# LLM Prompt Injection Defense Tools

> Search results for `defend LLM apps against prompt injection` on awesome-repositories.com. 115 total matches; showing the first 50.

Explore on the web: https://awesome-repositories.com/q/defend-llm-apps-against-prompt-injection

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## Results

- [dair-ai/prompt-engineering-guide](https://awesome-repositories.com/repository/dair-ai-prompt-engineering-guide.md) (75,678 ⭐) — This project is a comprehensive educational resource and technical guide focused on the development, optimization, and application of large language models. It provides a structured curriculum for mastering prompt engineering, ranging from foundational principles of instruction design to advanced techniques for improving model reasoning, accuracy, and reliability.

The guide distinguishes itself by offering deep technical insights into agentic workflows and autonomous system design. It covers the implementation of multi-step reasoning chains, tool integration through function calling, and stat
- [giskard-ai/giskard](https://awesome-repositories.com/repository/giskard-ai-giskard.md) (5,434 ⭐) — 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
- [mastra-ai/mastra](https://awesome-repositories.com/repository/mastra-ai-mastra.md) (21,221 ⭐) — Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention.

The framework distinguishes itself through its focus on observability and secure, isolated execut
- [mlabonne/llm-course](https://awesome-repositories.com/repository/mlabonne-llm-course.md) (80,178 ⭐) — This project is a comprehensive educational curriculum and engineering handbook focused on the lifecycle of large language models. It serves as a structured knowledge base for machine learning practitioners, covering the fundamental mathematical and architectural principles of transformer-based sequence modeling, as well as the practical implementation of supervised instruction fine-tuning and preference-based model alignment.

The repository distinguishes itself by providing a deep dive into advanced model composition and optimization techniques. It details methodologies for weight-space mode
- [nidhinjs/prompt-master](https://awesome-repositories.com/repository/nidhinjs-prompt-master.md) (9,731 ⭐) — Prompt Master is an AI skill that automates prompt engineering by detecting the target AI system and applying the correct prompt architecture automatically. It generates optimized prompts for over 30 different AI tools, adapting format and syntax to each target system without requiring manual conversion.

The system distinguishes itself through several integrated capabilities. It extracts missing dimensions of intent from vague requests by asking up to three targeted clarifying questions before generating a final prompt. A memory block of prior decisions and constraints is prepended to maintai
- [simeononsecurity/windows-defender-hardening](https://awesome-repositories.com/repository/simeononsecurity-windows-defender-hardening.md) (77 ⭐) — Take advantage of some more advanced Windows Defender settings.
- [protectai/llm-guard](https://awesome-repositories.com/repository/protectai-llm-guard.md) (2,561 ⭐) — 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
- [aounon/certified-llm-safety](https://awesome-repositories.com/repository/aounon-certified-llm-safety.md) (53 ⭐) — This repository contains code for the paper Certifying LLM Safety against Adversarial Prompting.
- [0x4m4/hexstrike-ai](https://awesome-repositories.com/repository/0x4m4-hexstrike-ai.md) (9,617 ⭐) — This project is a comprehensive security platform providing an LLM security orchestration framework, an AI agent firewall, and tools for vulnerability remediation, compliance automation, and endpoint protection. It functions as a centralized system to protect AI models from adversarial exploits while managing the identification and patching of software flaws.

The platform distinguishes itself through the coordination of specialized AI agents to automate complex security workflows, including reconnaissance, bug hunting, and exploit development. It implements dedicated guardrails to block promp
- [wagner-group/prompt-injection-defense](https://awesome-repositories.com/repository/wagner-group-prompt-injection-defense.md) (36 ⭐) — Fine-tuning base models to build robust task-specific models
- [nearai/ironclaw](https://awesome-repositories.com/repository/nearai-ironclaw.md) (12,456 ⭐) — Ironclaw is an LLM orchestration framework and AI agent gateway designed to connect large language models with external tools, messaging interfaces, and persistent memory systems. It functions as a communication layer that routes interactions between users and AI models via HTTP webhooks and various messaging channels.

The system focuses on secure tool execution through a WebAssembly sandbox and isolated containers, which allows the framework to run untrusted code and dynamically generate new tools from natural language descriptions. Security middleware provides prompt injection defense and s
- [angular/angular](https://awesome-repositories.com/repository/angular-angular.md) (100,360 ⭐) — Angular is a platform for building web applications using a component-based architecture. It provides a comprehensive suite of tools for managing encapsulated UI units, including hierarchical dependency injection, a declarative template system, and fine-grained reactivity through signals. The framework supports complex application requirements such as client-side routing, form management, and internationalization.

