Analyzing PDF Malware with PDFiD

When to Use

• A suspicious PDF attachment has been flagged by email security or reported by a user
• You need to determine if a PDF contains embedded JavaScript, shellcode, or exploit code
• Triaging PDF documents before opening them in a sandbox or analysis environment
• Extracting embedded executables, scripts, or URLs from malicious PDF objects
• Analyzing PDF exploit kits targeting Adobe Reader or other PDF viewer vulnerabilities

Do not use for analyzing the rendered visual content of a PDF; this is for structural analysis of the PDF file format for malicious objects.

Prerequisites

• Python 3.8+ with Didier Stevens' PDF tools installed (pip install pdfid pdf-parser)
• peepdf installed for interactive PDF analysis (pip install peepdf)
• pdftotext from poppler-utils for extracting text content safely
• YARA with PDF-specific rules for malware family identification
• Isolated analysis VM without a PDF reader installed (prevent accidental opening)
• CyberChef for decoding embedded Base64, hex, or deflate streams

Workflow

Step 1: Initial Triage with PDFiD

Scan the PDF for suspicious keywords and structures:

# Run PDFiD to identify suspicious elements
pdfid suspect.pdf

# Expected output analysis:
# /JS           - JavaScript (HIGH risk)
# /JavaScript   - JavaScript object (HIGH risk)
# /AA           - Auto-Action triggered on open (HIGH risk)
# /OpenAction   - Action on document open (HIGH risk)
# /Launch       - Launch external application (HIGH risk)
# /EmbeddedFile - Embedded file (MEDIUM risk)
# /RichMedia    - Flash content (MEDIUM risk)
# /ObjStm       - Object stream (used for obfuscation)
# /URI          - URL reference (contextual risk)
# /AcroForm     - Interactive form (MEDIUM risk)

# Run with extra detail
pdfid -e suspect.pdf

# Run with disarming (rename suspicious keywords)
pdfid -d suspect.pdf

PDFiD Risk Assessment:
━━━━━━━━━━━━━━━━━━━━━
HIGH RISK indicators (any count > 0):
  /JS, /JavaScript  -> Embedded JavaScript code
  /AA               -> Automatic Action (triggers without user interaction)
  /OpenAction       -> Code runs when document is opened
  /Launch           -> Can launch external executables
  /JBIG2Decode      -> Associated with CVE-2009-0658 exploit

MEDIUM RISK indicators:
  /EmbeddedFile     -> Contains embedded files (could be EXE/DLL)
  /RichMedia        -> Flash/multimedia (Flash exploits)
  /AcroForm         -> Form with possible submit action
  /XFA              -> XML Forms Architecture (complex attack surface)

LOW RISK indicators:
  /ObjStm           -> Object streams (obfuscation technique)
  /URI              -> External URL references
  /Page             -> Number of pages (context only)

Step 2: Parse PDF Structure with pdf-parser

Examine suspicious objects identified by PDFiD:

# List all objects referencing JavaScript
pdf-parser --search "/JavaScript" suspect.pdf
pdf-parser --search "/JS" suspect.pdf

# List all objects with OpenAction
pdf-parser --search "/OpenAction" suspect.pdf

# Extract a specific object by ID (example: object 5)
pdf-parser --object 5 suspect.pdf

# Extract and decompress stream content
pdf-parser --object 5 --filter --raw suspect.pdf

# Search for embedded files
pdf-parser --search "/EmbeddedFile" suspect.pdf

# List all objects with their types
pdf-parser --stats suspect.pdf

Step 3: Extract and Analyze Embedded JavaScript

Pull out JavaScript code from PDF objects:

# Extract JavaScript using pdf-parser
pdf-parser --search "/JS" --raw --filter suspect.pdf > extracted_js.txt

# Alternative: Use peepdf for interactive JavaScript extraction
peepdf -f -i suspect.pdf << 'EOF'
js_analyse
EOF

# peepdf interactive commands for JS analysis:
# js_analyse          - Extract and show all JavaScript code
# js_beautify         - Format extracted JavaScript
# js_eval <object>    - Evaluate JavaScript in sandboxed environment
# object <id>         - Display object content
# rawobject <id>      - Display raw object bytes
# stream <id>         - Display decompressed stream
# offsets             - Show object offsets in file

# Python script for comprehensive PDF JavaScript extraction
import subprocess
import re

# Extract all streams and search for JavaScript
result = subprocess.run(
    ["pdf-parser", "--stats", "suspect.pdf"],
    capture_output=True, text=True
)

# Find object IDs containing JavaScript references
js_objects = []

…