News

HoundDog.ai Expands Privacy-Focused Code Scanner to Cover AI Applications

• By John K. Waters
• 10/01/2025

San Francisco-based software company HoundDog.ai has released a new version of its privacy-by-design code scanning platform, adding tools designed to detect and prevent data exposure in artificial intelligence (AI) applications.

The product update comes as companies integrating large language models (LLMs) into their workflows face heightened scrutiny over how sensitive data is handled, with regulators tightening oversight of data security and privacy practices.

The scanner is designed to identify risks in software code that could expose personally identifiable information (PII), protected health information (PHI), cardholder data, and authentication tokens. It monitors how data moves through code and highlights potential vulnerabilities across logs, temporary files, local storage, and third-party integrations.

The new release expands these capabilities to cover AI-specific risks, including data embedded in LLM prompts and outputs, as well as integrations with third-party software development kits (SDKs) and open-source frameworks. According to the company, the system automatically detects AI usage within applications, whether through direct integrations such as OpenAI and Anthropic or indirect connections using libraries like LangChain.

By enforcing allowlists, the tool can block the transfer of unapproved data types into AI models, which can help organizations comply with regulatory frameworks such as the EU’s General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and U.S. healthcare privacy laws. The system also produces audit-ready records of processing activities and privacy impact assessments.

HoundDog.ai emerged from stealth mode in May 2024. Since then, it has been adopted by enterprises in various sectors, including finance, healthcare, and technology. The company reports that it has scanned more than 20,000 code repositories across its customer base and prevented hundreds of data leaks before deployment.

The platform integrates into development workflows by operating from the first line of code, using extensions for major integrated development environments (IDEs) such as Visual Studio Code, JetBrains, and Eclipse. It also supports pre-merge checks within continuous integration (CI) pipelines.

HoundDog.ai claims that its customers have reduced their reliance on reactive data loss prevention tools, saving both engineering hours and compliance costs.

One early adopter, PioneerDev.ai, deployed the scanner while developing a healthcare enrollment platform that uses AI components. The system flagged risks related to sensitive data exposure in prompts, logs, and third-party integrations. By aligning scanner policies with its internal privacy standards, the firm was able to block unapproved data flows before launch and automate the creation of privacy assessments.

The company also announced the general availability of a cursor extension, which embeds privacy controls into AI-generated applications from the start of development. Both the command-line scanner and the cursor extension are available free for Python and JavaScript/TypeScript projects.

HoundDog.ai positions its approach as part of a broader trend toward embedding privacy controls earlier in the software development lifecycle, sometimes referred to as "shifting privacy left." This shift reflects growing industry demand for proactive monitoring, as organizations seek to prevent sensitive data exposure before software is deployed.