Prevent PII leaks and track third-party data flows.

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December 20, 2024

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HoundDog

Data leak prevention

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Prevent PII leaks and track third-party data flows.

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Overview

HoundDog.ai is a highly efficient AI-powered static code scanner designed to prevent Personal Identifiable Information (PII) leaks and uphold data processing agreements with third-party applications.

This innovative tool implements a proactive 'shift-left' strategy, ensuring data security and privacy compliance at the code level.HoundDog.ai's code scanner can continuously detect vulnerabilities that are often overlooked by SAST scanners, where sensitive information is exposed in plain text through avenues such as logs, files, tokens, cookies, or third-party systems.

Information exposed can include PII, PIFI, and PHI. It provides essential context and suggests remediation strategies, such as omitting sensitive data, applying masking or obfuscation, or using UUIDs instead of PII.Furthermore, HoundDog.ai's code scanner can track and visualize the flow of sensitive data within a digital ecosystem, making it easier for organizations to generate Records of Processing Activities (RoPA) and keep up with PII changes in the speed of development.

The tool will also alert users to anomalies, such as unreviewed product changes introducing new PII or third-party integrations that might violate accepted data processing agreements.HoundDog.ai is built for speed, with capabilities to scan over millions of lines of code quickly.

It is designed to seamlessly integrate within developer workflows, operating wherever it is needed, from CLI to CI/CD. The platform supports most CI pipelines, surfaces findings in security dashboards such as GitHub and GitLab, and sends actionable notifications through Slack and Jira.

HoundDog.ai is SOC-2 compliant, supports SSO, offers standardized audit logs for SIEM integration, and includes enterprise support.

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Initial release

November 8, 2024

Initial release of HoundDog.

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$100/year

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Yearly

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Data leak prevention HoundDog

Data leak prevention

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Pros and Cons

Pros

Prevents PII leaks

Upholds data processing agreements

Proactive 'shift-left' strategy

Ensures code level security

Address vulnerabilities SAST miss

Exposure detection (log, file, token)

Essential context provision

Remediation strategies suggestion

Sensitive data flow tracking

Visualization of sensitive data flow

Records of Processing Activities generation

Anomaly alerts

Speed; scans millions of lines

Integration with developer workflows

Works from CLI to CI/CD

Supports most CI pipelines

Accommodates GitHub and GitLab

Actionable notifications through Slack and Jira

SOC-2 compliance

Single Sign On Support

Standardized audit logs

SIEM integration

Enterprise support

Third-party data flow tracking

Avoids PII spread to systems

Plaintext exposure detection

Privacy compliance implementation at code level

Quick RoPA generation

Fast PII changes tracking

Product change alert

Data processing violation alert

High accuracy

Pre-defined sensitive data definitions

Scans over 10 million lines

Supports popular frameworks and technologies

Supports Java, C#, TypeScript, Javascript, Python

Supports OpenAPI, GraphQL

Supports Azure Pipelines, CircleCI

Supports Bitbucket, Jenkins

Data security at early stages

Automated privacy compliance

View 36 more pros

Cons

Doesn't support all programming languages

May generate false positives

Limited third-party system compatibility

No explicit mention of scalability

Detailed results could overwhelm users

Possible delays in anomaly alerts

Dependent on a continuous integration environment

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Q&A

What is the main purpose of HoundDog.ai?

HoundDog.ai is primarily designed to prevent Personal Identifiable Information (PII) leaks and uphold data processing agreements with third-party applications. It ensures data security and privacy compliance at the code level with its proactive 'shift-left' strategy.

How does HoundDog.ai prevent Personal Identifiable Information (PII) leaks?

HoundDog.ai employs an AI-powered static code scanner to detect vulnerabilities where PII may be exposed. These vulnerabilities could be overlooked by traditional SAST scanners and involve the exposure of sensitive data through logs, files, tokens, cookies, or third-party systems. HoundDog.ai is equipped with remediation strategies and can suggest measures such as omitting sensitive data, applying masking or obfuscation, or using UUIDs instead of PII.

What is the 'shift-left' strategy implemented by HoundDog.ai?

