Open-source alternatives to AI Infra Guard

SkillSpector is a security scanner designed to detect vulnerabilities and malicious patterns in AI agent plugins and extensions before they are installed. It functions as a runtime guardrail that calculates numeric risk scores and assigns severity labels to provide installation recommendations or block risky external extensions. The project distinguishes itself by using language models to perform semantic code analysis, evaluating code intent and context to reduce false positives. It also employs fingerprint-based issue suppression to track and ignore previously accepted risks across repeated

L1B3RT4S is an adversarial machine learning toolkit designed for red teaming and evaluating the robustness of large language models. It provides a research framework for investigating how safety alignment mechanisms and content moderation systems respond to sophisticated input strategies. The project focuses on identifying vulnerabilities in model guardrails by employing techniques such as adversarial narrative framing, dynamic context injection, and latent space steering. It utilizes multi-agent prompt decomposition and recursive text transformation to analyze how structural changes to input

RagaAI-Catalyst is a suite of software implementation tools providing an SDK, dashboard, and platform for monitoring, debugging, red-teaming, and evaluating agentic AI workflows. It serves as an observability framework for tracing the execution paths of large language models and multi-agent systems. The project distinguishes itself through a security suite for automated red-teaming and vulnerability scanning to detect biases, alongside a centralized prompt registry that decouples templates from application code. It further provides an evaluation platform that combines synthetic data generatio

This repository provides tools and methodologies for studying adversarial attacks on large language models. It focuses on understanding how carefully crafted inputs can manipulate or bypass the safety mechanisms of LLMs, enabling researchers to probe model vulnerabilities and improve their robustness. The project covers techniques for generating adversarial prompts, evaluating model responses under attack conditions, and analyzing the effectiveness of different attack strategies.

Superagent is a framework for AI assistant orchestration and agent security. It provides the tools to build intelligent assistants that integrate external APIs and maintain conversation memory to automate complex tasks. The project focuses on AI agent security through adversarial testing, red teaming, and the detection of prompt injections and malicious tool calls. It includes automated vulnerability patching, which scans codebases and configurations for security flaws and generates pull requests with fixes. The platform supports retrieval augmented generation by connecting language models t

Giskard is an evaluation framework, testing library, and quality monitoring system for large language models and AI agents. It serves as a toolkit for quantifying model performance and reliability, providing specialized capabilities for validating retrieval-augmented generation pipelines. The project distinguishes itself through an automated red teaming tool and security scanner designed to identify vulnerabilities, prompt injections, and safety risks. It utilizes adversarial probing and synthetic edge case generation to quantify model robustness and detect information disclosure. The platfo

Superagent is an AI safety platform that protects applications from prompt injections, data leaks, and harmful outputs through built-in guardrails. It functions as a prompt injection detection system, data redaction tool, and red team testing tool, automatically removing personally identifiable information and protected health data from AI inputs and outputs while scanning image uploads with vision AI to detect visual prompt injection attacks before processing. The platform routes every prompt through a sequential pipeline of safety checks including injection detection, data redaction, and co

WPScan is a security analysis utility and vulnerability scanner designed specifically for auditing WordPress installations and other content management systems. It functions as a web application security tool that identifies misconfigurations, outdated software, and security holes in core installations, plugins, and themes. The tool employs black-box scanning techniques to perform site component enumeration, identifying users, themes, and plugins by matching known file paths and response signatures. It matches these detected components against a database of known security flaws to analyze the

Snyk is an application security testing platform designed to identify and remediate vulnerabilities across source code, open-source dependencies, container images, and infrastructure-as-code configurations. It functions as a comprehensive security workflow automation tool, utilizing a static analysis engine and dependency graph mapping to detect security flaws and license compliance issues throughout the software development lifecycle. The platform distinguishes itself through agentic workflow orchestration and an automated remediation pipeline that generates and submits pull requests to patc

