ENCRYPT.md is a plain-text Markdown file you place in the root of any AI agent repository. It defines how the agent must handle data: what is critical (API keys, passwords), what is sensitive (PII), what encryption standards to use at rest and in transit, and what secrets must never be logged, hardcoded, committed, or transmitted in plaintext. It follows the same convention as AGENTS.md.

ENCRYPT.md — The AI Agent Data Protection Protocol

Q: How does ENCRYPT.md relate to KILLSWITCH.md?

KILLSWITCH.md stops your agent when something goes wrong. ENCRYPT.md prevents data exposure from happening in the first place. They are complementary — ENCRYPT.md is the preventive layer; KILLSWITCH.md is the reactive layer.

Q: What data classifications does it define?

Four tiers: Critical (API keys, passwords, private keys — never logged, encrypted at rest and in transit), Sensitive (PII like emails, phone numbers — masked in logs, encrypted in transit), Internal (business logic, configs — standard protection), Public (marketing content — no restrictions).

Q: What regulations does it address?

GDPR (encryption of personal data), SOC 2 Type II (encryption controls), ISO 27001 (information security management), EU AI Act 2026 (data protection for high-risk AI), and various US state privacy laws. ENCRYPT.md provides the auditable record each requires.

ENCRYPT.md

// AI Agent Data Protection Protocol

A plain-text file convention for defining data protection requirements in AI agent projects. Place it in your repo root and define exactly what your agent must encrypt, how secrets must be handled, and what can never be transmitted.

AGENTS.md tells it what to do.
ENCRYPT.md tells it what to protect.

ENCRYPT.md is a plain-text Markdown file you place in the root of any repository that contains an AI agent. It defines exactly what data your agent can and cannot access, how it must be handled, and what is forbidden.

The problem it solves

AI agents access credentials, transmit user data, log sensitive information — often without any explicit data handling rules. A misconfigured agent can log an API key, transmit PII to an external service, or cache credentials to disk. The damage is invisible until it isn't.

How it works

Drop ENCRYPT.md in your repo root and define: data classification (critical/sensitive/internal/public), encryption requirements at rest and in transit, secrets handling rules (never log, never hardcode, never commit), and forbidden transmission patterns. The agent reads it on startup. Your compliance team reads it in the audit.

The regulatory context

GDPR mandates encryption of personal data. SOC 2 Type II requires encryption controls. ISO 27001 mandates information security management. The EU AI Act (effective August 2026) requires data protection measures for high-risk AI systems. ENCRYPT.md is your auditable compliance record.

How to use it

Copy the template from GitHub and place it in your project root:

your-project/
├── AGENTS.md
├── KILLSWITCH.md
├── ENCRYPT.md ← add this
├── README.md
└── src/

What it replaces

Before ENCRYPT.md, data protection rules were scattered: embedded in environment variable docs, buried in security policies, or missing entirely. ENCRYPT.md makes protection boundaries version-controlled, auditable, and co-located with your code.

Who reads it

The AI agent reads it on startup. Your engineer reads it during code review. Your security team reads it during audits. Your regulator reads it if something goes wrong. One file serves all four audiences.

Frequently asked questions.

What is ENCRYPT.md?

A plain-text Markdown file defining how AI agents must handle data. It classifies data by sensitivity, mandates encryption standards, prohibits hardcoding secrets, and defines what can never be transmitted in plaintext. It gives your compliance team an auditable record of your agent's data protection rules.

How does ENCRYPT.md relate to KILLSWITCH.md?

KILLSWITCH.md stops your agent when something goes wrong. ENCRYPT.md prevents data exposure from happening in the first place. They are complementary — ENCRYPT.md is the preventive layer; KILLSWITCH.md is the reactive layer.

What data classifications does it define?

Four tiers: Critical (API keys, passwords, private keys — never logged, encrypted at rest and in transit), Sensitive (PII like emails, phone numbers — masked in logs, encrypted in transit), Internal (business logic, configs — standard protection), Public (marketing content — no restrictions).

What regulations does it address?

GDPR (encryption of personal data), SOC 2 Type II (encryption controls), ISO 27001 (information security management), EU AI Act 2026 (data protection for high-risk AI), and various US state privacy laws. ENCRYPT.md provides the auditable record each requires.

Does it work with secret managers like AWS Secrets Manager?

Yes. ENCRYPT.md defines the policy; secret managers implement it. The file specifies that secrets must come from environment variables or a secrets manager — never hardcoded. AWS Secrets Manager, HashiCorp Vault, and similar tools are the approved implementation.

What happens if an agent detects a secret in its output?

ENCRYPT.md defines an `on_secret_detected_in_output` handler: redact the value, replace with [REDACTED], log the event, and notify the security contact. Regex patterns for common secret formats (OpenAI keys, AWS access keys, GitHub tokens, private keys) are built into the spec.

Own the standard.
Own encrypt.md

This domain is available for acquisition. It is the canonical home of the ENCRYPT.md specification — the data protection layer of the AI agent safety stack, directly relevant to GDPR, SOC 2, ISO 27001, and EU AI Act compliance.

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