How It Works

• Continuously detect and prevent the exposure of PII data in plaintext within logs, files, tokens, cookies, and third-party systems. These vulnerabilities are overlooked by SAST scanners due to their inability to identify code logic that handles sensitive data, and have been the root cause of significant data breaches, leading to the exposure of cleartext passwords, password hints, and PII data for millions of records. Here is a sample of the vulnerability types covered by HoundDog.ai.
  • CWE-201: Information Exposure Through Sent Data
  • CWE-209: Information Exposure Through an Error Message
  • CWE-312: Cleartext Storage of Sensitive Information
  • CWE-313: Cleartext Storage in a File or on Disk
  • CWE-315: Cleartext Storage of Sensitive Information in a Cookie
  • CWE-532: Insertion of Sensitive Information into Log File
  • CWE-539: Use of Persistent Cookies Containing Sensitive Information
• Apply a proactive “shift-left” approach to privacy compliance and third-party application data flow tracking
  • Continuously track and visualize the flow of sensitive data (e.g., PII, PIFI, and PHI). Generate Records of Processing Activities (RoPA) with a few clicks and keep pace with PII changes at the speed of development.
  • Receive proactive alerts to avoid surprises caused by product changes introducing new PII without proper reviews or by third-party integrations that violate accepted data processing agreements. Catch these issues in development to avoid dealing with the more expensive repercussions when discovered later in production.

Our scanner includes a comprehensive library of predefined definitions for sensitive data, covering most PII, PIFI, and PHI data. For more extensive coverage, you also have the option to enable AI validation. **Our previous AI workflow, which relied on OpenAI, has been discontinued as we are developing a new workflow using a lightweight, open-source LLM model. This model can be deployed within your cloud account or on your on-premises infrastructure. The AI workflow processes only the discovered tokens (e.g., class names, variables, functions, methods, etc.) to determine whether they potentially handle sensitive data. As a result, the actual source code is not shared with the LLM model during processing. The new AI workflow will be available in Q2 2025.