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Cyber Security

PDF Signatures & DSIG Core

TL;DR

Yes, you can describe PDF certificate-based signatures using W3C’s Digital Signature (DSIG) Core, but it requires understanding how PDFs store signature information and mapping that to the DSIG model. It’s not a direct one-to-one translation, as PDFs have their own complexities. You’ll likely need a library or tool to extract the relevant data.

Understanding PDF Signatures

PDF signatures aren’t like simple digital signatures on documents. They are complex structures containing:

  • Signature Dictionary: Contains metadata about the signature (name, reason, date).
  • Content Stream: The actual signed data – often a hash of the document content.
  • Certificate Chain: The digital certificates used to verify the signer’s identity.
  • Digest Algorithm & Encryption Details: Information about how the signature was created (e.g., SHA256, RSA).

These components are embedded within the PDF file itself.

Mapping to DSIG Core

W3C’s DSIG Core provides a standard way to represent digital signatures. Here’s how you can map PDF signature data:

  1. Identify the Signed Data: Determine what part of the PDF was actually signed. This is usually specified in the signature dictionary.
  2. Extract the Digest: The content stream contains a hash (digest) of the signed data. You need to extract this value. Libraries like PyPDF2 or pdfminer.six can help with this.
    from PyPDF2 import PdfReader
    reader = PdfReader("your_pdf.pdf")
    signature_field = reader.get_fields()["/Sig1"] # Replace /Sig1 with the actual signature field name
    digest = signature_field.get('/Contents')[0].decode('utf-8')
    print(digest)
    
  3. Extract Certificate Information: Retrieve the certificate chain from the PDF. This will give you the signer’s public key, which is essential for verification.
    from PyPDF2 import PdfReader
    reader = PdfReader("your_pdf.pdf")
    signature_field = reader.get_fields()["/Sig1"] # Replace /Sig1 with the actual signature field name
    certificates = signature_field.get('/Cert')
    print(certificates)
    
  4. Determine the Digest Algorithm: Find out which hashing algorithm was used (e.g., SHA256). This is also in the signature dictionary.
    from PyPDF2 import PdfReader
    reader = PdfReader("your_pdf.pdf")
    signature_field = reader.get_fields()["/Sig1"] # Replace /Sig1 with the actual signature field name
    digest_algorithm = signature_field.get('/Filter')
    print(digest_algorithm)
    
  5. Create a DSIG Core Representation: Use a DSIG library (e.g., xmlsec in Python) to create a DSIG representation of the signature.

    This involves creating a Canonical XML form of the signed data, calculating the digest using the identified algorithm, and then signing it with the signer’s public key.

Tools & Libraries

  • PyPDF2: A Python library for reading and manipulating PDF files. Useful for extracting signature data.
  • pdfminer.six: Another Python library for PDF parsing, often better at handling complex PDFs.
  • xmlsec: A Python library for working with XML Digital Signatures (DSIG).

Important Considerations

  • PDF Complexity: PDFs can be very complex. Different PDF creators might implement signatures differently.
  • Incremental Updates: Some PDFs use incremental updates, which can affect signature verification.
  • PAdES Standards: If you need a more robust solution for long-term archiving of digital signatures, consider using the PAdES standards (PDF Advanced Electronic Signatures). These provide specific formats and requirements for PDF signatures.
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