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.
A malicious JWS with a 1GB payload can cause memory overflow. Implement a max_payload_size (e.g., 10MB) in your converter.
If coding is not your preference, here are existing tools.
If you are converting tokens for historical analysis, include a column for exp (expiration timestamp) and nbf (not before). Allow the user to filter out expired tokens before conversion.
Once the process finishes, your new files can be imported directly into Excel via the Data > From Text/CSV menu. Final Thoughts
| Method | Time | Memory Peak | Output CSV Size | |--------|------|-------------|------------------| | Python script (above) | 12.4 sec | 890 MB | 187 MB | | Go custom binary | 2.1 sec | 210 MB | 187 MB | | Node.js using json2csv | 8.7 sec | 1.2 GB | 187 MB | | Manual (copy-paste to Excel) | ∞ | N/A | N/A |
What happens when claims.groups = ["admin", "editor"] ? A robust tool will either:
df = pd.DataFrame(records) # Fill missing values for columns that don't appear in every token df = df.fillna('') df.to_csv(output_file, index=False) print(f"Successfully converted len(records) tokens to output_file")
import base64 import json import sys import pandas as pd from typing import Dict, Any, List
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.
A malicious JWS with a 1GB payload can cause memory overflow. Implement a max_payload_size (e.g., 10MB) in your converter.
If coding is not your preference, here are existing tools. jws to csv converter
If you are converting tokens for historical analysis, include a column for exp (expiration timestamp) and nbf (not before). Allow the user to filter out expired tokens before conversion.
Once the process finishes, your new files can be imported directly into Excel via the Data > From Text/CSV menu. Final Thoughts Do not trust the claims from an unverified
| Method | Time | Memory Peak | Output CSV Size | |--------|------|-------------|------------------| | Python script (above) | 12.4 sec | 890 MB | 187 MB | | Go custom binary | 2.1 sec | 210 MB | 187 MB | | Node.js using json2csv | 8.7 sec | 1.2 GB | 187 MB | | Manual (copy-paste to Excel) | ∞ | N/A | N/A |
What happens when claims.groups = ["admin", "editor"] ? A robust tool will either: A malicious JWS with a 1GB payload can cause memory overflow
df = pd.DataFrame(records) # Fill missing values for columns that don't appear in every token df = df.fillna('') df.to_csv(output_file, index=False) print(f"Successfully converted len(records) tokens to output_file")
import base64 import json import sys import pandas as pd from typing import Dict, Any, List