The project includes a command-line interface for scaffolding and build automation, alongside a testing ecosystem for unit and integration verification. It offers multiple rendering
- [elder-plinius/cl4r1t4s](https://awesome-repositories.com/repository/elder-plinius-cl4r1t4s.md) (40,356 ⭐) — CL4R1T4S is a framework designed to orchestrate generative AI workflows and optimize language model outputs. It functions as a centralized utility for managing, versioning, and deploying structured system prompts and behavioral parameters to ensure consistent performance across complex tasks.

The project distinguishes itself by implementing a structured pipeline that wraps model interactions to enforce behavioral constraints and sanitize inputs. This orchestration layer incorporates heuristic-based validation and stateful context management to maintain coherence and quality throughout multi-s
- [langgptai/awesome-llama-prompts](https://awesome-repositories.com/repository/langgptai-awesome-llama-prompts.md) (270 ⭐) — LLM prompts, llama3 prompts, llama2 prompts
- [anthropics/defending-code-reference-harness](https://awesome-repositories.com/repository/anthropics-defending-code-reference-harness.md) (6,224 ⭐) — This project is a framework for the autonomous discovery and remediation of security vulnerabilities using large language model agents. It functions as a security research pipeline that automates the process of reconnaissance, crash discovery, and exploitability analysis to identify reproducible software bugs.

The system distinguishes itself by utilizing a containerized agent sandbox that restricts network egress and filesystem access to prevent host compromise. It employs a specialized patch generation and validation loop, which includes adversarial re-attack testing where a fresh agent atte
- [diegosouzapw/omniroute](https://awesome-repositories.com/repository/diegosouzapw-omniroute.md) (6,391 ⭐) — OmniRoute is a unified LLM API gateway that connects multiple AI providers to a single endpoint. Its primary purpose is to simplify the integration of various AI models into tools and agents by translating different provider formats into a standardized API.

The project distinguishes itself through a multi-strategy request routing system that optimizes for cost, speed, and availability, including automatic model fallbacks and a circuit-breaker resilience model to isolate provider failures. It employs a local-first security posture, using AES-256-GCM encryption to store API keys and conversatio
- [pathwaycom/llm-app](https://awesome-repositories.com/repository/pathwaycom-llm-app.md) (59,341 ⭐) — This project is a data processing engine and AI application platform designed for building production-grade machine learning workflows. It provides a unified programming model that handles both historical batch data and live stream ingestion, enabling the development of real-time ETL pipelines and scalable data transformation workflows.

The framework distinguishes itself through differential dataflow execution, which propagates only changes through a pipeline rather than recomputing entire datasets. It supports distributed state management across worker nodes and utilizes incremental stream p
- [helicone/helicone](https://awesome-repositories.com/repository/helicone-helicone.md) (5,830 ⭐) — Helicone is an AI gateway and observability platform designed to intercept, manage, and monitor interactions with large language models. By acting as a reverse-proxy, it provides a centralized layer for routing requests across multiple AI providers, allowing developers to maintain consistent application logic while gaining deep visibility into model performance, usage, and costs.

The platform distinguishes itself through a robust suite of traffic management and prompt engineering tools. It enables policy-driven control, including automatic failover between providers, rate limiting, and edge-b
- [langgptai/llm-jailbreaks](https://awesome-repositories.com/repository/langgptai-llm-jailbreaks.md) (680 ⭐) — LLM Jailbreaks, ChatGPT, Claude, Llama, DAN Prompts, Prompt Leaking
- [pewdiepie-archdaemon/odysseus](https://awesome-repositories.com/repository/pewdiepie-archdaemon-odysseus.md) (72,184 ⭐) — Odysseus is a self-hosted AI workspace and autonomous agent framework designed for deploying and managing large language models. It serves as a centralized platform for orchestrating agentic tasks, utilizing a model context protocol server to connect AI models to external system utilities, browser automation, and local hardware.

The system distinguishes itself through a combination of retrieval-augmented generation and a RAG knowledge base, using vector stores and local embeddings to provide persistent semantic memory. It further integrates AI-driven communication management to triage email i
- [f/prompts.chat](https://awesome-repositories.com/repository/f-prompts-chat.md) (163,814 ⭐) — This platform serves as a centralized management system for organizing, refining, and versioning AI instructions and agent skills. It functions as a repository that enables users to store, categorize, and retrieve structured prompts, ensuring consistent performance across various artificial intelligence models. By integrating with the Model Context Protocol, the system allows external AI assistants and development environments to discover and access these instruction libraries directly.

