HAR to CSV (2026): Export Network Logs to Excel/Sheets + Remove Cookies Safely

HAR (HTTP Archive) files contain detailed network request data from your browser. Converting HAR to CSV allows developers, analysts, and performance engineers to analyze network traffic, debug API issues, and optimize load times using familiar spreadsheet tools.

What is a HAR File?

HAR is a JSON format that records all HTTP requests and responses made by a web browser, including:

Request URLs and methods (GET, POST, etc.)
Headers (including cookies and auth tokens)
Response status codes and timings
Content size and MIME types
Performance metrics (DNS, SSL, wait time)

Common use cases:

Web performance analysis
API debugging and testing
Security audits
Load testing analysis
Client support and troubleshooting

How to Generate a HAR File

Chrome/Edge (Chromium)

Open DevTools (F12 or Cmd+Option+I)
Go to Network tab
Reload the page or perform actions
Right-click anywhere in the request list
Select "Save all as HAR with content"

Firefox

Open Developer Tools (F12)
Click Network tab
Load the page
Click the gear icon (⚙️) → "Save All As HAR"

Safari

Enable Develop menu: Preferences → Advanced → "Show Develop menu"
Develop → Show Web Inspector → Network
Click Export icon

Why Convert HAR to CSV?

While HAR files are comprehensive, they're difficult to analyze without specialized tools. CSV conversion makes network data accessible:

Task	HAR (JSON)	CSV (Excel/Sheets)
Filter slow requests	❌ Complex JSON parsing	✅ Sort by duration column
Find failed requests	❌ Manual searching	✅ Filter status != 200
Calculate total size	❌ Requires scripting	✅ SUM() formula
Share with team	⚠️ Requires dev knowledge	✅ Universal format
Create reports	❌ Complex	✅ Pivot tables, charts

What Data Gets Exported

A typical HAR to CSV conversion includes these columns:

Core Request Data

URL: Full request path
Method: GET, POST, PUT, DELETE, etc.
Status: HTTP response code (200, 404, 500...)
Status Text: OK, Not Found, Internal Server Error
Type: MIME type (image/png, application/json)

Size & Performance

Size: Response body size (bytes)
Transfer: Actual transferred (with compression)
Time: Total request duration (ms)
DNS: DNS lookup time
Connect: TCP connection time
SSL: TLS handshake time
Send: Request send time
Wait: Server processing time (TTFB)
Receive: Response download time

Headers (Optional)

Cookies: Request/response cookies (can be removed)
User-Agent: Browser identification
Content-Type: Response format
Cache-Control: Caching directives

Security: Removing Sensitive Data

⚠️ HAR files often contain sensitive information:

🔴 Session cookies (auth tokens)
🔴 API keys in headers or URLs
🔴 Personal data in POST bodies
🔴 Bearer tokens (OAuth credentials)

Safe Export Options

Our HAR to CSV Converter includes privacy controls:

Remove cookies: Strips Cookie and Set-Cookie headers
Redact Authorization: Removes Authorization headers
Hide POST data: Excludes request/response bodies
Sanitize URLs: Removes query parameters (e.g., ?api_key=...)

Manual sanitization (if needed):

Open HAR in text editor
Search and replace sensitive values
Remove "cookies" and "headers" arrays
Then convert to CSV

Analysis Use Cases

1. Find Performance Bottlenecks

Goal: Identify slowest requests

Convert HAR to CSV
Open in Excel/Sheets
Sort by Time column (descending)
Focus on top 10 slowest requests

What to look for:

High Wait time: Slow server processing → optimize backend
High Receive time: Large response → add compression
High DNS time: DNS issues → use DNS prefetch
High SSL time: Certificate issues → check SSL config

2. Debug Failed Requests

Goal: Find all 4xx and 5xx errors

Filter Status column
Show only values ≥ 400
Group by Status or URL

Common issues:

404: Missing resources (broken links, old cache)
403: CORS issues or auth failures
500/502/503: Server errors → check backend logs

3. Calculate Total Page Weight

In Google Sheets or Excel:

