sticky_keys_hunter

Sticky Keys हंटर यह POC bash स्क्रिप्ट sticky keys और utilman बैकडोर के लिए परीक्षण करती है। स्क्रिप्ट एक RDP सर्वर से जुड़ेगी, sticky keys और utilman दोनों ट्रिगर भेजेगी और परिणाम का स्क्रीनशॉट लेगी। यह स्क्रिप्ट एक सिद्धांत को साबित करने के लिए लिखी गई थी जो मेरे पास इन बैकडोर को ब्लैकबॉक्स तरी...

changeme

changeme एक डिफ़ॉल्ट क्रेडेंशियल स्कैनर। परिचय changeme वहीं से शुरू होता है जहाँ व्यावसायिक स्कैनर छोड़ देते हैं। इसका ध्यान डिफ़ॉल्ट और बैकडोर क्रेडेंशियल्स का पता लगाने पर है, न कि सामान्य क्रेडेंशियल्स पर। इसका डिफ़ॉल्ट मोड HTTP डिफ़ॉल्ट क्रेडेंशियल्स को स्कैन करना है, लेकिन अन्य क्रेडेंशियल्...

psad

psad - iptables लॉग के साथ घुसपैठ का पता लगाना परिचय पोर्ट स्कैन अटैक डिटेक्टर psad एक हल्का सिस्टम डेमॉन है जो लिनक्स iptables/ip6tables/firewalld फ़ायरवॉल कोड के साथ काम करने के लिए डिज़ाइन किया गया है, ताकि संदिग्ध ट्रैफ़िक जैसे पोर्ट स्कैन और स्वीप, बैकडोर, बॉटनेट कमांड और कंट्रोल संचार, और...

vscan

vscan Ferramenta de scanner de vulnerabilidades que usa nmap e scripts NSE para encontrar vulnerabilidades Esta ferramenta agrega valor adicional à varredura de vulnerabilidades com nmap. Ela usa scripts NSE que podem adicionar flexibilidade em termos de detecção e exploração de vulnerabilidades...

modelaudit

ModelAudit तैनाती से पहले अपने AI मॉडलों को सुरक्षित करें। स्टैटिक स्कैनर जो ML मॉडल फ़ाइलों में दुर्भावनापूर्ण कोड, संभावित बैकडोर संकेतकों, और सुरक्षा कमज़ोरियों का पता लगाता है — उन्हें कभी लोड या निष्पादित किए बिना। पूर्ण दस्तावेज़ीकरण | उपयोग उदाहरण | समर्थित प्रारूप ModelAudit क्यों मॉडल...

RCLocals

RCLocals Inspirado pelo 'Autoruns' da Sysinternals, o RCLocals analisa todas as possibilidades de inicialização do Linux para encontrar backdoors, também realiza verificação de integridade de processos, verifica processos com injeção de DLL e muito mais Itens cobertos: ·Listar chaves GPG confiada...

CVE-2021-44228

CVE-2021-44228 كشف الباب الخلفي لـ VMware View Horizon يتضمن هذا كاناري مع إرسال اختياري. يُستخدم بوضوح على مسؤوليتك الخاصة وهكذا تم تصميم هذا ليعمل على خوادم اتصال VMware Horizon بنظام Windows. لا يفحص أجهزة UAG فهي تعمل بنظام Photon Linux...

TNC-Defense

TNC-Defense TNC-Defense, टेक्स्ट-टू-इमेज डिफ्यूज़न मॉडल में बैकडोर का पता लगाने और उन्हें डिटॉक्सिफाई करने के लिए शोध कोड प्रदान करता है। रिपॉजिटरी में वर्तमान में Stable Diffusion v1.4, Stable Diffusion v1.5, Stable Diffusion XL और Stable Diffusion 3 Medium के लिए डिटेक्शन पाइपलाइन, साथ ही Stabl...

CVE-NetScalerFileSystemCheck

CVE-NetScalerFileSystemCheck यह स्क्रिप्ट जाँचती है कि क्या Citrix Netscaler CVE-2019-19781 हमलों से समझौता किया गया है और सभी फ़ाइल सिस्टम जानकारी एकत्र करती है। निम्नलिखित फ़ाइलें और लॉग जाँचे जाएँगे नवीनतम संस्करण 1.13: XML फ़ाइलों के लिए टेम्पलेट फ़ोल्डर Apache एक्सेस लॉगफ़ाइलें Apache त्रुटि...

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...