Redaction & PII - API Reference

Analyze PDF for PII

POST /api/AnalyzePdf 1 token

Scans a PDF for PII patterns (SSN, email, credit card, phone, etc.) and returns match coordinates without modifying the document. Optionally accepts a template to auto-detect field locations via AI extraction. Use the results to preview what would be redacted.

Parameters

Name	Type	Required	Description
`pdf`	string	required	Base64-encoded PDF
`patterns`	array	optional	PII pattern names to detect: ssn, email, credit_card, phone_us, date, currency, ip_address, etc.
`customPatterns`	array	optional	Custom regex patterns: [{regex, label, color}]
`templateId`	string	optional	UUID of a saved template — auto-detects field locations for redaction
`template`	object	optional	Inline template definition: {prebuiltModel, fields: [{fieldKey, label, type}]}
`redactFields`	array	optional	Template field keys to include (omit to detect all template fields)
`pages`	string	optional	Pages to analyze: "all" or "1-3,5" (default: `all`)
`padding`	number	optional	Padding around matches in points (default: `2`)

Request Example

JSON

{"pdf": "<base64-pdf>", "patterns": ["ssn", "email", "credit_card", "phone_us"], "pages": "all", "padding": 2}

Response Example

JSON

{"success": true, "totalMatches": 5, "pagesAnalyzed": 3, "matches": [{"page": 1, "label": "SSN", "value": "***-**-1234", "x": 72.5, "y": 680.3, "width": 85.2, "height": 12.0, "color": "#FF0000"}]}

Code Examples

curl -X POST "https://docbutterfly.com/api/AnalyzePdf" \
  -H "X-API-Key: df_your_api_key_here" \
  -H "Content-Type: application/json" \
  -d '{"pdf": "<base64-pdf>", "patterns": ["ssn", "email", "credit_card", "phone_us"], "pages": "all", "padding": 2}'

using var client = new HttpClient();
client.DefaultRequestHeaders.Add("X-API-Key", "df_your_api_key_here");

var json = @"{""pdf"": ""<base64-pdf>"", ""patterns"": [""ssn"", ""email"", ""credit_card"", ""phone_us""], ""pages"": ""all"", ""padding"": 2}";
var content = new StringContent(json, System.Text.Encoding.UTF8, "application/json");

var response = await client.PostAsync("https://docbutterfly.com/api/AnalyzePdf", content);
response.EnsureSuccessStatusCode();

var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);

import requests
import json

url = "https://docbutterfly.com/api/AnalyzePdf"
headers = {
    "X-API-Key": "df_your_api_key_here",
    "Content-Type": "application/json"
}
payload = json.loads('{"pdf": "<base64-pdf>", "patterns": ["ssn", "email", "credit_card", "phone_us"], "pages": "all", "padding": 2}')

response = requests.post(url, headers=headers, json=payload)
response.raise_for_status()

data = response.json()
print(json.dumps(data, indent=2))

┌─────────────────────────────────────────────┐
│  Power Automate - HTTP Action               │
├─────────────────────────────────────────────┤
│                                             │
│  Method:  POST                              │
│  URI:     https://docbutterfly.com/api/AnalyzePdf
│                                             │
│  Headers:                                   │
│    X-API-Key:    df_your_api_key_here       │
│    Content-Type: application/json           │
│                                             │
│  Body:                                      │
│    {
│      "pdf": "\u003Cbase64-pdf\u003E",
│      "patterns": [
│        "ssn",
│        "email",
│        "credit_card",
│        "phone_us"
│      ],
│      "pages": "all",
│      "padding": 2
│    }
│                                             │
└─────────────────────────────────────────────┘

Steps:
1. Add an HTTP action to your flow
2. Set Method to "POST"
3. Set URI to "https://docbutterfly.com/api/AnalyzePdf"
4. Add the headers shown above
5. Paste the Body JSON into the Body field
6. Replace placeholder values with dynamic content as needed

Try in Testbed

Redact PDF by Text

POST /api/RedactPdfText 2 tokens

Finds text strings or regex patterns in a PDF and draws opaque colored rectangles over each match. Optionally accepts a template to auto-detect field locations for redaction. Fast overlay-based redaction — use RedactPdfFlatten for guaranteed text removal.

