• crackpw This executes Nacho Barrientos Arias's PDFCrack tool by performing an OS call. The command allows the user to input a custom dictionary, perform a benchmark or continue from a saved state file. If no custom dictionary is input, this command will attempt to brute force a password using a modifiable charset text file in directory "ParanoiDF/pdfcrack". (http://pdfcrack.sourceforge.net/)
• decrypt This uses an OS call to Jay Berkenbilt's "QPDF" which decrypts the PDF document and outputs the decrypted file. This requires the user-password. (http://qpdf.sourceforge.net/)
• encrypt Encrypts an input PDF document with any password you specify. Uses 128-bit RC4 encryption.
• embedf Create a blank PDF document with an embedded file. This is for research purposes to show how files can be embedded in PDFs. This command imports Didier Stevens Make-pdf-embedded.py script as a module. (http://blog.didierstevens.com/programs/pdf-tools/)
• embedjs Similiar to "embedf", but embeds custom JavaScript file inside a new blank PDF document. If no custom JavaScript file is input, a default app.alert messagebox is embedded (http://blog.didierstevens.com/programs/pdf-tools/)
• extractJS This attempts to extract any embedded JavaScript in a PDF document. It does this by importing Blake Hartstein's Jsunpackn's "pdf.py" JavaScript tool as a module, then executing it on the file. (https://code.google.com/p/jsunpack-n/)
• redact Generate a list of words that will fit inside a redaction box in a PDF document. The words (with a custom sentence) can then be parsed in a grammar parser and a custom amount can be displayed depending on their score. This command requires a tutorial to use. Please read "redactTutorial.pdf" in directory "ParanoiDF/docs".
• removeDRM Remove DRM (editing, copying etc.) restrictions from PDF document and output to a new file. This does not need the owner-password and there is a possibility the document will lose some formatting. This command works by calling Kovid Goyal's Calibre's "ebook-convert" tool. (http://calibre-ebook.com/)

• Decodings: hexadecimal, octal, name objects
• More used filters
• References in objects and where an object is referenced
• Strings search (including streams)
• Physical structure (offsets)
• Logical tree structure
• Metadata
• Modifications between versions (changelog)
• Compressed objects (object streams)
• Analysis and modification of Javascript (PyV8): unescape, replace, join
• Shellcode analysis (Libemu python wrapper, pylibemu)
• Variables (set command)
• Extraction of old versions of the document
• Easy extraction of objects, Javascript code, shellcodes (>, >>, $>, $>>)
• Checking hashes on VirusTotal

• Basic PDF creation
• Creation of PDF with Javascript executed wen the document is opened
• Creation of object streams to compress objects
• Embedded PDFs
• Strings and names obfuscation
• Malformed PDF output: without endobj, garbage in the header, bad header...
• Filters modification
• Objects modification

• Simple command line execution
• Powerful interactive console (colorized or not)
• Batch mode

• Embedded PDFs analysis
• Improving automatic Javascript analysis
• GUI 

PDFMiner is a tool for extracting information from PDF documents. Unlike other PDF-related tools, it focuses entirely on getting and analyzing text data. PDFMiner allows one to obtain the exact location of text in a page, as well as other information such as fonts or lines. It includes a PDF converter that can transform PDF files into other text formats (such as HTML). It has an extensible PDF parser that can be used for other purposes than text analysis.

Features

• Written entirely in Python. (for version 2.4 or newer)
• Parse, analyze, and convert PDF documents.
• PDF-1.7 specification support. (well, almost)
• CJK languages and vertical writing scripts support.
• Various font types (Type1, TrueType, Type3, and CID) support.
• Basic encryption (RC4) support.
• PDF to HTML conversion (with a sample converter web app).
• Outline (TOC) extraction.
• Tagged contents extraction.
• Reconstruct the original layout by grouping text chunks.