The 'shift-left' strategy implemented by HoundDog.ai intends to embed data security and privacy controls early in the code development, thereby catching and addressing issues early. This proactive measure aids in preventing PII leaks and ensuring privacy compliance, rather than retroactively dealing with these issues after they've occurred.

What vulnerabilities can HoundDog.ai detect that are often overlooked by SAST scanners?

HoundDog.ai can detect vulnerabilities that are often overlooked by SAST scanners. These vulnerabilities can lead to the exposure of sensitive information in plain text through different avenues such as logs, files, tokens, cookies, or third-party systems.

What sensitive information can HoundDog.ai protect?

HoundDog.ai's sensitive data protection extends to Personal Identifiable Information (PII), Personal Financial Information (PIFI), and Protected Health Information (PHI).

What remediation strategies does HoundDog.ai suggest?

The primary remediation strategies suggested by HoundDog.ai are omitting sensitive data, applying masking or obfuscation, and using UUIDs instead of PII. These strategies can be employed to address vulnerabilities identified and ensure data security.

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How does HoundDog.ai visualize the flow of sensitive data?

HoundDog.ai can track and visualize the flow of sensitive data in a digital ecosystem. This feature enables organizations to view and understand how their data moves within the system in a simplified manner. The flow visualization can assist in identifying potential vulnerabilities and areas where sensitive data might be exposed.

What are Records of Processing Activities (RoPA) and how does HoundDog.ai help in generating them?

Records of Processing Activities (RoPA) are records that outline the lifecycle of collected data and how it has been processed. HoundDog.ai aids organizations in generating RoPAs by tracking and visualizing the flow of data within a digital ecosystem. This makes it easier for organizations to know what PII changes are occurring at development speed. It facilitates comprehensive and proactive data governance.

Can HoundDog.ai alert users about anomalies in the data?

Yes, HoundDog.ai can alert users about anomalies in data flows. These can include unreviewed product changes introducing new PII or third-party integrations that might violate accepted data processing agreements.

How quickly can HoundDog.ai scan lines of code?

HoundDog.ai is built for speed and can scan millions of lines of code swiftly.

What workflows can HoundDog.ai easily integrate with?

HoundDog.ai is designed to seamlessly integrate within developer workflows and can operate where needed, from the command-line interface (CLI) to continuous integration/continuous delivery (CI/CD).

Which CI pipelines does HoundDog.ai support?

HoundDog.ai supports most CI pipelines, making it a versatile tool across various development environments.

What security dashboards are compatible with HoundDog.ai?

Security dashboards on platforms such as GitHub and GitLab are compatible with HoundDog.ai. It surfaces its findings on these dashboards to make the information readily accessible to developers and cybersecurity teams.

Is HoundDog.ai SOC-2 compliant?

Yes, HoundDog.ai is SOC-2 compliant, testifying to its adherence to high standards in data security.

Does HoundDog.ai support SSO?

Yes, HoundDog.ai supports Single Sign-On (SSO), providing greater ease and security for user logins.

How does HoundDog.ai standardize audit logs for SIEM integration?

HoundDog.ai offers standardized audit logs intended for SIEM integration. However, explicit details of the standardization process aren't specified.

Is HoundDog.ai suitable for enterprise use?

HoundDog.ai includes enterprise support, thus making it suitable for enterprise environments.

What are the data leak prevention features of HoundDog.ai?

HoundDog.ai's data leak prevention features come from its proactive approach in identifying potential PII leaks in the code-level. It employs continuous detection methods to identify vulnerabilities that may lead to PII exposure and suggests remediation strategies to address these shortcomings.

How does HoundDog.ai track third-party data flows?

HoundDog.ai's AI-powered code scanner not only detects PII leaks but also tracks third-party data flows. It provides alerts for anomalies including third-party integrations that might violate accepted data processing agreements. This enables a proactive approach in ensuring compliance and preventing potential leaks.

What privacy compliance measures does HoundDog.ai provide?

HoundDog.ai provides several privacy compliance measures, from helping generate Records of Processing Activities (RoPA) to sending alerts about product changes introducing new PII or third-party integrations that might violate data processing agreements.

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