The platform distinguishes itself through its focus on prompt engineering and automated refinement, utilizi
- [kamranahmedse/developer-roadmap](https://awesome-repositories.com/repository/kamranahmedse-developer-roadmap.md) (357,434 ⭐) — Developer Roadmap is a community-driven platform that provides structured, graph-based learning paths for software engineering. It serves as a comprehensive knowledge repository where technical domains are organized into visual sequences to guide professional skill acquisition and career growth.

The project distinguishes itself through a collaborative ecosystem that enables users to contribute roadmaps, curate industry best practices, and maintain professional profiles. It integrates diagnostic assessment frameworks to evaluate technical proficiency, helping developers identify knowledge gaps
- [deadbits/vigil-llm](https://awesome-repositories.com/repository/deadbits-vigil-llm.md) (482 ⭐) — ⚡ Security scanner for LLM prompts ⚡
- [nirdiamant/prompt_engineering](https://awesome-repositories.com/repository/nirdiamant-prompt-engineering.md) (7,159 ⭐) — This project is a comprehensive guide and framework for designing, optimizing, and securing inputs to improve the accuracy and reasoning of large language model outputs. It provides core methodologies for implementing logical reasoning steps, example-based learning, and reusable template systems.

The framework distinguishes itself through a focus on security guardrails and ethical auditing, implementing primitives to prevent adversarial prompt injection attacks and identify biases. It also emphasizes structured generation, using persona assignment and negative constraints to control the tone,
- [dontriskit/awesome-ai-system-prompts](https://awesome-repositories.com/repository/dontriskit-awesome-ai-system-prompts.md) (5,206 ⭐) — This project is a comprehensive library of structured system prompts and configuration templates designed to define the behavior, persona, and operational boundaries of autonomous artificial intelligence agents. It serves as a framework for prompt engineering, providing modular instructions that help models parse complex tasks, maintain consistent interaction tones, and adhere to specific domain constraints.

The repository distinguishes itself by offering specialized configurations for agent safety and security, including protocols to prevent prompt injection and unauthorized data access. It
- [prompt-engineering/prompt-patterns](https://awesome-repositories.com/repository/prompt-engineering-prompt-patterns.md) (3,098 ⭐) — 欢迎使用集成了这些模式的工具：https://github.com/prompt-engineering/click-prompt
- [formbricks/formbricks](https://awesome-repositories.com/repository/formbricks-formbricks.md) (12,391 ⭐) — Formbricks is an open-source survey and feedback platform designed to help teams capture and analyze user insights through targeted, in-app, and website-based interactions. It functions as a comprehensive customer experience analytics system that allows organizations to maintain full control over their data, user attributes, and survey workflows.

The platform distinguishes itself through its event-driven architecture, which enables precise behavioral targeting by triggering surveys based on specific user actions or application events. It supports deep integration with external ecosystems by a
- [qwenlm/qwen](https://awesome-repositories.com/repository/qwenlm-qwen.md) (21,294 ⭐) — Qwen is a comprehensive framework for large language model development, serving, and deployment. It provides a complete ecosystem for transformer-based sequence modeling, offering base models alongside specialized tools for instruction-tuned alignment, fine-tuning, and long-context inference. The project is designed to support both research and production environments, enabling users to train, optimize, and host generative models locally or across distributed hardware.

The framework distinguishes itself through its focus on high-performance serving and extensibility. It features a high-perfor
- [forem/forem](https://awesome-repositories.com/repository/forem-forem.md) (22,726 ⭐) — Forem is an open-source platform designed for building and managing technical communities. It functions as a social publishing engine that enables members to share long-form content, participate in threaded discussions, and engage through social interactions. The platform provides tools for organizations to maintain branded profiles, host community hackathons, and facilitate collaborative learning through structured educational tracks.

Beyond its social features, Forem integrates advanced capabilities for AI agent workflow orchestration and codebase knowledge graphing. It allows developers to
- [cranot/chatbot-injections-exploits](https://awesome-repositories.com/repository/cranot-chatbot-injections-exploits.md) (407 ⭐) — ChatBot Injection and Exploit Examples: A Curated List of Prompt Engineer Commands - ChatGPT
- [midudev/jscamp](https://awesome-repositories.com/repository/midudev-jscamp.md) (3,811 ⭐) — jscamp is a full-stack web development and education project focused on mastering JavaScript, TypeScript, and AI integration. It provides a structured curriculum and interactive exercises covering language fundamentals, frontend engineering, and backend API development.