Parameters

Name	Type	Required	Description
`pdf`	string	required	Base64-encoded PDF
`redactions`	array	optional	Array of redaction rules: [{text, regex, color, caseSensitive}]
`templateId`	string	optional	UUID of a saved template — auto-detects field locations for redaction
`template`	object	optional	Inline template definition: {prebuiltModel, fields: [{fieldKey, label, type}]}
`redactFields`	array	optional	Template field keys to redact (omit to redact all detected fields)
`pages`	string	optional	Pages to redact: "all" or "1-3,5" (default: `all`)
`padding`	number	optional	Padding around matches in points (default: `2`)
`returnBase64`	boolean	optional	Return base64 JSON or raw binary (default: `true`)

Request Example

JSON

{"pdf": "<base64-pdf>", "redactions": [{"text": "John Smith", "color": "#000000", "caseSensitive": false}, {"regex": "\\b\\d{3}-\\d{2}-\\d{4}\\b", "color": "#FF0000"}], "pages": "all", "returnBase64": true}

Response Example

PDF

{"pdf": "JVBERi0xLjcK...", "pageCount": 3, "totalRedactions": 7, "redactionsPerPage": {"1": 3, "2": 4}}

Code Examples

curl -X POST "https://docbutterfly.com/api/RedactPdfText" \
  -H "X-API-Key: df_your_api_key_here" \
  -H "Content-Type: application/json" \
  -d '{"pdf": "<base64-pdf>", "redactions": [{"text": "John Smith", "color": "#000000", "caseSensitive": false}, {"regex": "\\b\\d{3}-\\d{2}-\\d{4}\\b", "color": "#FF0000"}], "pages": "all", "returnBase64": true}'

using var client = new HttpClient();
client.DefaultRequestHeaders.Add("X-API-Key", "df_your_api_key_here");

var json = @"{""pdf"": ""<base64-pdf>"", ""redactions"": [{""text"": ""John Smith"", ""color"": ""#000000"", ""caseSensitive"": false}, {""regex"": ""\\b\\d{3}-\\d{2}-\\d{4}\\b"", ""color"": ""#FF0000""}], ""pages"": ""all"", ""returnBase64"": true}";
var content = new StringContent(json, System.Text.Encoding.UTF8, "application/json");

var response = await client.PostAsync("https://docbutterfly.com/api/RedactPdfText", content);
response.EnsureSuccessStatusCode();

// The response contains a base64-encoded file in the JSON body
var result = await response.Content.ReadAsStringAsync();
using var doc = System.Text.Json.JsonDocument.Parse(result);
var base64 = doc.RootElement.GetProperty("pdf").GetString();
var bytes = Convert.FromBase64String(base64!);
await File.WriteAllBytesAsync("output.pdf", bytes);

import requests
import json
import base64

url = "https://docbutterfly.com/api/RedactPdfText"
headers = {
    "X-API-Key": "df_your_api_key_here",
    "Content-Type": "application/json"
}
payload = json.loads('{"pdf": "<base64-pdf>", "redactions": [{"text": "John Smith", "color": "#000000", "caseSensitive": false}, {"regex": "\\b\\d{3}-\\d{2}-\\d{4}\\b", "color": "#FF0000"}], "pages": "all", "returnBase64": true}')

response = requests.post(url, headers=headers, json=payload)
response.raise_for_status()

# Decode the base64 PDF and save to file
data = response.json()
pdf_bytes = base64.b64decode(data["pdf"])
with open("output.pdf", "wb") as f:
    f.write(pdf_bytes)
print("Saved to output.pdf")

