1641 matches found
CISO's Expert Guide To AI Supply Chain Attacks
AI-enabled supply chain attacks jumped 156% last year. Discover why traditional defenses are failing and what CISOs must do now to protect their organizations. Download the full CISO’s expert guide to AI Supply chain attacks here. TL;DR AI-enabled supply chain attacks are exploding in scale and...
MAL-2025-106103 Malicious code in nadia-menjes16-ruro (npm)
--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector c3d5627915c8b4f7054460fcf8fa95c7e5786ec790180c1e0b31c52d23c21f8b This package appears to be part of the tea.xyz token reward campaign that flooded npm. These packages typically contain autopublish scripts auto.js,...
CYPRESS: Transferring Secrets in the Shadow of Visible Packets
Network steganography and covert communication channels have been studied extensively in the past. However, prior works offer minimal practical use for their proposed techniques and are limited to specific use cases and network protocols. In this paper, we show that covert channels in networking...
Google Uncovers PROMPTFLUX Malware That Uses Gemini AI to Rewrite Its Code Hourly
Google on Wednesday said it discovered an unknown threat actor using an experimental Visual Basic Script VB Script malware dubbed PROMPTFLUX that interacts with its Gemini artificial intelligence AI model API to write its own source code for improved obfuscation and evasion. "PROMPTFLUX is writte...
Malicious VSX Extension "SleepyDuck" Uses Ethereum to Keep Its Command Server Alive
Cybersecurity researchers have flagged a new malicious extension in the Open VSX registry that harbors a remote access trojan called SleepyDuck. According to Secure Annex's John Tuckner, the extension in question, juan-bianco.solidity-vlang version 0.0.7, was first published on October 31, 2025, ...
The Evolution of SOC Operations: How Continuous Exposure Management Transforms Security Operations
Security Operations Centers SOC today are overwhelmed. Analysts handle thousands of alerts every day, spending much time chasing false positives and adjusting detection rules reactively. SOCs often lack the environmental context and relevant threat intelligence needed to quickly verify which aler...
PhantomRaven Malware Found in 126 npm Packages Stealing GitHub Tokens From Devs
Cybersecurity researchers have uncovered yet another active software supply chain attack campaign targeting the npm registry with over 100 malicious packages that can steal authentication tokens, CI/CD secrets, and GitHub credentials from developers' machines. The campaign has been codenamed...
RedTiger Malware Steals Data, Discord Tokens and Even Webcam Images
A new Python-based infostealer called RedTiger is targeting Discord gamers to steal authentication tokens, passwords, and payment information. Learn how the malware works, its evasion tactics, and essential security steps like enabling MFA...
PT-2025-44224
Name of the Vulnerable Software and Affected Versions Supermicro BMC firmware on Supermicro MBD-X12STW-F affected versions not specified Description An issue exists in the firmware validation logic of Supermicro BMC firmware. An attacker can potentially update the system firmware using a speciall...
PT-2025-44225
Name of the Vulnerable Software and Affected Versions Supermicro BMC firmware versions affected versions not specified Description The Supermicro BMC firmware contains a flaw in its validation logic. An attacker can exploit this to update the system firmware with a specially crafted image...
Canada Fines Cybercrime Friendly Cryptomus $176M
Financial regulators in Canada this week levied $176 million in fines against Cryptomus , a digital payments platform that supports dozens of Russian cryptocurrency exchanges and websites hawking cybercrime services. The penalties for violating Canada's anti money-laundering laws come ten months...
Exploit for Out-of-bounds Write in Mediatek Software_Development_Kit
What is Registry Exploit? Phantom-Registry-Exploit-Cve2025-20...
The evolving landscape of email phishing attacks: how threat actors are reusing and refining established techniques
Introduction Cyberthreats are constantly evolving, and email phishing is no exception. Threat actors keep coming up with new methods to bypass security filters and circumvent user vigilance. At the same time, established – and even long-forgotten – tactics have not gone anywhere; in fact, some ar...
CVE-2025-61303
Hatching Triage Sandbox Windows 10 build 2004 2025-08-14 and Windows 10 LTSC 20212025-08-14 contains a vulnerability in its Windows behavioral analysis engine that allows a submitted malware sample to evade detection and cause denial-of-analysis. The vulnerability is triggered when a sample...
CVE-2025-61303
Hatching Triage Sandbox Windows 10 build 2004 2025-08-14 and Windows 10 LTSC 20212025-08-14 contains a vulnerability in its Windows behavioral analysis engine that allows a submitted malware sample to evade detection and cause denial-of-analysis. The vulnerability is triggered when a sample...
CVE-2025-61303
Hatching Triage Sandbox Windows 10 build 2004 2025-08-14 and Windows 10 LTSC 20212025-08-14 contains a vulnerability in its Windows behavioral analysis engine that allows a submitted malware sample to evade detection and cause denial-of-analysis. The vulnerability is triggered when a sample...
Hexstrike-redteam
HexStrike AI RED-TEAM AI-Powered MCP Cybersecurity Automat...
A Hard-Label Black-Box Evasion Attack against ML-Based Malicious Traffic Detection Systems
Machine Learning ML-based malicious traffic detection is a promising security paradigm. It outperforms rule-based traditional detection by identifying various advanced attacks. However, the robustness of these ML models is largely unexplored, thereby allowing attackers to craft adversarial traffi...
DeepTrust: Multi-Step Classification through Dissimilar Adversarial Representations for Robust Android Malware Detection
Over the last decade, machine learning has been extensively applied to identify malicious Android applications. However, such approaches remain vulnerable against adversarial examples, i.e., examples that are subtly manipulated to fool a machine learning model into making incorrect predictions...