The project distinguishes itself through the implementation of autonomous AI agents capable of complex task automation, such as modifying files, managing servers, and executing API calls. It includes advanced AI development tools for conversational querying, real-time code suggestions, and automated repository analysis to gene
- [crewaiinc/crewai](https://awesome-repositories.com/repository/crewaiinc-crewai.md) (53,687 ⭐) — CrewAI is a multi-agent orchestration framework designed for building autonomous systems that execute complex, multi-step workflows. It provides a development platform where specialized agents are defined with specific roles, goals, and tool sets to perform tasks collaboratively. By leveraging a declarative workflow engine, the system manages task dependencies, state transitions, and execution logic, allowing for the creation of structured, stateful sequences of operations.

The framework distinguishes itself through its hierarchical management capabilities, which utilize manager agents to coo
- [langgptai/awesome-gemini-prompts](https://awesome-repositories.com/repository/langgptai-awesome-gemini-prompts.md) (471 ⭐) — Gemini Prompts, Gemini 3 Prompts, jailbreak, LLM Prompts, LangGPT —— by 云中江树
- [owasp/cheatsheetseries](https://awesome-repositories.com/repository/owasp-cheatsheetseries.md) (32,298 ⭐) — The OWASP Cheat Sheet Series is a comprehensive, community-driven repository of concise security best practices and defensive coding patterns. It serves as a centralized knowledge base for developers and security professionals, providing actionable guidance to secure applications across the entire software development lifecycle. The project covers a vast array of security domains, ranging from fundamental web application hardening and authentication protocols to specialized controls for modern infrastructure and artificial intelligence systems.

What distinguishes this project is its decentral
- [yihanwang617/llm-jailbreaking-defense-backtranslation](https://awesome-repositories.com/repository/yihanwang617-llm-jailbreaking-defense-backtranslation.md) (35 ⭐) — Defending LLMs against Jailbreaking Attacks via Backtranslation
- [modular/modular](https://awesome-repositories.com/repository/modular-modular.md) (26,357 ⭐) — Modular is a unified machine learning development platform designed for building, compiling, and deploying high-performance neural network models. It provides a comprehensive execution engine that supports both local and production-grade inference, enabling developers to manage the entire model lifecycle from initial architecture definition to scalable, containerized service deployment.

The platform distinguishes itself through a hardware-agnostic runtime that abstracts diverse silicon architectures, allowing models to execute efficiently across varied compute environments. It includes a spec
- [j3ssie/osmedeus](https://awesome-repositories.com/repository/j3ssie-osmedeus.md) (6,425 ⭐) — Osmedeus is a security workflow orchestration engine that coordinates AI agents, shell commands, and scanning tools through declarative YAML pipelines. It functions as a distributed security scanner, a declarative workflow automator, and an AI agent framework for security, enabling automated multi-step security analysis with conditional branching, parallel execution, and distributed workers.

The engine distinguishes itself through a hybrid runner model that executes workflow steps on the local host, inside Docker containers, or over SSH to remote machines, selected per step or module. It supp
- [artesaos/defender](https://awesome-repositories.com/repository/artesaos-defender.md) (439 ⭐) — Roles & Permissions for Laravel
- [yusufkaraaslan/skill_seekers](https://awesome-repositories.com/repository/yusufkaraaslan-skill-seekers.md) (9,641 ⭐) — Skill Seekers is a toolset for generating large language model knowledge bases, featuring a multi-source content scraper and a dedicated RAG data pipeline. It extracts technical data from documentation, code, and video to create structured assets and configuration files for AI-powered IDE extensions.

The project distinguishes itself through the ability to transform raw data into polished tutorials and specialized skills for AI plugin marketplaces. It utilizes abstract syntax tree parsing and optical character recognition to analyze GitHub repositories, PDFs, and video frames, converting these
- [linkerd/linkerd](https://awesome-repositories.com/repository/linkerd-linkerd.md) (5,316 ⭐) — Linkerd is a Kubernetes service mesh that manages network traffic between microservices. It functions as a transparent networking proxy, layer 7 traffic manager, and mutual TLS security layer, providing observability and reliability for service-to-service communication without requiring changes to application code.

