MARD: A Multi-Agent Framework for Robust Android Malware Detection

With the rapid evolution of Android applications, traditional machine learning-based detection models suffer from concept drift. Additionally, they are constrained by shallow features, lacking deep semantic understanding and interpretability of decisions. Although Large Language Models LLMs...

MAL-2026-3104 Malicious code in robase-ui (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: kam193 9ca93a110c410fd6294e5270289bebb1872f9b81152d837f4990756881646cc0 During installation package downloads and runs a malicious executable. Likely continuation of 2026-03-rowrap. The campaign is built over a malicious Roblox API...

Malicious code in fetch-data-api-syncapi (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: kam193 dda63ba0d0dbd4ddf1d89523cacf89d51ffc9a25891e38cb49a9e424721fba9d The package contains code to download and start a malicious executable. It's masqueraded using name similar to Windows services. In analyzed versions, the code...

⚡ Weekly Recap: Fast16 Malware, XChat Launch, Federal Backdoor, AI Employee Tracking & More

Everything is dumb again. This week feels broken in a very familiar way. Old tricks are back. New tools are doing shady crap. Supply chains got hit. Fake help desks worked. Weird research showed how easy some attacks still are. Most of it feels like stuff we should have fixed years ago. Bad...

UNC6692 Hackers Exploit Microsoft Teams to Deploy SNOW Malware

UNC6692 hackers exploit Microsoft Teams with fake IT alerts to deploy SNOW malware, steal credentials, and breach corporate networks in advanced attacks...

A week in security (April 20 – April 26)

Last week on Malwarebytes Labs: Medical data of 500,000 UK volunteers listed for sale on Alibaba How cyberattacks on companies affect everyone Apple fixes iOS bug that kept deleted notifications, including chat previews Roblox clamps down on chats and age checks as legal pressure builds Malicious...

MAL-2026-3090 Malicious code in bytedecs (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: kam193 33034832d7823023eca4d7640030b040b26d4d5274e222bf294b7cf0be28430c Installing the package or importing the module exfiltrates basic information about the host, and the package has no other purpose. --- Category: PROBABLYPENTES...

info-security-portfolio

Information Security Portfolio A curated collection of nine e...

Malicious code in quicksolving (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: kam193 334524bfbf6438acc5016e76054740cdb532bdd9921695cbcc1852c568226708 During installation package downloads and runs a malicious executable. Likely continuation of 2026-03-rowrap. The campaign is built over a malicious Roblox API...

MAL-2026-3044 Malicious code in quicksolving (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: kam193 334524bfbf6438acc5016e76054740cdb532bdd9921695cbcc1852c568226708 During installation package downloads and runs a malicious executable. Likely continuation of 2026-03-rowrap. The campaign is built over a malicious Roblox API...

MAL-2026-3074 Malicious code in axis-abc-portal-menu (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 84dbd03fbc7970d1f3fc987743f698a9ea6a0af44ea2b89d0f2c1cbaa397f933 The package axis-abc-portal-menu was found to contain malicious code. Source: ossf-package-analysis...

Researchers Uncover Pre-Stuxnet ‘fast16’ Malware Targeting Engineering Software

Cybersecurity researchers have discovered a new Lua-based malware created years before the notorious Stuxnet worm that aimed to sabotage Iran's nuclear program by destroying uranium enrichment centrifuges. According to a new report published by SentinelOne, the previously undocumented cyber...

AsmRAG: LLM-Driven Malware Detection by Retrieving Functionally Similar Assembly Code

Deep learning malware detectors achieve high classification accuracy but suffer from severe interpretability limitations, typically returning probabilistic verdicts that lack forensic context. We introduce AsmRAG, a framework performing malware analysis through Assembly-Level Retrieval-Augmented...

TeamPCP Hijacks Bitwarden CLI, Uses Dependabot to Deploy Shai-Hulud Malware

GitGuardian uncovers TeamPCP attack on Bitwarden CLI, abusing GitHub Dependabot to spread Shai-Hulud and poison AI coding tools...

MAL-2026-3026 Malicious code in sagat-core (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 3b9e0a31b6bceddf90e920c8c6eb6313c822ca883c8daaa6905c5d8835fb8220 The package sagat-core was found to contain malicious code. Source: ghsa-malware cd038a03954f5c3c52c0f68ddfd36cbd9746f905131c22fa2089a72f8929be62 Any...

Malicious code in sagat-core (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 3b9e0a31b6bceddf90e920c8c6eb6313c822ca883c8daaa6905c5d8835fb8220 The package sagat-core was found to contain malicious code. Source: ghsa-malware cd038a03954f5c3c52c0f68ddfd36cbd9746f905131c22fa2089a72f8929be62 Any...

📄 MISP 2.5.27 Workflow Engine Cross Site Scripting

This Metasploit auxiliary module targets a potential stored cross site scripting vulnerability in the MISP Workflow Engine. It is designed to interact with the MISP API, create workflows, and inject malicious payloads into workflow data fields...

Adversarial Co-Evolution of Malware and Detection Models: A Bilevel Optimization Perspective

Machine learning-based malware detectors are increasingly vulnerable to adversarial examples. Traditional defenses, such as one-shot adversarial training, often fail against adaptive attackers who use reinforcement learning to bypass detection. This paper proposes a robust defense framework based...

Detecting Concept Drift in Evolving Malware Families Using Rule-Based Classifier Representations

This work proposes a structural approach to concept drift detection in malware classification using decision tree rulesets. Classifiers are trained across temporal windows on the EMBER2024 dataset, and drift is quantified by comparing extracted rule representations using feature importance,...

Self-Supervised Learning for Android Malware Detection on a Time-Stamped Dataset

Android malware detectors built with machine learning often suffer from temporal bias: models are trained and evaluated without respecting apps' actual release times, inflating accuracy and weakening real-world robustness. We address this by constructing a time-stamped dataset of benign and...