pip install PyJWT pandas import base64 import json import csv import sys import pandas as pd from pathlib import Path def decode_jws_payload(jws_token): """Decode the payload (second part) of a compact JWS.""" try: parts = jws_token.split('.') if len(parts) != 3: raise ValueError("Invalid compact JWS: expected 3 parts") # Decode base64url (add padding if needed) payload_b64 = parts[1] # Add padding for base64 decoding padding = '=' * (4 - (len(payload_b64) % 4)) payload_bytes = base64.urlsafe_b64decode(payload_b64 + padding) return json.loads(payload_bytes) except Exception as e: return "error": str(e), "raw_token": jws_token[:50]
Replace the row-building section with:
Extend the script to handle JWE (encrypted tokens) or add signature validation columns. Happy data wrangling. Have you built a similar converter for a different token format? Let me know in the comments. jws to csv converter
from pandas import json_normalize normalized = json_normalize(payload) rows.append(normalized.iloc[0].to_dict()) What About Invalid or Expired Signatures? A pure converter doesn’t need to verify the signature – it just decodes the payload. However, you may want to add a signature_valid column using a cryptographic library (e.g., cryptography or jwt with verification disabled first, then verified separately). pip install PyJWT pandas import base64 import json