┌─────────────────────────────────────────────┐
│  Power Automate - HTTP Action               │
├─────────────────────────────────────────────┤
│                                             │
│  Method:  POST                              │
│  URI:     https://docbutterfly.com/api/RedactPdfText
│                                             │
│  Headers:                                   │
│    X-API-Key:    df_your_api_key_here       │
│    Content-Type: application/json           │
│                                             │
│  Body:                                      │
│    {
│      "pdf": "\u003Cbase64-pdf\u003E",
│      "redactions": [
│        {
│          "text": "John Smith",
│          "color": "#000000",
│          "caseSensitive": false
│        },
│        {
│          "regex": "\\b\\d{3}-\\d{2}-\\d{4}\\b",
│          "color": "#FF0000"
│        }
│      ],
│      "pages": "all",
│      "returnBase64": true
│    }
│                                             │
└─────────────────────────────────────────────┘

Steps:
1. Add an HTTP action to your flow
2. Set Method to "POST"
3. Set URI to "https://docbutterfly.com/api/RedactPdfText"
4. Add the headers shown above
5. Paste the Body JSON into the Body field
6. Replace placeholder values with dynamic content as needed

To save the output file:
7. Add a "Parse JSON" action on the HTTP response body
8. Use base64ToBinary(body('Parse_JSON')?['pdf']) to convert
9. Pass the result to a "Create file" action (SharePoint, OneDrive, etc.)

Try in Testbed

Redact PDF by Area

POST /api/RedactPdfArea 1 token

Draws opaque colored rectangles at specified coordinates on PDF pages. Use for targeted redaction of known regions.

Parameters

Name	Type	Required	Description
`pdf`	string	required	Base64-encoded PDF
`areas`	array	required	Array of areas: [{page, x, y, width, height, color}]
`returnBase64`	boolean	optional	Return base64 JSON or raw binary (default: `true`)

Request Example

JSON

{"pdf": "<base64-pdf>", "areas": [{"page": 1, "x": 100, "y": 200, "width": 150, "height": 20, "color": "#000000"}, {"page": 1, "x": 300, "y": 400, "width": 200, "height": 20, "color": "#000000"}], "returnBase64": true}

Response Example

PDF

{"pdf": "JVBERi0xLjcK...", "pageCount": 3, "areasApplied": 2}

Code Examples

curl -X POST "https://docbutterfly.com/api/RedactPdfArea" \
  -H "X-API-Key: df_your_api_key_here" \
  -H "Content-Type: application/json" \
  -d '{"pdf": "<base64-pdf>", "areas": [{"page": 1, "x": 100, "y": 200, "width": 150, "height": 20, "color": "#000000"}, {"page": 1, "x": 300, "y": 400, "width": 200, "height": 20, "color": "#000000"}], "returnBase64": true}'

using var client = new HttpClient();
client.DefaultRequestHeaders.Add("X-API-Key", "df_your_api_key_here");

var json = @"{""pdf"": ""<base64-pdf>"", ""areas"": [{""page"": 1, ""x"": 100, ""y"": 200, ""width"": 150, ""height"": 20, ""color"": ""#000000""}, {""page"": 1, ""x"": 300, ""y"": 400, ""width"": 200, ""height"": 20, ""color"": ""#000000""}], ""returnBase64"": true}";
var content = new StringContent(json, System.Text.Encoding.UTF8, "application/json");

var response = await client.PostAsync("https://docbutterfly.com/api/RedactPdfArea", content);
response.EnsureSuccessStatusCode();

// The response contains a base64-encoded file in the JSON body
var result = await response.Content.ReadAsStringAsync();
using var doc = System.Text.Json.JsonDocument.Parse(result);
var base64 = doc.RootElement.GetProperty("pdf").GetString();
var bytes = Convert.FromBase64String(base64!);
await File.WriteAllBytesAsync("output.pdf", bytes);

import requests
import json
import base64

url = "https://docbutterfly.com/api/RedactPdfArea"
headers = {
    "X-API-Key": "df_your_api_key_here",
    "Content-Type": "application/json"
}
payload = json.loads('{"pdf": "<base64-pdf>", "areas": [{"page": 1, "x": 100, "y": 200, "width": 150, "height": 20, "color": "#000000"}, {"page": 1, "x": 300, "y": 400, "width": 200, "height": 20, "color": "#000000"}], "returnBase64": true}')

response = requests.post(url, headers=headers, json=payload)
response.raise_for_status()

