Shift-Left Sensitive Data Protection
Prevent PII Leaks from the Source
Weeks lost chasing sensitive data across application logs?
Not anymore. HoundDog.ai flips the model by analyzing code early to catch unintentional developer mistakes that lead to the overlogging and oversharing of sensitive data, before it ever reaches production.
Eliminate the chaos of reactive cleanups
Enforce privacy-by-design from day one
Operationalize Zero Trust through proactive data minimization
Stay compliant with GDPR, CCPA, HIPAA, PCI, FedRAMP, and other regulations
Third-party risk management starts with visibility
from simple_salesforce
import Salesforce
from hubspot
import HubSpot
from amplitude
import Amplitude, BaseEvent
Uncover all third-party and shadow integrations introduced by engineering teams, sometimes without the knowledge or approval of privacy teams
from datadog
import DogStatsd
import sentry_sdk
import analytics
Track sensitive data across code - no matter how deep it’s buried
Detect developer (or AI-generated) mistakes that leak sensitive data into logs, files, local storage, and other risky areas.
Logs
Files
Local Storage
Cookies
JSON Web Tokens
Enforce privacy rules and stop risky code before it reaches production.
Redefining software development with built-in privacy and data control
Proactive Third-Party Risk Management and Shadow IT Discovery
Disadvantages of Current Approaches:
Most platforms rely on identity providers or network traffic to detect third-party integrations, which only reveals tools that have already been authorized or are actively used.
These methods miss SDKs, open-source packages, and homegrown integrations embedded directly in code, leaving security teams blind to Shadow IT.
Advantages of HoundDog.ai's Approach:
HoundDog.ai discovers third-party SDKs and APIs directly in the codebase before they are deployed or granted access to data.
This early detection gives security and privacy teams full visibility into both sanctioned and unsanctioned third-party integrations across the development lifecycle.
Shadow integrations are surfaced as part of the CI workflow, making it easy to block risky code before it leads to compliance or security issues.
Proactive Third-Party Risk Management and Shadow IT Discovery
Disadvantages of Current Approaches:
Most platforms rely on identity providers or network traffic to detect third-party integrations, which only reveals tools that have already been authorized or are actively used.
These methods miss SDKs, open-source packages, and homegrown integrations embedded directly in code, leaving security teams blind to Shadow IT.
Advantages of HoundDog.ai's Approach:
HoundDog.ai discovers third-party SDKs and APIs directly in the codebase before they are deployed or granted access to data.
This early detection gives security and privacy teams full visibility into both sanctioned and unsanctioned third-party integrations across the development lifecycle.
Shadow integrations are surfaced as part of the CI workflow, making it easy to block risky code before it leads to compliance or security issues.
Proactive Data Minimization and Leak Prevention
Disadvantages of Current Approaches:
DLP tools detect leaks only after the fact, with remediation taking weeks to clean logs, assess exposure, and patch code
They rely on pattern matching and often miss organization-specific data like internal IDs or proprietary fields
Without code-level visibility, these tools cannot trace how sensitive data entered a risky medium, making prevention difficultAdvantages of HoundDog.ai’s Approach:
HoundDog.ai detects sensitive data exposure across risky mediums caused by unintentional developer or AI-generated mistakes during development, before any data reaches them.
It enforces allowlists at the code level, blocking unapproved data types in PRs and CI workflows.
By tracing data through function calls and transformations, it uncovers risks that reactive tools miss.
This proactive, shift-left approach helps teams prevent leaks at the source rather than patching them later.Built for AppSec Teams and Loved by Developers
For Developers
Get detailed context on why issues were flagged through data flow traces that explain every transformation step, even when they span multiple files or functions
Receive suggested fixes directly in your PRs as actionable comments, making remediation quick and easyFor AppSec Teams
Expand AppSec coverage to detect unintentional developer or AI generated mistakes that expose sensitive data in risky mediums. These are issues that are difficult to identify and remediate in production, reducing the burden on your data security peers
Leverage the sensitive data map, which lists all sensitive data types processed within a code repository, to enhance risk scoring by factoring in the sensitivity of the data. Not all SQL injection vulnerabilities should be treated equally
Centralize visibility through integrations with leading ASPM platforms like Checkmarx, Brinqa, and others
Enabling PII Leak Detection & Data Mapping Across All Stages of Development
IDE PLUGINS. (VS Code, Cursor, IntelliJ, and Eclipse)
- Highlights PII leaks as code is being written
Managed Scans
- Offload scanning to HoundDog.ai with direct source control integrations
CI/CD Integrations
- Use HoundDog.ai's direct source code integrations to automatically push CI configurations and embed the scanner for pre-merge checks
DIY PII Detection Doesn’t Scale
Hardcoded RegEx rules break easily and are a nightmare to maintain. Most DIY efforts stall before they scale
HoundDog.ai: Purpose-Built for PII Detection & Data Mapping
Unparalleled Coverage and Accuracy
Built-in detection with extensive coverage across:
- Sensitive data elements (PII, PHI, PIFI, CHD)
- Risky data sinks (including hundreds of third-party integrations)
- Sanitization functions (flag only when data isn’t properly sanitized)
Endless Flexibility
- Finetune detection across data elements, sinks, and sanitization to fit your environment.
Ready to Scale
- Connect to GitHub, GitLab, or Bitbucket to scan code, block PRs, and leave actionable comments – automatically.
- Managed Scans: Offload scanning to HoundDog.ai for continuous, hands-off coverage
- CI Jobs: Push CI configs to selected repos using your self-hosted runners, with options for direct commits or approval-based PRs
AI-Ready
- AI-powered detection that plugs into any LLM running in your environment – boosting coverage across data elements, sinks, and sanitization, while minimizing manual tuning.
Realize Significant Cost Reduction and Increased Productivity
ROI for proactive sensitive data protection
Make Privacy-by-Design a Reality in Your SDLC
Shift Left on Privacy. Scan Code. Get Evidence-Based Data Maps. Prevent PII Leaks in Logs and Other Risky Mediums Early—Before Weeks of Remediation in Production.