HoundDog.ai, a startup that helps developers ensure their code doesn't leak personally identifiable information, announced a $3,1 million seed round led by E14, Mozilla Ventures and several angel investors. Unlike other scanning tools, HoundDog actually analyzes the code a developer writes, using both traditional pattern matching and large language models (LLM) to find potential problems.
HoundDog was founded by Amjad Afanah who previously co-founded DCHQ, which It was later acquired by Gridstore which, to complicate matters, later changed its name to HyperGrid in 2016. Afanah also co-founded apisec.ai, which is still in operation, and worked at autonomous driving startup Cruise. The inspiration for HoundDog came during his time at data security startup Cyral and speaking to the privacy teams there, Afanah said.
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“Cuando estaba en Cyral, teníamos muchos datos”, dijo. “Lo que hace Cyral, como muchos otros en el espacio de la seguridad de datos, es centrarse en los sistemas de producción. Le ayudan a descubrir, clasificar sus datos estructurados y sus bases de datos, y luego le ayudan a aplicar controles de acceso. Pero los comentarios abrumadores que seguí escuchando de los equipos de seguridad y privacidad fueron: ‘Sabes, es demasiado reactivo y no se mantiene al día con los cambios en el código base’”.
HoundDog desplaza este proceso aún más río arriba. Si bien todavía se encuentra en el flujo de integración continua y aún no en el entorno de desarrollo (aunque eso puede suceder en el futuro próximo), la idea aquí es encontrar posibles fugas de datos antes de fusionar el código. Y lo más importante, HoundDog lo hace observando el código real, no el flujo de datos que produce. “Nuestra fuente de verdad es el código base”, dijo Afanah.
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Thanks to this, if a development team starts collecting Social Security numbers, for example, HoundDog would raise a flag and warn the team before the code was merged. I would also alert the security team as it could be a major and expensive issue.
The service currently supports code written in Java, C#, JavaScript, and TypeScript, as well as SQL, GraphQL, and OpenAPI/Swagger queries. Support for Python is imminent, the company says.
Afanah noted that a tool like this is becoming especially important in this era of AI-generated code, something also echoed by Replit CEO and HoundDog angel investor Amjad Masad.
“A medida que un número cada vez mayor de empresas recurren al código generado por IA para acelerar el desarrollo, incorporar las mejores prácticas de seguridad y garantizar la seguridad del código generado se vuelve esencial”, dijo Masad. “HoundDog.ai está liderando el camino en la protección de datos en las primeras etapas del ciclo de desarrollo, lo que lo convierte en un componente indispensable de cualquier flujo de trabajo de generación de código de IA. Ésta es la razón por la que elegí invertir en esta empresa”.
However, HoundDog itself also uses AI. It currently relies on OpenAI models to do this, but it is important to emphasize that this is optional. Users who worry about their code leaving their private repositories can also choose to rely solely on the company's more traditional code scanner.
An important part of HoundDog's value proposition is that it can reduce compliance costs for startups thanks to its automated reporting capabilities. The Service may automatically generate a Record of Processing Activities (RoPA). To do this, HoundDog uses generative AI to generate these reports and sends that data to OpenAI. The team emphasizes that only tokens that the service has discovered through its regular scanner are shared with OpenAI and that no actual source code is shared.
The company offers a limited free plan with paid plans starting at $200/month to scan up to two repositories.