// Total transferred data
=SUM(E:E) / 1024 / 1024  → Result in MB

// Average request time
=AVERAGE(F:F)            → Result in ms

// Count of each resource type
=COUNTIF(D:D, "image/png")
=COUNTIF(D:D, "application/javascript")

4. API Endpoint Analysis

Goal: Analyze API performance

Filter URLs containing /api/
Group by endpoint (use =LEFT(A2, FIND("?", A2)-1) to remove query params)
Calculate average time per endpoint
Create chart showing slowest endpoints

Excel Analysis Tips

Pivot Table for Resource Summary

Select your CSV data
Insert → PivotTable
Rows: Type (MIME type)
Values: Count of URL, Sum of Size, Average of Time

Result: Summary showing count, total size, and average time per resource type (JS, CSS, images, etc.)

Conditional Formatting

Highlight slow requests: Format cells → Color scale (red for >2000ms)
Highlight errors: Formula: =C2>=400 → Red fill
Highlight large files: Formula: =E2>1000000 → Orange fill

Limitations of HAR Files

What HAR Doesn't Capture

Client-side rendering: JavaScript execution time
User interactions: Clicks, scrolls, form fills
Memory usage: RAM consumption
Browser caching logic: Why resources were/weren't cached

Complement HAR With:

Lighthouse reports: Performance scores
Chrome Performance tab: JS profiling
Real User Monitoring (RUM): Actual user experience

Advanced: Scripting HAR Analysis

Python Script for Custom Analysis

import json
import csv

# Load HAR file
with open('network.har', 'r') as f:
    har = json.load(f)

# Extract entries
entries = har['log']['entries']

# Convert to CSV
with open('output.csv', 'w', newline='') as f:
    writer = csv.writer(f)
    writer.writerow(['URL', 'Status', 'Time', 'Size'])
    
    for entry in entries:
        url = entry['request']['url']
        status = entry['response']['status']
        time = entry['time']
        size = entry['response']['bodySize']
        writer.writerow([url, status, time, size])

print("Converted successfully!")

JavaScript/Node.js Example

const fs = require('fs');
const har = JSON.parse(fs.readFileSync('network.har', 'utf8'));

const rows = har.log.entries.map(entry => ({
  url: entry.request.url,
  method: entry.request.method,
  status: entry.response.status,
  time: entry.time,
  size: entry.response.bodySize
}));

// Convert to CSV
const csv = [
  'URL,Method,Status,Time,Size',
  ...rows.map(r => `"${r.url}",${r.method},${r.status},${r.time},${r.size}`)
].join('\n');

fs.writeFileSync('output.csv', csv);

FAQ: HAR to CSV Conversion

Can I edit a HAR file before converting?

Yes! HAR is plain JSON—open in any text editor, remove sensitive data, then convert. Always sanitize production HAR files before sharing.

How large can HAR files get?

Complex web apps can generate 10-50MB HAR files (thousands of requests). Large HAR files may require scripting instead of online tools.

Does HAR include response bodies?

Only if you select "Save as HAR with content" in Chrome. Standard HAR includes headers and metadata but not full responses (to keep file size manageable).

Can I merge multiple HAR files?

Yes, using scripts. Extract the entries array from each HAR, combine them, then convert to CSV. Useful for comparing different sessions or tests.

What's the difference between "Size" and "Transfer"?

Size: Uncompressed response size. Transfer: Actual bytes sent (with gzip/brotli compression). Transfer is smaller if compression is enabled.

Related Tools

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VCF to CSV for Gmail (2026): Import Contacts - Another practical CSV conversion guide

CSV to JSON — Reverse conversion
XML to CSV — Other data formats

Conclusion

Converting HAR to CSV unlocks powerful network analysis capabilities using familiar spreadsheet tools. Whether debugging slow page loads, analyzing API performance, or auditing security headers, CSV export makes complex network data accessible to developers, analysts, and stakeholders. Always sanitize HAR files before sharing—remove cookies, auth tokens, and sensitive headers. Use our HAR to CSV Converter for instant, privacy-safe conversion with customizable column selection.