Debt behind the AI Boom: A Large-Scale Empirical Study of AI-Generated Code in the Wild

AI coding assistants are now widely used in software development. Software developers increasingly integrate AI-generated code into their codebases to improve productivity. Prior studies have shown that AI-generated code may contain code quality issues under controlled settings. However, we still...

Syntx security vulnerabilities

Syntx is an artificial intelligence-based data analysis and automated decision-making platform developed by Syntx Corporation. There is a security vulnerability in Syntx; this vulnerability stems from the command automatic approval module’s susceptibility to OS command injection, which may lead t...

Label-Efficient Training Updates for Malware Detection over Time

Machine Learning ML-based detectors are becoming essential to counter the proliferation of malware. However, common ML algorithms are not designed to cope with the dynamic nature of real-world settings, where both legitimate and malicious software evolve. This distribution drift causes models...

EUVD-2026-17042

Ghidra versions prior to 12.0.3 improperly process annotation directives embedded in automatically extracted binary data, resulting in arbitrary command execution when an analyst interacts with the UI. Specifically, the @execute annotation which is intended for trusted, user-authored comments is...

ANT-2026-H5T8XKWR · TryGhost/Ghost · sql-injection

sql-injection critical GHSA-w52v-v783-gw97 Severity Claude critical · Security research firm - · Maintainer critical Discovered by Claude Mythos Preview REPORT The report below was sent to the maintainer and sealed at approval. ANT-2026-H5T8XKWR: SQL injection in Content API The Ghost Content API...

CVE-2026-4946

Ghidra versions prior to 12.0.3 improperly process annotation directives embedded in automatically extracted binary data, resulting in arbitrary command execution when an analyst interacts with the UI. Specifically, the @execute annotation which is intended for trusted, user-authored comments is...

CVE-2026-4946 NSA Ghidra Auto-Analysis Annotation Command Execution

Ghidra versions prior to 12.0.3 improperly process annotation directives embedded in automatically extracted binary data, resulting in arbitrary command execution when an analyst interacts with the UI. Specifically, the @execute annotation which is intended for trusted, user-authored comments is...

CVE-2026-4946

Ghidra up to version 12.0.2 is affected by a flaw where annotation directives embedded in automatically extracted binary data (notably the @execute directive parsed from auto-analysis comments like CFStrings in Mach‑O) are executed when an analyst clicks benign-looking UI text. This yields arbitr...

CVE-2026-4946

Ghidra versions prior to 12.0.3 improperly process annotation directives embedded in automatically extracted binary data, resulting in arbitrary command execution when an analyst interacts with the UI. Specifically, the @execute annotation which is intended for trusted, user-authored comments is...

CVE-2026-4946 NSA Ghidra Auto-Analysis Annotation Command Execution

Ghidra versions prior to 12.0.3 improperly process annotation directives embedded in automatically extracted binary data, resulting in arbitrary command execution when an analyst interacts with the UI. Specifically, the @execute annotation which is intended for trusted, user-authored comments is...

CVE-2026-4946

Ghidra versions prior to 12.0.3 improperly process annotation directives embedded in automatically extracted binary data, resulting in arbitrary command execution when an analyst interacts with the UI. Specifically, the @execute annotation which is intended for trusted, user-authored comments is...

CVE-2026-4946 NSA Ghidra Auto-Analysis Annotation Command Execution

Ghidra versions prior to 12.0.3 improperly process annotation directives embedded in automatically extracted binary data, resulting in arbitrary command execution when an analyst interacts with the UI. Specifically, the @execute annotation which is intended for trusted, user-authored comments is...

Malicious code in f0-state-manager (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 989b5f62777b6b7fbd236eb28a54b0e42ba48548dc0a49919c5f311c1f1c7072 The package f0-state-manager was found to contain malicious code. Source: ossf-package-analysis...

Malicious code in dial-app-version (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 9efdd5b481d49a0d9ac535aedde75dbf5638bd85e7efe9c536d2938c57142799 The package dial-app-version was found to contain malicious code. Source: ossf-package-analysis...

MAL-2026-2284 Malicious code in bizsignupnodeweb (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector ceaf1cee13e367f987a97f8de4c8fb4985ab1eedd49be1912467793dce9f0ef9 The package bizsignupnodeweb was found to contain malicious code. Source: ossf-package-analysis...

CVE-2026-4946: Improper Neutralization of Special Elements used in an OS Command

Ghidra versions prior to 12.0.3 improperly process annotation directives embedded in automatically extracted binary data, resulting in arbitrary command execution when an analyst interacts with the UI. Specifically, the @execute annotation which is intended for trusted, user-authored comments is...

penclaw

🦀 PenClaw AI-powered penetration testing CLI. One command...

Quantum Bit Error Rate Analysis in BB84 Quantum Key Distribution: Measurement, Statistical Estimation, and Eavesdropping Detection

Quantum Key Distribution QKD provides information-theoretic security by exploiting the principles of quantum mechanics. Among QKD protocols, the BB84 scheme remains the most widely adopted for both theoretical research and practical implementation. A critical parameter determining the reliability...

Finding Memory Leaks in C/C++ Programs Via Neuro-Symbolic Augmented Static Analysis

Memory leaks remain prevalent in real-world C/C++ software. Static analyzers such as CodeQL provide scalable program analysis but frequently miss such bugs because they cannot recognize project-specific custom memory-management functions and lack path-sensitive control-flow modeling. We present...

Context-Aware Phishing Email Detection Using Machine Learning and NLP

Phishing attacks remain among the most prevalent cybersecurity threats, causing significant financial losses for individuals and organizations worldwide. This paper presents a machine learning-based phishing email detection system that analyzes email body content using natural language processing...