HoundDog.ai, a company implementing data security and privacy controls at the code level, announced the completion of a $3.1 million seed funding round led by E14, Mozilla Ventures, ex/ante, and additional angel investors.
This funding announcement coincides with the general availability of the HoundDog.ai cloud platform, which helps organizations apply data security and privacy controls as developers write code. This proactive approach helps organizations stay ahead of potential threats and reduces the financial and operational costs of addressing these vulnerabilities after they are discovered in production.
HoundDog.ai provides an AI-powered code scanner designed to implement a proactive, shift-left strategy for the protection of sensitive data and for ensuring privacy compliance. And this scanner continuously detects vulnerabilities that SAST scanners overlook—vulnerabilities that expose sensitive data in plaintext across various mediums, such as logs, files, tokens, cookies, or through third-party systems.
HoundDog.ai also tracks and visualizes the flow of sensitive data in real-time, documenting processing activities. And HoundDog.ai can scan more than 3 million lines of code in less than 3 minutes. Plus, it alerts users when new data elements are introduced based on their sensitivity levels and facilitates the generation of Records of Processing Activities (RoPA) and other privacy-related reports with just a few clicks, thereby eliminating the manual and error-prone processes traditionally used for this task.
HoundDog.ai utilizes AI to magnify the platform’s coverage and accuracy. Generative AI is used to evaluate tokens for sensitive data handling, achieving higher precision rates. This complements the scanner’s pre-defined sensitive data definitions, which encompass personally identifiable information (PII), personally identifiable financial information (PIFI), and protected health information (PHI).
The HoundDog.ai cloud platform provides a consolidated view of vulnerabilities across all code repositories and automatically sends actionable security notifications in Jira and Slack. Before release, customers had integrated the scanner into their CI pipelines, which surfaced the security findings on security dashboards. And while this may continue to be the preferred model for many organizations that have standardized security scanning workflows in GitHub and GitLab, the cloud platform enables more intricate workflows that rely on ticketing systems for vulnerability tracking and, of course, supports privacy-related workflows.
HoundDog.ai also now offers alerts on new data elements and automatic generation of RoPA reports for GDPR compliance. Support for Python, TypeScript and JavaScript has been added, in addition to the existing support for Java, C#, and structured languages like SQL, GraphQL and OpenAPI.
KEY QUOTES:
“Most companies detect sensitive data leaks through logs, files or third-party systems when it’s too late, after damage has occurred. Additionally, documenting data flows for GDPR compliance proves to be a manual, error-prone process that often fails to accurately reflect the reality of constantly changing codebases. With HoundDog.ai, companies can take a proactive stance in ensuring their sensitive data is protected and eliminate costly, reactive and error-prone processes for privacy compliance.”
– Amjad Afanah, founder and CEO of HoundDog.ai
“Business models built around adding AI to existing products are hamstrung from the outset. We’re looking for the entrepreneurs and products that are using AI to unlock value in ways that go far beyond incremental improvements to existing offerings, and that’s what HoundDog.ai has done. Amjad and his team have incorporated AI to dramatically reduce privacy compliance costs and simplify the proactive detection of sensitive data exposure with an efficient, frictionless code scanner. They’re fulfilling a true need in a market ripe with growth potential.”
– Habib Haddad, managing director at E14 Fund
“As an increasing number of companies turn to AI-generated code to accelerate development, embedding security best practices and ensuring the security of the generated code becomes essential. HoundDog.ai is leading the way in securing PII data early in the development cycle, making it an indispensable component of any AI code generation workflow. This is the reason I chose to invest in this company.”
– Amjad Masad, CEO of Replit and an investor in the round
“Companies handling sensitive data need a code scanner that is both fast and integrates with existing security dashboards, such as the GitLab Vulnerability Report in our case. It needs to provide peace of mind by ensuring that sensitive data does not accidentally leak into logs, files, or third-party systems, even with high-frequency updates to the codebases. It’s this capability that drew us to HoundDog.ai, as no one else is presently offering this.”
– Bryan Kaplan, EVP, chief information and security officer at Juvare
“The Cacilian platform has helped hundreds of customers improve their security posture with its comprehensive penetration testing capabilities. We are excited to extend the coverage of our findings to include sensitive data leaks through logs, files and third-party systems, which can be extremely costly to address in production, via our integration with HoundDog.ai. HoundDog’s AI-powered scanner can be plugged into the CI pipeline for continuous — and not just point-in-time — detection, and can drastically simplify datamap generation for privacy compliance.”
– Chase Bowman, vice president of security testing and engineering at Prescient Security
