HoundDog.ai today announced the general availability of its expanded privacy-by-design static code scanner, now purpose-built to address privacy risks in AI applications. Addressing the growing concerns around data leaks in AI workflows, the new release enables security and privacy teams to enforce guardrails on the types of sensitive data embedded in large language model (LLM) prompts or exposed in high-risk AI data sinks, such as logs and temporary files, all before any code is pushed to production and privacy violations occur. HoundDog.ai is a privacy-focused static code scanner designed to identify unintentional mistakes by developers or AI-generated code that could expose sensitive data such as personally identifiable information (PII), protected health information (PHI), cardholder data (CHD) and authentication tokens across risky mediums like logs, files, local storage and third-party integrations. Since its launch from stealth in May 2024, HoundDog.ai has been adopted by a g...
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