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7 dépôts

Awesome GitHub RepositoriesAdversarial Input Detection

Analyzes input data or internal model activations to flag samples likely crafted to deceive the model.

Distinct from Adversarial Input Generation: Distinct from Adversarial Input Generation: focuses on detecting adversarial inputs, not generating them.

Explore 7 awesome GitHub repositories matching security & cryptography · Adversarial Input Detection. Refine with filters or upvote what's useful.

Awesome Adversarial Input Detection GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • superagent-ai/superagentAvatar de superagent-ai

    superagent-ai/superagent

    6,631Voir sur GitHub↗

    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

    Detects and blocks prompt injection attacks, jailbreaks, and malicious instructions before they reach the language model.

    TypeScriptaianthropicguardrails
    Voir sur GitHub↗6,631
  • nvidia/nemo-guardrailsAvatar de NVIDIA

    NVIDIA/NeMo-Guardrails

    6,453Voir sur GitHub↗

    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

    Protects models from jailbreak attempts and malicious instructions using input inspection.

    Python
    Voir sur GitHub↗6,453
  • trusted-ai/adversarial-robustness-toolboxAvatar de Trusted-AI

    Trusted-AI/adversarial-robustness-toolbox

    6,056Voir sur GitHub↗

    The Adversarial Robustness Toolbox (ART) is an open-source library that provides a unified framework for evaluating, defending, and certifying machine learning models against adversarial threats. It wraps models from any framework behind a common estimator interface, enabling composable pipelines for attack generation, defense application, robustness certification, and privacy auditing across evasion, poisoning, and extraction threats. The library distinguishes itself by covering the full adversarial ML security lifecycle within a single toolkit. It supports gradient-based adversarial example

    Analyzes inputs and activations to flag samples crafted to deceive the model.

    Pythonadversarial-attacksadversarial-examplesadversarial-machine-learning
    Voir sur GitHub↗6,056
  • helicone/heliconeAvatar de Helicone

    Helicone/helicone

    5,830Voir sur GitHub↗

    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

    Analyzes user messages to identify jailbreak attempts and malicious instructions across multiple languages and blocks the request.

    TypeScript
    Voir sur GitHub↗5,830
  • microsoft/agent-governance-toolkitAvatar de microsoft

    microsoft/agent-governance-toolkit

    4,522Voir sur GitHub↗

    The agent-governance-toolkit is a framework for enforcing security policies, managing zero-trust identities, and sandboxing the execution of autonomous AI agents. It provides a governance layer designed to control the behavior of agents through the use of a security policy engine, cryptographic identity management, and a runtime execution sandbox. The project distinguishes itself through a multi-tier privilege ring system and a cryptographic identity mesh that secures communication between autonomous entities. It implements a decay-based trust scoring mechanism to track entity reliability and

    Uses a multi-vector evaluation system to detect and block prompt injection and jailbreak attempts.

    Python
    Voir sur GitHub↗4,522
  • vllm-project/semantic-routerAvatar de vllm-project

    vllm-project/semantic-router

    3,205Voir sur GitHub↗

    Blocks prompt injection and jailbreak attempts by inspecting incoming requests for malicious patterns.

    Goai-gatewaybert-classificationfine-tuning
    Voir sur GitHub↗3,205
  • protectai/llm-guardAvatar de protectai

    protectai/llm-guard

    2,561Voir sur GitHub↗

    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

    Detects and blocks prompt injection and jailbreak attempts to prevent malicious hijacking of model behavior.

    Pythonadversarial-machine-learningchatgptlarge-language-models
    Voir sur GitHub↗2,561
  1. Home
  2. Security & Cryptography
  3. Adversarial Robustness Testing
  4. Adversarial Input Generation
  5. Adversarial Input Detection

Explorer les sous-tags

  • Jailbreak DetectorsIdentifies and blocks attempts to circumvent AI safety measures using a binary classification model. **Distinct from Adversarial Input Detection:** Distinct from Adversarial Input Detection: specifically targets jailbreak attempts against LLM safety measures.
  • Prompt Injection Detectors1 sous-tagBlocks prompt injection and jailbreak attempts by inspecting incoming requests for malicious patterns. **Distinct from Adversarial Input Detection:** Distinct from Adversarial Input Detection: specifically targets prompt injection and jailbreak patterns in LLM requests.