The project distinguishes itself through a sidecar-proxy architecture that intercepts TCP and application-level traffic to provide automatic mutual TLS encryption and identity verification. It enables cross-cluster service networking to link multiple clusters and implements cloud-n
- [joe-b-security/awesome-prompt-injection](https://awesome-repositories.com/repository/joe-b-security-awesome-prompt-injection.md) (525 ⭐) — Learn about a type of vulnerability that specifically targets machine learning models
- [rightnow-ai/openfang](https://awesome-repositories.com/repository/rightnow-ai-openfang.md) (17,834 ⭐) — OpenFang is an operating system for LLM agents designed to orchestrate autonomous agents with built-in task scheduling, tool sandboxing, and multi-model routing. It provides a secure AI execution environment that integrates prompt injection scanning, cryptographic audit trails, and resource metering to ensure controlled processing.

The platform distinguishes itself through a comprehensive security architecture, featuring fuel-metered tool sandboxing and an immutable activity audit trail based on cryptographic hash-chains. It implements high-assurance identity verification via signed manifests
- [google/inject.dart](https://awesome-repositories.com/repository/google-inject-dart.md) (861 ⭐) — Compile-time dependency injection for Dart and Flutter
- [swisskyrepo/payloadsallthethings](https://awesome-repositories.com/repository/swisskyrepo-payloadsallthethings.md) (78,434 ⭐) — This project is a comprehensive, community-sourced knowledge base designed for security professionals and researchers. It functions as a centralized repository of offensive security techniques, providing a structured collection of exploit payloads, attack vectors, and methodologies for conducting vulnerability assessments and penetration testing.

The repository distinguishes itself through a cross-platform payload taxonomy that categorizes exploitation methods by vulnerability type and target environment, enabling rapid lookup during security assessments. It maintains high standards of data i
- [linkerd/linkerd2](https://awesome-repositories.com/repository/linkerd-linkerd2.md) (11,424 ⭐) — This project is a service mesh platform designed to manage, secure, and observe service-to-service communication within Kubernetes clusters. It functions as a control plane that orchestrates transparent sidecar proxies, which intercept and manage network traffic to provide reliable connectivity for microservices. By automating the injection of these proxies, the platform ensures that infrastructure-level policies are applied consistently across all workloads without requiring manual configuration changes.

The platform distinguishes itself through its focus on zero-trust security and cross-clu
- [simeononsecurity/windows-defender-application-control-hardening](https://awesome-repositories.com/repository/simeononsecurity-windows-defender-application-control-hardening.md) (49 ⭐) — Harden Windows with Windows Defender Application Control (WDAC)
- [promptfoo/promptfoo](https://awesome-repositories.com/repository/promptfoo-promptfoo.md) (10,529 ⭐) — 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
- [modelcontextprotocol/servers](https://awesome-repositories.com/repository/modelcontextprotocol-servers.md) (87,320 ⭐) — The Model Context Protocol is a standardized communication framework designed to connect language models to external data sources, functional tools, and interactive user interfaces. It provides a vendor-neutral interface layer that enables AI hosts to discover and execute capabilities across heterogeneous service environments, using a JSON-RPC based messaging standard to facilitate bidirectional communication between clients and servers.

The protocol distinguishes itself through a robust capability-based handshake that negotiates feature sets during session initialization, ensuring compatibil
- [modelcontextprotocol/typescript-sdk](https://awesome-repositories.com/repository/modelcontextprotocol-typescript-sdk.md) (12,674 ⭐) — This project provides a TypeScript software development kit for the Model Context Protocol, a standard designed to facilitate bidirectional communication between AI applications and external data sources or tools. It serves as a foundational framework for building both clients and servers, enabling language models to interact with external systems through a unified, decoupled interface.

The SDK distinguishes itself by implementing a transport-agnostic connection layer that supports both local standard input-output streams and remote HTTP endpoints. It utilizes a JSON-RPC message bus to manage
- [giskard-ai/giskard-oss](https://awesome-repositories.com/repository/giskard-ai-giskard-oss.md) (5,467 ⭐) — Giskard is an AI quality assurance suite and evaluation framework designed to measure the performance, bias, and security risks of large language models and AI agents. It functions as a vulnerability scanner to detect security flaws and performance regressions.

The project provides automated red-teaming and adversarial testing workflows. These tools generate prompt-injection probes and adversarial attacks based on system descriptions to identify security gaps and vulnerabilities.

The platform covers AI agent auditing and RAG quality validation, using knowledge-base grounding and synthetic da