The package browser-client-neptune was found to contain malicious code. Source: ghsa-malware...

GAPS: Guiding Dynamic Android Analysis with Static Path Synthesis

Dynamically resolving method reachability in Android applications remains a critical and largely unsolved problem. Despite notable advancements in GUI testing and static call graph construction, current tools are insufficient for reliably driving execution toward specific target methods, especial...

Malicious code in accounts-base (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 07acaccf5cae78ad4bfd5f967e15c5ba68180c1350310492a9065ca97124bf26 The package accounts-base was found to contain malicious code. Source: ghsa-malware cf76e57ba69c401756a0d9279f66fcd197667ce73a011c643099737d08dc306c...

Malicious code in wartsila-application-json (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 8e0377e0cb41b793d9733d21ccf71ee44de194a8988cbbd874d88c3cb5e03cce The package wartsila-application-json was found to contain malicious code. Source: ghsa-malware...

lw-cnapp-microservices-iac

Project 2: Microservices with Infrastructure as Code ⚠️ WAR...

web-app-vulnerability-scanner

web-app-vulnerability-scanner A Python-based Web Application V...

Malicious code in br2s-ui-componentlibrary_r2 (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector be6786b979a9a6378e096381748fc3546c761e95cf2631585010ca066ad5ef19 The package br2s-ui-componentlibraryr2 was found to contain malicious code. Source: ghsa-malware...

MAL-2025-191475 Malicious code in atlassian-exp (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: kam193 802483ac3ec3749092037040a0a50ed9fa329232a832ac15fd5a0c692c42a9fd Installing the package or importing the module exfiltrates basic information about the host, and the package has no other purpose. --- Category: PROBABLYPENTES...

3 SOC Challenges You Need to Solve Before 2026

2026 will mark a pivotal shift in cybersecurity. Threat actors are moving from experimenting with AI to making it their primary weapon, using it to scale attacks, automate reconnaissance, and craft hyper-realistic social engineering campaigns. The Storm on the Horizon Global world instability,...

MAL-2025-191171 Malicious code in @accordproject/concerto-analysis (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector bd4dfaf2dbfd72597ed98e94903934d34e97ddd5dc4f7aeb7f5450767cb3a34c The package @accordproject/concerto-analysis was found to contain malicious code. Source: ghsa-malware...

EUVD-2025-199350

Malicious code in @accordproject/concerto-analysis npm...

Semantic Superiority Vs. Forensic Efficiency: A Comparative Analysis of Deep Learning and Psycholinguistics for Business Email Compromise Detection

Business Email Compromise BEC is a sophisticated social engineering threat that manipulates organizational hierarchies and exploits psychological vulnerabilities, leading to significant financial damage. According to the 2024 FBI Internet Crime Report, BEC accounts for over $2.9 billion in annual...

Quantum-Resistant Authentication Scheme for RFID Systems Using Lattice-Based Cryptography

We propose a novel quantum-resistant mutual authentication scheme for radio-frequency identification RFID systems. Our scheme uses lattice-based cryptography and, in particular, achieves quantum-resistance by leveraging the hardness of the inhomogeneous short integer solution ISIS problem. In...

A Reality Check on SBOM-Based Vulnerability Management: An Empirical Study and a Path Forward

The Software Bill of Materials SBOM is a critical tool for securing the software supply chain SSC, but its practical utility is undermined by inaccuracies in both its generation and its application in vulnerability scanning. This paper presents a large-scale empirical study on 2,414 open-source...

Improving the Identification of Real-World Malware's DNS Covert Channels Using Locality Sensitive Hashing

Nowadays, malware increasingly uses DNS-based covert channels in order to evade detection and maintain stealthy communication with its command-and-control servers. While prior work has focused on detecting such activity, identifying specific malware families and their behaviors from captured...

Mutillidae-SAST-Analysis

🛡️ Static Application Security Testing SAST: OWASP Mutillida...

injection-research

injection-research A study comparing injection vulnerabilities...

Amazon Is Using Specialized AI Agents for Deep Bug Hunting

Born out of an internal hackathon, Amazon’s Autonomous Threat Analysis system uses a variety of specialized AI agents to detect weaknesses and propose fixes to the company’s platforms...

MAL-2025-190626 Malicious code in vue3-transpiler (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 61eaca42a219c9b161768c7938d34f6bc4d6e169c5ae43e88acf7a8a70be537b The package vue3-transpiler was found to contain malicious code. Source: ossf-package-analysis...

LLM-CSEC: Empirical Evaluation of Security in C/C++ Code Generated by Large Language Models

The security of code generated by large language models LLMs is a significant concern, as studies indicate that such code often contains vulnerabilities and lacks essential defensive programming constructs. This work focuses on examining and evaluating the security of LLM-generated code,...