changeme

changeme 一个默认凭证扫描器。 关于 changeme 接续商业扫描器停止的地方。它专注于检测默认和后门凭证，而不一定检测常见凭证。它的默认模式是扫描 HTTP 默认凭证，但也支持其他凭证。 changeme 设计为可以轻松添加新凭证，而无需编写任何代码或模块。changeme 将凭证数据与代码分离。所有凭证都存储在 yaml 文件中，因此它们既易于人类阅读，也便于 changeme 处理。凭证文件可以通过使用 ./changeme.py --mkcred 工具并回答几个问题来创建。 changeme 支持...

modelaudit

ModelAudit Asegura tus modelos de IA antes del despliegue. Escáner estático que detecta código malicioso, posibles indicadores de puerta trasera y vulnerabilidades de seguridad en archivos de modelos de ML — sin cargarlos ni ejecutarlos nunca. Documentación completa | Ejemplos de uso |...

sticky_keys_hunter

粘滞键猎人 这是一个用于测试粘滞键和 utilman 后门的 POC bash 脚本。该脚本将连接到 RDP 服务器，发送粘滞键和 utilman 触发命令，并对结果进行截图。 此脚本是为了证明我关于以黑盒方式检测这些后门的理论而编写的，自撰写博客文章 追踪粘滞键后门 以来未再更新。然而，@DennisMald 和 @notmedic 进一步推进了这项研究，并在他们的 DEF CON 24 演讲 粘滞键通往王国之路 中发布了 粘滞键杀手 工具。请查看他们的工具，因为它在许多方面优于这个 POC 脚本。 它是如何工作的？ 1. 使用 rdesktop 连接到 RDP 2. 使用 xdoto...

psad

psad - 基于 iptables 日志的入侵检测 简介 端口扫描攻击检测器 psad 是一个轻量级的系统守护进程，用 Perl 编写，旨在与 Linux iptables/ip6tables/firewalld 防火墙代码协同工作，检测可疑流量，如端口扫描和扫描、后门、僵尸网络命令与控制通信等。它提供了一组高度可配置的危险阈值（附带合理的默认值），详细的警报消息，包括源、目标、扫描端口范围、开始和结束时间、TCP 标志及对应的 nmap 选项、反向 DNS 信息、电子邮件和 syslog 警报、通过动态配置 iptables 规则集自动阻止恶意 IP 地址、被动操作系统指纹识别以及...

RCLocals

RCLocals 受Sysinternals中'Autoruns'的启发，RCLocals分析所有Linux启动可能性以发现后门，还执行进程完整性验证，扫描DLL注入进程等 涵盖内容： ·列出系统信任的GPG密钥 ·已安装的软件包 ·文件完整性 ·进程完整性 （不属于任何已安装包的进程及其加载的库） ·名称伪装的进程 （使用prctl在/bin/ps中更改名称的进程） ·CRON条目 ·RC文件 ·X系统启动文件 ·活动的Systemd单元 ·Systemd定时器单元 ·tmpfiles.d ·linger用户 ·恶意命名空间...

vscan

vscan 漏洞扫描工具使用nmap和nse脚本查找漏洞 此工具为使用nmap进行漏洞扫描增加了额外价值。它使用NSE脚本，可以在漏洞检测和利用方面增加灵活性。以下是NSE脚本提供的一些功能： 网络发现 更复杂的版本检测 漏洞检测 后门检测 漏洞利用 此工具使用路径 /usr/share/nmap/scripts/，其中nse脚本位于Kali Linux中。 该工具执行以下操作： 通过检查ICMP请求来检查与目标主机的通信 接受协议名称（如http）作为输入，并执行与该协议相关的所有nse脚本 如果有任何漏洞触发，它将输出保存到日志文件中 它可以对一系列IP地址执行上述所有操作...

CVE-2021-44228

CVE-2021-44228 Backdoor detection for VMware view horizon This includes a canary with an optional submit. Clearly use at own risk blah blah This is designed to be run on Windows VMware Horizon connection servers. It doens't look at the UAG appliances they are Photon linux...

TNC-Defense

TNC-Defense TNC-Defense proporciona código de investigación para detectar y desintoxicar puertas traseras en modelos de difusión de texto a imagen. El repositorio incluye actualmente pipelines de detección para Stable Diffusion v1.4, Stable Diffusion v1.5, Stable Diffusion XL y Stable Diffusion 3...

CVE-NetScalerFileSystemCheck

CVE-NetScalerFileSystemCheck Este script verifica si el Citrix Netscaler ha sido comprometido por ataques CVE-2019-19781 y recopila toda la información del sistema de archivos. Los siguientes archivos y registros serán revisados versión más reciente 1.13: Carpetas de plantilla para archivos XML...

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...

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...

Coward: toward Practical Proactive Federated Backdoor Defense Via Collision-Based Watermark

Backdoor detection is currently the mainstream defense against backdoor attacks in federated learning FL, where malicious clients upload poisoned updates that compromise the global model and undermine the reliability of FL deployments. Existing backdoor detection techniques fall into two...

DUP: Detection-Guided Unlearning for Backdoor Purification in Language Models

As backdoor attacks become more stealthy and robust, they reveal critical weaknesses in current defense strategies: detection methods often rely on coarse-grained feature statistics, and purification methods typically require full retraining or additional clean models. To address these challenges...

Exploit for Improper Access Control in Elasticsearch

欢迎各位大佬提BUG,当前版本 AssetScanV1.3 周期 初版：2019年11月28日 V1.0初版编写完成 修改1：2019年12月02日 感谢Shadow·J反馈kali下文件导入异常 修改2：2019年12月03日 V1.1发布，新增ARP存活检测（回滚，测bug） 修改3：2019年12月04日 V1.2发布，修复漏洞脚本异常，修复weblogic脚本 修改4：2019年12月05日 V1.2修改，感谢sevck提供设计思路以及代码不规范问题 修改5：2019年12月05日 V1.2修改，修复IP数据处理异常 修改6：2019年12月19日...