DefectDojo is a vulnerability management system and application security orchestration tool. It serves as a centralized platform for importing, deduplicating, and tracking security findings from multiple scanners and tools to manage an organization's overall security posture. The system distinguishes itself by aggregating findings from various security tools into a single report and normalizing that data to prioritize remediation. It provides specific workflows for vulnerability triage and deduplication to reduce noise and redundant manual work across the software development lifecycle. The

This project is a Docker educational resource and a collection of practical examples designed for learning containerization technologies. It serves as a guide for understanding container fundamentals, including the creation and management of custom images and the use of registries. The repository provides specialized references for container security hardening, such as managing kernel privileges and implementing supply chain security. It also includes tutorials for multi-container orchestration and a DevOps guide focused on CI/CD automation and image optimization. The material covers a broad

Subfinder is a security reconnaissance framework designed for subdomain enumeration and attack surface management. It functions as a discovery engine that identifies and maps internet-exposed infrastructure, cloud-hosted assets, and network ranges to maintain a comprehensive inventory of an organization's digital footprint. The project distinguishes itself through a modular, template-driven scanning engine that executes security checks against discovered assets. It leverages cloud-native asset discovery to query provider APIs and infrastructure metadata, while supporting distributed agent orc

Naabu is a port scanner library and tool that probes hosts for open ports using SYN, CONNECT, and UDP methods to identify active services. It functions as a Go library for embedding port scanning into programs, and as a standalone tool that accepts targets as hostnames, IP addresses, CIDR ranges, or ASN numbers. The tool discovers live hosts before scanning, filters ports by range or top lists, and can integrate with Nmap for service version detection. The project distinguishes itself through its SYN-based port probing approach that sends TCP SYN packets and analyzes responses without complet

PurpleLlama is a collection of security toolsets and frameworks designed to audit large language model vulnerabilities and implement runtime input-output guardrails. It provides a security evaluation framework and benchmark suite to quantify risks associated with prompt injections and the generation of malicious code. The project includes a content moderator and input-output filters that use a standardized taxonomy to identify and block harmful content, jailbreaking attempts, and insecure commands. It also features capabilities for sensitive document classification to prevent the unauthorized

NeMo-Guardrails is a toolkit for adding programmable safety constraints and dialogue boundaries to large language model conversational systems. It functions as security middleware that intercepts inputs and outputs to block prompt injections, jailbreaks, and sensitive data leaks, while providing a conversational dialogue manager to define structured interaction flows through configuration files. The framework includes a hallucination filter to screen model outputs for factual accuracy and a specialized modeling language for defining conversational flows and constraints. It provides capabiliti

This project is a comprehensive ecosystem of frameworks, toolkits, and datasets designed to evaluate model vulnerabilities and analyze jailbreak patterns. It serves as an adversarial testing framework and research toolkit for measuring the effectiveness of safety guardrails in large language models. The system includes a library of real-world prompt injection datasets harvested from social media to study bypass strategies. It provides specialized tools for semantic attack analysis and prompt visualization, allowing for the mapping of relationships between adversarial prompts to discover commo

Learn-Web-Hacking is a structured web security study guide and penetration testing knowledge base. It provides a collection of research notes focused on identifying and exploiting vulnerabilities in web applications and network protocols. The project includes specialized frameworks for evaluating security risks in large language models to prevent prompt injection, as well as guides for hardening cloud-native infrastructure, including container standards and orchestration tools. It also covers the analysis of identity standards and authentication protocols. The material spans a broad range of

Agent-skills is a collection of structured instructions and behavioral personas designed to standardize how AI coding agents perform engineering tasks. It functions as a workflow orchestrator that maps natural language intent to repeatable technical sequences and verification checklists. The project distinguishes itself through the use of specialized markdown-defined roles, such as security auditors or test engineers, to apply targeted domain expertise. It employs an evidence-based verification model that requires runtime data or passing tests as mandatory exit criteria to ensure AI-generated

