Code-Based DSPM Traces Sensitive Data Exposure to Application Code
Summary
The article contrasts storage-scanning DSPM with code-based analysis that traces sensitive data through application code, identifies risks such as PII in logs, and suggests fixes without accessing production data stores.
Key points
- Traditional DSPM scans storage systems and connected platforms to locate sensitive data and assess permissions or exposure.
- Code-based DSPM examines application paths—including APIs, logging, queues, and AI integrations—to show how sensitive data moves and where it may be mishandled.
- Aikido describes its Data Exposure Audit as identifying PII, PHI, payment data, secrets, tokens, and AI-related data handling, with code evidence and remediation suggestions.
- An illustrative example traces billing details logged by a checkout controller to Datadog and recommends redacting sensitive fields before logging.
- Suggested code-level fixes include limiting API responses, checking tenant ownership, avoiding tokens in URLs, masking production data before staging, and removing customer data from LLM prompts.
- Aikido says its approach reads code rather than connecting to or downloading data from production datastores; this is a vendor claim, not an independently demonstrated finding in the article.
Article Details
- Topic
- Code-based Data Security Posture Management (DSPM) and Data Exposure Audits for tracing sensitive data flows and exposure risks in application code.