> ## Documentation Index
> Fetch the complete documentation index at: https://docs.yoid.me/llms.txt
> Use this file to discover all available pages before exploring further.

# Credential Revocation

> Revoke credentials that are no longer valid.

## Overview

Credentials can be revoked when they are no longer valid — a fraudulent completion, an expired certification, or incorrect data that needs re-issuance.

When a credential is revoked, any future verification attempt against it will show `isValid: false`.

## When to Revoke

| Scenario                 | Example                                                           |
| ------------------------ | ----------------------------------------------------------------- |
| **Fraudulent issuance**  | A youth didn't actually complete the programme                    |
| **Credential expiry**    | Annual certifications that need renewal                           |
| **Data correction**      | Credential issued with incorrect attributes — revoke and re-issue |
| **Programme withdrawal** | Youth withdraws after a credential was issued                     |

## Endpoint

```
POST https://test.didxtech.com/me-creds/api/credentials/revoke
```

## Request

Revocation is a **batch operation** — you pass an array of credential IDs to revoke in a single call.

```bash theme={null}
curl -X POST "https://test.didxtech.com/me-creds/api/credentials/revoke" \
  -H "Authorization: Bearer <access_token>" \
  -H "Content-Type: application/json" \
  -d '{
    "ids": ["cred_abc123def456"]
  }'
```

### Request Body

| Field | Type      | Description                       |
| ----- | --------- | --------------------------------- |
| `ids` | string\[] | Array of credential IDs to revoke |

<Note>
  Revocation is permanent. To re-credential a youth after revoking, issue a new credential through the standard issuance workflow.
</Note>

## Impact on Verification

When a verifier checks a revoked credential, the `isValid` field will be `false`. The verifier's application should check `isValid` before trusting any presented data.