sticky_keys_hunter

Sticky Keys Hunter Ce script bash POC teste les portes dérobées des touches rémanentes et d'utilman. Le script se connecte à un serveur RDP, envoie les déclencheurs des touches rémanentes et d'utilman, puis prend une capture d'écran du résultat. Ce script a été écrit pour prouver une théorie que...

changeme

changeme Un scanner d'identifiants par défaut. À propos changeme reprend là où les scanners commerciaux s'arrêtent. Il se concentre sur la détection des identifiants par défaut et de backdoor, et pas nécessairement des identifiants courants. Son mode par défaut consiste à analyser les identifiant...

psad

psad - Détection d'intrusion avec les journaux iptables Introduction Le Port Scan Attack Detector psad est un démon système léger écrit en conçu pour fonctionner avec le pare-feu Linux iptables/ip6tables/firewalld afin de détecter le trafic suspect tel que les scans de ports et les balayages, les...

vscan

vscan L'outil de scan de vulnérabilités utilise nmap et les scripts NSE pour détecter des vulnérabilités. Cet outil apporte une valeur ajoutée au scan de vulnérabilités avec nmap. Il utilise les scripts NSE qui offrent une flexibilité en termes de détection et d'exploitation de vulnérabilités...

modelaudit

ModelAudit Обезопасьте свои AI-модели перед развёртыванием. Статический сканер, который обнаруживает вредоносный код, потенциальные индикаторы бэкдоров и уязвимости безопасности в файлах ML-моделей — без их загрузки или выполнения. Полная документация | Примеры использования | Поддерживаемые...

RCLocals

RCLocals Вдохновленный утилитой 'Autoruns' из Sysinternals, RCLocals анализирует все возможности автозапуска Linux для поиска бэкдоров, а также выполняет проверку целостности процессов, сканирование на наличие DLL-инъекций и многое другое. Охваченные возможности: ·Список GPG-ключей, доверяемых...

CVE-2021-44228

CVE-2021-44228 Обнаружение бэкдора для VMware View Horizon Включает канареечную проверку canary с опциональной отправкой. Очевидно, используйте на свой страх и риск, и так далее. Предназначен для запуска на серверах подключения Windows VMware Horizon. Он не проверяет устройства UAG они работают н...

TNC-Defense

TNC-Defense TNC-Defense предоставляет исследовательский код для обнаружения и обезвреживания бэкдоров в диффузионных моделях генерации изображений по текстовому описанию. В настоящее время репозиторий включает конвейеры обнаружения для Stable Diffusion v1.4, Stable Diffusion v1.5, Stable Diffusio...

CVE-NetScalerFileSystemCheck

CVE-NetScalerFileSystemCheck Этот скрипт проверяет, был ли Citrix NetScaler скомпрометирован атаками CVE-2019-19781, и собирает всю информацию о файловой системе. Будут проверены следующие файлы и журналы последняя версия 1.13: Папки шаблонов для XML-файлов Файлы журналов доступа Apache Файлы...

Learning Normal Diffusion Dynamics for Backdoor Defense in Text-To-Image Models

Backdoor attacks pose a serious threat to the secure deployment of text-to-image T2I diffusion models. Existing defenses typically detect backdoors from specific abnormal patterns in internal representations, which may limit their generalizability with the emergence of increasingly diverse attack...

Security Properties of Neural Networks As Decision Problems

Certifying a deployed neural network raises decision problems that the verification literature has not classified: whether the model carries a backdoor planted in its training data, whether a fault in its stored parameters can drive it into an unsafe state, whether its output leaks a private part...

WordPress Adds Automated Plugin Reviews to Block High-Risk Updates Before Distribution

WordPress has announced it's launching an automated security review for every release of a plugin before it's distributed through the WordPress.org update API so as to analyze it for potential security issues and ensure there are no risks involved. "New plugins are reviewed before they enter the...

When Modalities Fail to Tango: Conformal Backdoor Detection in Multimodal Contrastive Learning

Backdoor attacks in multimodal contrastive learning MCL have garnered growing attention in recent years, as many downstream tasks critically depend on pre-trained MCL models. Existing detection-based defenses predominantly rely on the CLIPScore metric, under the assumption that poisoned pairs...

CLIP-Inspector: Model-Level Backdoor Detection for Prompt-Tuned CLIP Via OOD Trigger Inversion

Organisations with limited data and computational resources increasingly outsource model training to Machine Learning as a Service MLaaS providers, who adapt vision-language models VLMs such as CLIP to downstream tasks via prompt tuning rather than training from scratch. This semi-honest setting...

Detecting backdoored language models at scale

Today, we are releasing new research on detecting backdoors in open-weight language models. Our research highlights several key properties of language model backdoors, laying the groundwork for a practical scanner designed to detect backdoored models at scale and improve overall trust in AI...

Detecting backdoored language models at scale

Today, we are releasing new research on detecting backdoors in open-weight language models. Our research highlights several key properties of language model backdoors, laying the groundwork for a practical scanner designed to detect backdoored models at scale and improve overall trust in AI...

LoRA As Oracle

Backdoored and privacy-leaking deep neural networks pose a serious threat to the deployment of machine learning systems in security-critical settings. Existing defenses for backdoor detection and membership inference typically require access to clean reference models, extensive retraining, or...

Cross-LLM Generalization of Behavioral Backdoor Detection in AI Agent Supply Chains

As AI agents become integral to enterprise workflows, their reliance on shared tool libraries and pre-trained components creates significant supply chain vulnerabilities. While previous work has demonstrated behavioral backdoor detection within individual LLM architectures, the critical question ...

PoTS: Proof-Of-Training-Steps for Backdoor Detection in Large Language Models

As Large Language Models LLMs gain traction across critical domains, ensuring secure and trustworthy training processes has become a major concern. Backdoor attacks, where malicious actors inject hidden triggers into training data, are particularly insidious and difficult to detect. Existing...

Binary Diff Summarization Using Large Language Models

Security of software supply chains is necessary to ensure that software updates do not contain maliciously injected code or introduce vulnerabilities that may compromise the integrity of critical infrastructure. Verifying the integrity of software updates involves binary differential analysis...