resk-mark embeds cryptographic watermarks in LLM outputs to prove AI provenance

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A new open-source Python library called resk-mark allows developers to embed invisible cryptographic watermarks directly into the token generation process of large language models. The watermark, tied to a secret key provided before generation, biases token sampling to encode a verifiable signature without altering the text's meaning or fluency. Once generated, the output can be verified against a corresponding public key to confirm its origin, even after copying, truncation, or light rewording. Resk Security released the tool under the Apache 2.0 license, making it freely auditable, and it is available via a simple pip install on PyPI. The library targets use cases such as SaaS AI platforms, enterprise chat systems, content moderation pipelines, and compliance audit trails amid growing regulatory pressure around AI-generated content.

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