As "vibe coding" and AI-native development become standard practice, a new security blind spot has emerged: the AI instruction file. BigID, a leader in data security and AI governance, has announced support for Markdown (.md) file scanning and classification, making it the only Data Security Posture Management (DSPM) solution capable of securing the sensitive context embedded in the files that power modern AI agents and coding tools.
BigID now supports discovery and classification of Markdown (.md) files across cloud storage, code repositories, and developer workstations.
The update targets "AI instruction files" including Claude skills, Cursor rules, GitHub Copilot instructions, and MCP server configurations.
These files often contain plaintext sensitive data such as API structures, credentials, database schemas, and proprietary IP.
Traditional DLP and DSPM tools are generally unable to parse the narrative, unstructured nature of .md files.
BigID enables automated risk scoring and remediation (access restriction, quarantining) for these artifacts.
To make AI coding assistants and agents effective, developers frequently "front-load" instruction files with internal system context. Because these files are written in natural language Markdown, they are human-readable but have remained largely invisible to legacy security tools designed for structured databases.
The proliferation of vibe coding—where natural language is used to generate entire applications—has accelerated the volume of these files. A credential fragment or an API key embedded within a developer's narrative description often fails to trigger standard DLP patterns, leaving a massive layer of sensitive data exposed across enterprise repositories.
By adding Markdown support, BigID allows security teams to treat AI instruction files with the same rigor as traditional databases. The platform can now:
Discover: Map out where .md files reside across the entire enterprise ecosystem.
Classify: Identify PII, tokens, and internal access patterns hidden within the content.
Remediate: Integrate findings into existing security workflows to alert owners or restrict access.
"Markdown files are the new shadow data," said Dimitri Sirota, CEO of BigID. "They are everywhere in modern development environments, human-readable but invisible to security tools, and they contain more sensitive context than most security teams realize. BigID can now find, classify, and protect what is inside them."
As agentic AI becomes the default architecture for enterprise software, BigID’s move to close this "instructional" blind spot provides a critical layer of governance for organizations scaling their AI-native developer workflows.
About BigID
BigID is an AI-native platform built to secure data and govern AI across the enterprise. Recognized as a leader in Sensitive Data Discovery and DSPM, BigID helps organizations manage risk across cloud storage, SaaS applications, and code repositories. BigID has been named to the Forbes Cloud 100 and recognized as a World Economic Forum Technology Pioneer.
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