LLM Guard is a security firewall and guardrail framework designed to scan and sanitize inputs and outputs for large language models. It functions as a proxy gateway and security layer to block prompt injections, toxicity, and sensitive data leakage while ensuring that model interactions remain compliant with organizational policies. The system distinguishes itself through a modular scanner pipeline that utilizes local model orchestration to eliminate external network dependencies. It supports real-time security filtering via streaming chunk analysis and implements a fail-fast execution model

Promptfoo is an evaluation framework designed for testing, benchmarking, and red-teaming language models and agentic workflows. It provides a unified environment to run prompts against multiple providers, allowing developers to systematically validate model outputs against objective assertions, semantic similarity metrics, and custom grading rubrics. The platform distinguishes itself through a provider-agnostic execution layer and a stateful orchestrator capable of simulating multi-turn conversations and complex tool-use trajectories. It includes a dedicated adversarial mutation pipeline that

Windows-Exploit-Suggester is a security audit tool designed to scan Windows systems for outdated components and missing security patches. It functions as a vulnerability scanner that compares target patch levels against official vendor security bulletins to identify security gaps. The tool specializes in exploit mapping, linking identified missing updates to known public exploit code and available penetration testing modules. It automates the research process by cross-referencing missing patches with specific vulnerability identifiers to determine applicable attack vectors. The system includ

Cleverhans is an adversarial machine learning library and toolkit designed to generate adversarial examples, incorporate them into training loops, and benchmark the resilience of machine learning models. It provides a gradient-based attack framework for constructing both white-box and black-box attacks to identify model misclassifications. The project includes capabilities for model robustness benchmarking, allowing users to evaluate and verify how models resist evasion attacks and malicious input perturbations. It also facilitates adversarial training to increase a model's resistance to pert

lmms-eval is a benchmarking system and performance analysis suite designed to measure the capabilities of large multimodal models. It provides a framework for evaluating models across text, image, audio, and video datasets, serving as a multimodal dataset orchestrator and benchmarking tool to quantify accuracy and efficiency. The project distinguishes itself through a unified multimodal message protocol that structures diverse media inputs for consistent model consumption. It features specialized benchmarking for audio, video, visual, document, and spatial reasoning, alongside tools for model

G0DM0D3 is a static web client and multi-model chat gateway designed for AI research, prompt optimization, and red teaming. It provides a unified interface to query numerous AI models in parallel, allowing for the simultaneous evaluation of different prompt variations and sampling parameters to identify the most successful outputs. The project features specialized tooling for probing safety filters and bypassing model constraints through an input perturbation engine that applies text obfuscation and character substitution. It includes a composite scoring system to rank model performance and a

This project is an open-source intelligence reconnaissance framework and recursive attack surface mapper. It functions as a containerized security scanner designed to map public-facing infrastructure, perform subdomain enumeration, and automate the gathering of open-source intelligence. The system employs a recursive discovery engine to iteratively explore target infrastructure, utilizing a plugin-based module architecture to extend scanning capabilities. It integrates third-party APIs for data enrichment and applies YARA rules across discovered assets to identify specific vulnerability patte

Dependency-Track is a software composition analysis tool and vulnerability management system designed to track dependencies and supply chain risk. It functions as a platform for ingesting and analyzing CycloneDX software bills of materials to identify known vulnerabilities and license compliance issues within third-party software components. The system distinguishes itself by mirroring external vulnerability databases locally to enable fast offline analysis and using VEX documents to differentiate between technical vulnerabilities and actual contextual risks. It also integrates with identity

dependabot-core is the automated dependency management engine that powers multi-ecosystem package updates and vulnerability remediation. It parses package manifests and lockfiles, polls package registries for newer versions, resolves version constraints across entire dependency trees, and generates pull requests with changelogs and structured descriptions. The system integrates vulnerability database matching to detect known security flaws and can automatically create remediation pull requests. What distinguishes this project is its handling of complex multi-ecosystem resolution across dozens