Jws To Csv Converter Apr 2026

df = pd.DataFrame(rows) df.to_csv(output_file, index=False) print(f"✅ Converted len(rows) tokens to output_file") if == " main ": # Example usage jws_to_csv("tokens.txt", "output.csv", fields_of_interest=["sub", "exp", "tenant_id"]) Step 3: Handling nested claims Sometimes your JWS payload contains nested objects:

Opening a raw .log file full of base64url-encoded strings isn’t practical. But dropping that data into a CSV? Now you can sort, filter, and pivot.

for token in tokens: if not token.strip(): continue payload = decode_jws_payload(token) # If no fields specified, take all top-level keys if fields_of_interest is None: rows.append(payload) else: filtered = field: payload.get(field, None) for field in fields_of_interest rows.append(filtered) jws to csv converter

Once you have the CSV, the world opens up – pivot tables, duplicate detection, expiration audits, and even machine learning on claim patterns.

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. df = pd

eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjMiLCJyb2xlIjoidXNlciIsImV4cCI6MTczNTY4OTAwMH0.signature1 eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiI0NTYiLCJyb2xlIjoiYWRtaW4iLCJleHAiOjE3MzU2ODkwMDB9.signature2 python jws_to_csv.py tokens.txt output.csv --fields sub,role

To flatten these into CSV columns (e.g., user.id , permissions.0 ), you can use pandas.json_normalize() instead of the direct DataFrame constructor. for token in tokens: if not token

Do not trust the claims from an unverified JWS in a security context. For analysis, it’s fine. For access control, always verify the signature. Real-World Example Input ( tokens.txt ):

Replace the row-building section with:

If you work with JWT (JSON Web Tokens) or JWS (JSON Web Signatures) in logging, analytics, or batch processing, you’ve likely run into the same headache: how do you analyze hundreds or thousands of these tokens in a human-readable way?

def jws_to_csv(input_file, output_file, fields_of_interest=None): """ Convert a file of JWS tokens (one per line) to CSV. fields_of_interest: list of claim names to extract (e.g., ['sub', 'exp', 'role']) """ tokens = Path(input_file).read_text().splitlines() rows = []