Showing 3 open source projects for "secrets"

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  • 1
    PasteGuard

    PasteGuard

    Masks sensitive data and secrets before they reach AI

    PasteGuard is an open-source privacy proxy that protects sensitive information like personal data and API secrets by detecting and masking them before they reach large language model APIs such as OpenAI or Anthropic Claude. It sits between an application and the LLM provider, automatically replacing names, emails, tokens, and other personally identifiable information (PII) with placeholders so that external services never see raw sensitive values, and then optionally unmasking them in the returned output. ...
    Downloads: 3 This Week
    Last Update:
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  • 2
    Superagent

    Superagent

    Superagent protects your AI applications

    ...It embeds real-time safety directly into AI workflows, helping teams secure models before threats cause damage. Superagent provides guardrails that block jailbreaks, prompt manipulation, and sensitive data exfiltration. It includes redaction tools to remove PII, PHI, and secrets automatically from text. The platform also scans code repositories to detect AI-specific attack vectors like repo poisoning. Superagent is designed for low-latency production environments and works with any major LLM provider. It enables teams to prove compliance with modern AI security and regulatory standards.
    Downloads: 1 This Week
    Last Update:
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  • 3
    LLM Guard

    LLM Guard

    The Security Toolkit for LLM Interactions

    ...It includes scanning mechanisms that detect malicious prompts, prompt injection attempts, toxic content, and other harmful inputs that could compromise AI systems. The toolkit also helps prevent sensitive information leaks by identifying secrets such as API keys or credentials before they are processed by the model. LLM Guard supports both input and output filtering pipelines, allowing developers to sanitize prompts and validate generated responses in real time. The library integrates easily with existing AI frameworks and can be deployed in production environments to enhance the security posture of LLM-based applications.
    Downloads: 0 This Week
    Last Update:
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