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HoundDog.ai Powers Privacy-by-Design in Replit's AI App Generation Platform

Implementing Data Security and Privacy Controls at the Code Level

News provided by

HoundDog.ai

Nov 20, 2025, 10:30 ET

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Integration brings 'privacy by design' to AI app generation, giving Replit creators instant visibility into sensitive data flows.

SAN FRANCISCO, Nov. 20, 2025 /PRNewswire/ -- HoundDog.ai today announced that Replit has integrated the company's AI-powered code scanner to embed privacy into its app-generation workflow.

HoundDog.ai  is building a privacy-focused code scanner that empowers organizations to detect sensitive data exposures early in development. Replit is the AI app-generation platform used by more than 45+ million creators worldwide. Replit, known for generating full-stack, production-ready applications with minimal technical input, is an innovator in making AI development accessible and safe for everyone.

After integrating with Semgrep earlier this year to detect security vulnerabilities such as SQL injection risks and outdated dependencies, Replit is now taking the next step by scanning for privacy risks from the very beginning of app creation with HoundDog.ai.

With the integration, Replit's users can automatically identify third-party and AI integrations embedded in generated code. Also, they can trace sensitive data flows across logs, files, local storage, third party SDKs and AI connectors. Finally, they can remediate identified privacy leaks with a single click. The process uses the same AI agent Replit users already rely on to fix security vulnerabilities, making privacy scanning frictionless.

"Many app creators struggle to understand where sensitive data goes once their code is generated. Our integration with Replit gives users instant visibility and automated privacy controls without technical burden," said Amjad Afanah, CEO and co-founder of HoundDog.ai.

"AI lowers the barrier to software creation, but with that comes new responsibility. By integrating HoundDog.ai, we're making sure privacy isn't an afterthought; it's built in from the very start. Every creator on Replit should have the tools to understand privacy and security for their AI-generated apps," shared Jeff Burke, Head of Partnerships at Replit.

AI Code Generation in a World of Sensitive Data
An increasing number of AI-generated applications now handle sensitive data such as Personally Identifiable Information (PII) and Protected Health Information (PHI). Many creators, including doctors, financial analysts and legal professionals may not initially think about compliance with GDPR, HIPAA or U.S. privacy frameworks. For example, Dr. Fahim Hussain at Northern Health used Replit to build a healthcare app in just a few days, demonstrating both the power and responsibility of AI-driven app creation.

As these apps gain real users, compliance and data protection become essential. Exposing sensitive data in plaintext within logs or files, or sharing it with third parties beyond established data processing agreements, can quickly lead to privacy issues and require remediation. By embedding HoundDog.ai's privacy scanner directly into the app generation process, Replit users can now identify risks proactively and start to build privacy compliance into their workflow from day one.

Raising the Bar for Trust and Transparency
With the HoundDog.ai integration, privacy becomes a core pillar of Replit's platform alongside security. Beyond compliance, this initiative reinforces user trust.

From Code Generation to Privacy Assurance
"Privacy can never be an afterthought. By integrating HoundDog.ai into Replit's workflow, we are helping every creator identify and address privacy issues from the outset," said Amjad Masad, CEO and cofounder of Replit.

The first phase of this integration focuses on detecting and remediating sensitive data leaks. These can be plaintext exposures of SSNs, passwords or other PII in logs, prompts or files. In future releases, Replit plans to provide live data flow maps that feed directly into Records of Processing Activities (RoPA), Privacy Impact Assessments (PIA) and other documentation required under privacy frameworks.

For non-technical creators generating apps through AI, these capabilities will assist with privacy compliance. As Replit continues to scale into markets where hundreds of developers contribute across thousands of repositories, HoundDog.ai's evidence-based data maps will help automate one of the most time-consuming aspects of privacy management. Manual tracking through spreadsheets or surveys can't scale. HoundDog.ai's capabilities will help Replit customers keep pace with development velocity and maintain compliance more reliably.

About HoundDog.ai
HoundDog.ai's Privacy by Design Code Scanner helps organizations proactively detect and prevent the overexposure of sensitive data in high risk mediums that could lead to privacy violations. The scanner embeds privacy into every stage of development, from IDE to CI. It discovers third party and AI integrations, including shadow AI, detects exposures of Personally Identifiable Information (PII), Protected Health Information (PHI), and authentication tokens in LLM prompts and other often overlooked surfaces such as logs, files, and third party SDKs, blocks unapproved data types before code reaches production, and generates audit ready Records of Processing Activities (RoPA) and Privacy Impact Assessments (PIA) prefilled with detected data flows and privacy risks. Learn more at www.hounddog.ai.

MEDIA CONTACT:
Cristin Connelly
Cathey.co for HoundDog.ai
[email protected]

SOURCE HoundDog.ai

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