quantum-security-project

OWASP Quantum Security Project 今日准备，守护明日。 OWASP 官方社区项目，以务实、供应商中立且基于风险的方式梳理量子时代的安全风险——对抗炒作与恐慌的解毒剂。 状态： 引导阶段（Bootstrap phase）。OWASP 量子安全风险 Top 10 目前处于 v0.1 草案阶段，开放社区意见征求。这是我们的起点，而非最终定稿清单。 关于本项目 NIST、英国 NCSC...

personal-security-checklist

個人セキュリティチェックリスト デジタルライフを守るための究極のヒント集 🌐digital-defense.io 👉 チェックリストを読む 👈 目次 チェックリスト ウェブサイト API 貢献 クレジット ライセンス チェックリスト 完全なチェックリストは CHECKLIST.md で読むことができます。 生データの表示/編集は personal-security-checklist.yml を参照してください。 ウェブサイト チェックリストを利用する最も簡単な方法は、ウェブサイト digital-defense.io からです。...

CVE-2026-2256-Threat-Model----ms-agent-Command-Injection

CVE-2026-2256-Threat-Model----ms-agent-Command-Injection...

macOS-Security-and-Privacy-Guide

This guide is a collection of techniques for improving the security and privacy of macOS on Apple silicon Macs. It targets experienced users who want security practices commonly used by organizations, but is also suitable for novice users with an interest in privacy and security. For...

sec_review_cve-2024-3094

オープンソースの脆弱性 CVE-2024-3094 の完全なセキュリティレビューが実施されました。得られたデータに基づき、以下を作成しました： 1. レポート「ThreatModel + SecurityReview」 – 脅威の詳細な説明、攻撃 経路、リスク評価、攻撃対象領域を縮小するための推奨事項。 2. 検証テストパッケージ – パッチ適用後に脆弱性の有無を 確認する自動テスト一式。 レポートは ReportFinal.pdf ファイルに収録されています。 情報源： 脆弱性のあるバージョンのアーカイブ：https://github.com/thesamesam/xz-archive...

threat-model-cookbook

OWASP 威胁模型食谱项目 本项目旨在创建并发布威胁模型示例。它们可以采用代码、图形或文本表示的形式。这些模型将使用多样化的技术、方法论和技巧。 你可以从这些模型中学习，以它们为基础构建自己的模型，或者为其中一些模型做出贡献并加以扩展。从而使其成为一本协作式的威胁模型食谱。 https://owasp.org/www-project-threat-model-cookbook/ https://twitter.com/OWASPtmcb 免责声明 本仓库中提供的示例并非安全系统的表示，而是易于建模的不安全系统。其中大多数是现实中并不存在的虚构系统。与真实系统的任何相似之处纯属巧合。 贡...

CVE-2026-82862

Hulumi versions prior to v1.3.2 are affected by a helper script shadowing vulnerability in which the threat-model helper script is resolved from an unsafe root . An attacker can place a malicious file in the workspace directory, causing it to be loaded in place of the intended helper script, resu...

CVE-2026-82862: Untrusted Search Path

Hulumi versions before v1.3.2 resolve the threat-model helper script from an unsafe root, allowing workspace files to shadow the intended helper script. Attackers can place malicious files in the workspace to execute arbitrary code during local skill execution...

CVE-2026-12634 Out-of-bounds stack write in the settings NVS backend from over-reported nvs_read length

The NVS backend of the Zephyr settings subsystem subsys/settings/src/settingsnvs.c reads stored setting-name entries into fixed 74-byte stack buffers and NUL-terminates them with bufrc = '\0', where rc is the return value of nvsread. Per its contract, nvsread returns the full stored entry length...

📄 rouille 3.6.2 HTTP Request Smuggling

rouille versions 3.6.2 and earlier contain an HTTP request smuggling vulnerability in the reverse proxy implementation. The proxy forwards the client's Transfer-Encoding header unchanged while forwarding a de-chunked request body, allowing backend request desynchronization and, under certain...

BackendAI vulnerable to Exposure of Sensitive Information to an Unauthorized Actor

Exposure of sensitive data in active sessions in Lablup's BackendAI allows attackers to retrieve credentials for users on the management platform.NOTE: The maintainers of BackendAI do not consider this report to fit with their threat model and advise users to follow security advice from...

nebula-mesh: POST /api/v1/hosts/{id}/mobile-bundle response lacks Cache-Control: no-store

internal/api/mobilebundle.go:62-66 sets only Content-Type: application/yaml. The Web-UI sibling at internal/web/handlers.go:1316-1321 sets Cache-Control: no-store, Pragma: no-cache, Expires: 0, X-Content-Type-Options: nosniff — and has a test asserting it. The API path was missed. Affected All...

Exploit for CVE-2026-2256

CVE-2026-...

Microsoft's MDASH AI System Finds 16 Windows Flaws Fixed in Patch Tuesday

Microsoft has unveiled a new multi-model artificial intelligence AI-driven system called MDASH to facilitate vulnerability discovery and remediation at scale, adding that it's being tested by some customers as part of a limited private preview. MDASH, short for m ulti-mod el a gentic s canning h...

MATRA: Modeling the Attack Surface of Agentic AI Systems -- OpenClaw Case Study

LLMs are increasingly deployed as autonomous agents with access to tools, databases, and external services, yet practitioners across different sectors lack systematic methods to assess how known threat classes translate into concrete risks within a specific agentic deployment. We present MATRA, a...

Heimdallr: Characterizing and Detecting LLM-Induced Security Risks in GitHub CI Workflows

GitHub Continuous Integration CI workflows increasingly integrate Large Language Models LLMs to automate review, triage, content generation, and repository maintenance. This creates a new attack surface: externally controllable workflow inputs can shape LLM prompts and outputs, which may in turn...

Revisiting JBShield: Breaking and Rebuilding Representation-Level Jailbreak Defenses

Defending large language models LLMs against jailbreak attacks, such as Greedy Coordinate Gradient GCG, remains a challenge, particularly under adaptive threat models where an attacker directly targets the defense mechanism. JBShield, a recent jailbreak defense with a 0% attack success rate in so...

VulStyle: A Multi-Modal Pre-Training for Code Stylometry-Augmented Vulnerability Detection

We present VulStyle, a multi-modal software vulnerability detection model that jointly encodes function-level source code, non-terminal Abstract Syntax Tree AST structure, and code stylometry CStyle features. Prior work in code representation primarily leverages token-level models or full AST...

Primer on GitHub Actions Security - Threat Model, Attacks and Defenses (Part 1/2)

Understanding and defending your GitHub Actions - from threat model to security controls...

Security and Privacy in Virtual and Robotic Assistive Systems: A Comparative Framework

Assistive technologies increasingly support independence, accessibility, and safety for older adults, people with disabilities, and individuals requiring continuous care. Two major categories are virtual assistive systems and robotic assistive systems operating in physical environments. Although...