# Decode the base64 PDF and save to file
data = response.json()
pdf_bytes = base64.b64decode(data["pdf"])
with open("output.pdf", "wb") as f:
    f.write(pdf_bytes)
print("Saved to output.pdf")

┌─────────────────────────────────────────────┐
│  Power Automate - HTTP Action               │
├─────────────────────────────────────────────┤
│                                             │
│  Method:  POST                              │
│  URI:     https://docbutterfly.com/api/RedactPdfArea
│                                             │
│  Headers:                                   │
│    X-API-Key:    df_your_api_key_here       │
│    Content-Type: application/json           │
│                                             │
│  Body:                                      │
│    {
│      "pdf": "\u003Cbase64-pdf\u003E",
│      "areas": [
│        {
│          "page": 1,
│          "x": 100,
│          "y": 200,
│          "width": 150,
│          "height": 20,
│          "color": "#000000"
│        },
│        {
│          "page": 1,
│          "x": 300,
│          "y": 400,
│          "width": 200,
│          "height": 20,
│          "color": "#000000"
│        }
│      ],
│      "returnBase64": true
│    }
│                                             │
└─────────────────────────────────────────────┘

Steps:
1. Add an HTTP action to your flow
2. Set Method to "POST"
3. Set URI to "https://docbutterfly.com/api/RedactPdfArea"
4. Add the headers shown above
5. Paste the Body JSON into the Body field
6. Replace placeholder values with dynamic content as needed

To save the output file:
7. Add a "Parse JSON" action on the HTTP response body
8. Use base64ToBinary(body('Parse_JSON')?['pdf']) to convert
9. Pass the result to a "Create file" action (SharePoint, OneDrive, etc.)

Try in Testbed

Redact PDF (Secure Flatten)

POST /api/RedactPdfFlatten 3 tokens

Securely redacts a PDF by rasterizing each page as an image, compositing black rectangles over redaction areas, and reassembling as a new PDF. Guarantees text is permanently removed — not just covered. Supports text/regex search, coordinate-based areas, and template-based AI field detection.

At least one of 'redactions' or 'areas' must be provided. Higher DPI produces better quality but increases processing time and file size.

Parameters

Name	Type	Required	Description
`pdf`	string	required	Base64-encoded PDF
`redactions`	array	optional	Text/regex redactions: [{text, regex}]
`areas`	array	optional	Area redactions: [{page, x, y, width, height}]
`templateId`	string	optional	UUID of a saved template — auto-detects field locations for redaction
`template`	object	optional	Inline template definition: {prebuiltModel, fields: [{fieldKey, label, type}]}
`redactFields`	array	optional	Template field keys to redact (omit to redact all detected fields)
`pages`	string	optional	Pages to process: "all" or "1-3,5" (default: `all`)
`dpi`	number	optional	Render resolution (higher = better quality, slower) (default: `150`)
`color`	string	optional	Redaction rectangle color (default: `#000000`)
`returnBase64`	boolean	optional	Return base64 JSON or raw binary (default: `true`)

Request Example

JSON

{"pdf": "<base64-pdf>", "redactions": [{"text": "John Smith"}, {"regex": "\\d{3}-\\d{2}-\\d{4}"}], "areas": [{"page": 1, "x": 100, "y": 200, "width": 150, "height": 20}], "dpi": 150, "returnBase64": true}

Response Example

PDF

{"pdf": "JVBERi0xLjcK...", "pageCount": 3, "textRedactions": 5, "areaRedactions": 1}

Code Examples

curl -X POST "https://docbutterfly.com/api/RedactPdfFlatten" \
  -H "X-API-Key: df_your_api_key_here" \
  -H "Content-Type: application/json" \
  -d '{"pdf": "<base64-pdf>", "redactions": [{"text": "John Smith"}, {"regex": "\\d{3}-\\d{2}-\\d{4}"}], "areas": [{"page": 1, "x": 100, "y": 200, "width": 150, "height": 20}], "dpi": 150, "returnBase64": true}'

using var client = new HttpClient();
client.DefaultRequestHeaders.Add("X-API-Key", "df_your_api_key_here");

var json = @"{""pdf"": ""<base64-pdf>"", ""redactions"": [{""text"": ""John Smith""}, {""regex"": ""\\d{3}-\\d{2}-\\d{4}""}], ""areas"": [{""page"": 1, ""x"": 100, ""y"": 200, ""width"": 150, ""height"": 20}], ""dpi"": 150, ""returnBase64"": true}";
var content = new StringContent(json, System.Text.Encoding.UTF8, "application/json");

var response = await client.PostAsync("https://docbutterfly.com/api/RedactPdfFlatten", content);
response.EnsureSuccessStatusCode();

// The response contains a base64-encoded file in the JSON body
var result = await response.Content.ReadAsStringAsync();
using var doc = System.Text.Json.JsonDocument.Parse(result);
var base64 = doc.RootElement.GetProperty("pdf").GetString();
var bytes = Convert.FromBase64String(base64!);
await File.WriteAllBytesAsync("output.pdf", bytes);

import requests
import json
import base64

url = "https://docbutterfly.com/api/RedactPdfFlatten"
headers = {
    "X-API-Key": "df_your_api_key_here",
    "Content-Type": "application/json"
}
payload = json.loads('{"pdf": "<base64-pdf>", "redactions": [{"text": "John Smith"}, {"regex": "\\d{3}-\\d{2}-\\d{4}"}], "areas": [{"page": 1, "x": 100, "y": 200, "width": 150, "height": 20}], "dpi": 150, "returnBase64": true}')

response = requests.post(url, headers=headers, json=payload)
response.raise_for_status()

# Decode the base64 PDF and save to file
data = response.json()
pdf_bytes = base64.b64decode(data["pdf"])
with open("output.pdf", "wb") as f:
    f.write(pdf_bytes)
print("Saved to output.pdf")

┌─────────────────────────────────────────────┐
│  Power Automate - HTTP Action               │
├─────────────────────────────────────────────┤
│                                             │
│  Method:  POST                              │
│  URI:     https://docbutterfly.com/api/RedactPdfFlatten
│                                             │
│  Headers:                                   │
│    X-API-Key:    df_your_api_key_here       │
│    Content-Type: application/json           │
│                                             │
│  Body:                                      │
│    {
│      "pdf": "\u003Cbase64-pdf\u003E",
│      "redactions": [
│        {
│          "text": "John Smith"
│        },
│        {
│          "regex": "\\d{3}-\\d{2}-\\d{4}"
│        }
│      ],
│      "areas": [
│        {
│          "page": 1,
│          "x": 100,
│          "y": 200,
│          "width": 150,
│          "height": 20
│        }
│      ],
│      "dpi": 150,
│      "returnBase64": true
│    }
│                                             │
└─────────────────────────────────────────────┘

Steps:
1. Add an HTTP action to your flow
2. Set Method to "POST"
3. Set URI to "https://docbutterfly.com/api/RedactPdfFlatten"
4. Add the headers shown above
5. Paste the Body JSON into the Body field
6. Replace placeholder values with dynamic content as needed

To save the output file:
7. Add a "Parse JSON" action on the HTTP response body
8. Use base64ToBinary(body('Parse_JSON')?['pdf']) to convert
9. Pass the result to a "Create file" action (SharePoint, OneDrive, etc.)

Try in Testbed