ghidra-re

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Ghidra Reverse Engineering for Firmware

Expert-level Ghidra workflows for analyzing stripped firmware binaries, with automation via Python scripting.

Skill Scope

Use this skill for:

Deep analysis of individual firmware binaries in Ghidra
Stripped binary reverse engineering
Automated vulnerability hunting
Cryptographic routine identification
Authentication logic discovery
Custom script development

Prerequisites:

Ghidra 12.1.3 with its bundled Jython extension installed (File → Install Extensions → Jython, then restart). Scripts explicitly select # @runtime Jython; they do not run in a standalone Python interpreter.
JDK required by the installed Ghidra release (JDK 21 for 12.1.3)
Python scripting knowledge
Understanding of assembly (ARM/MIPS/x86)
Binary already extracted (use firmware-extraction skill)

Integration:

After: firmware-extraction, firmware-static-analysis (initial recon)
Before/During: firmware-emulation (validate findings dynamically)

The four bundled scripts produce review candidates, not confirmed vulnerabilities. They inspect recovered instructions and resolved references; indirect calls, inlined code and unrecovered data may be missed. They preserve existing names and comments; candidate renames apply only to default symbols. Save the project before running analysis scripts.

Set these paths for the headless examples (replace with absolute local paths):

bash

export GHIDRA_INSTALL_DIR=/path/to/ghidra_12.1.3_PUBLIC
export GHIDRA_SCRIPT_DIR=/path/to/ghidra-re/scripts
mkdir -p /projects

Analysis Workflow

1. Project Setup

bash

# Create project
"$GHIDRA_INSTALL_DIR/ghidraRun"

# Or headless for automation
"$GHIDRA_INSTALL_DIR/support/analyzeHeadless" /projects FirmwareProject -scriptPath "$GHIDRA_SCRIPT_DIR" -import /path/to/binary.elf

# Batch import
for bin in extracted/bin/*; do
    "$GHIDRA_INSTALL_DIR/support/analyzeHeadless" /projects Firmware -scriptPath "$GHIDRA_SCRIPT_DIR" -import "$bin"
done

2. Initial Analysis (Stripped Binary Focus)

Automated approach:

bash

# Run analysis scripts in sequence
"$GHIDRA_INSTALL_DIR/support/analyzeHeadless" /projects Firmware -scriptPath "$GHIDRA_SCRIPT_DIR" -process binary.elf \
  -postScript find_crypto.py \
  -postScript find_auth_functions.py \
  -postScript find_buffer_overflows.py

Manual approach:

Run Auto-Analysis (Analysis → Auto Analyze)

Enable: Aggressive Instruction Finder, Stack, Decompiler Parameter ID

Find Functions - Stripped binaries need manual function discovery

Entry point: Find _start or main
Prologue scanning (see references/stripped-analysis.md)
Cross-reference analysis
String reference tracing

Initial Renaming

Run scripts/auto_rename.py for heuristic-based naming
Manually rename critical functions

3. Target-Specific Analysis

Choose analysis path based on goal:

Authentication Analysis → Use scripts/find_auth_functions.py

Identifies strcmp, password string refs, multi-return patterns
Ranks by heuristic score (not a probability)
Adds candidate names to highly ranked default symbols

Crypto Analysis → Use scripts/find_crypto.py

Searches for AES S-boxes, MD5/SHA constants
Labels crypto tables
Finds functions referencing crypto constants

Vulnerability Hunting → Use scripts/find_buffer_overflows.py

Detects dangerous function calls (strcpy, sprintf, gets)
Flags source/sink co-occurrence within a function; does not trace taint
Lists large recovered stack objects in functions with risky API calls

Network Protocol Analysis

Find socket/recv/send calls
Trace data flow from network input
Identify protocol parsing functions

4. Deep Function Analysis

For each interesting function:

python

# @runtime Jython
# Decompile and enhance
func = getFunctionAt(toAddr("0x00401000"))

# Set signature (if known)
sig = "int verify_password(char *user_input, char *stored_hash)"
from ghidra.app.cmd.function import ApplyFunctionSignatureCmd
from ghidra.app.util.parser import FunctionSignatureParser
from ghidra.program.model.symbol import SourceType
from ghidra.program.model.listing import Function, ParameterImpl
from ghidra.program.model.data import *
assert func is not None, "Select a valid function entry"
definition = FunctionSignatureParser(currentProgram.getDataTypeManager(), None).parse(func.getSignature(), sig)
assert ApplyFunctionSignatureCmd(func.getEntryPoint(), definition, SourceType.USER_DEFINED).applyTo(currentProgram)

# Define structures
dtm = currentProgram.getDataTypeManager()
struct = StructureDataType("auth_request", 0)
struct.add(DWordDataType(), "session_id", None)
struct.add(PointerDataType(CharDataType()), "username", None)
struct.add(PointerDataType(CharDataType()), "password", None)
dtm.addDataType(struct, DataTypeConflictHandler.REPLACE_HANDLER)

# Apply to function parameters
param = ParameterImpl("request", PointerDataType(struct), currentProgram)
func.replaceParameters(Function.FunctionUpdateType.DYNAMIC_STORAGE_ALL_PARAMS, True, SourceType.USER_DEFINED, param)

5. Vulnerability Analysis

Buffer Overflow Detection:

python

# @runtime Jython
# Manual verification after script identifies candidates
# 1. Check buffer size
# 2. Trace input length
# 3. Verify bounds checking (or lack thereof)
# 4. Confirm exploitability

# Example: strcpy without length check
# Decompiler shows:
#   strcpy(local_buffer, user_input);
# Check local_buffer size in stack frame
# Verify attacker-controlled length exceeds the destination and reaches this call.
# A write beyond the buffer is a vulnerability; code execution needs separate evidence.

Format String Bugs:

python

# @runtime Jython
# Find printf(user_controlled_string)
# Script pattern:
if "printf" in called_functions:
    # Check if format arg is from user input
    # A variable format is not necessarily attacker-controlled; trace its origin.
    pass  # Manual review, not a complete detector

Command Injection:

python

# @runtime Jython
# Find system/popen with user data
# Pattern: system(cmd) where cmd contains user input
# Look for string concatenation before system() call

6. Type and Structure Recovery

Automated structure inference:

python

# @runtime Jython
# See references/stripped-analysis.md for a sketch, not a complete inference engine
# Analyzes memory access patterns:
# - *(ptr + 0) → field at offset 0
# - *(ptr + 4) → field at offset 4
# Define the structure manually after verifying offsets and field sizes

Manual structure definition:

python

# @runtime Jython
# From decompiler output showing member accesses
struct = StructureDataType("device_state", 0)
struct.add(DWordDataType(), "magic", None)          # offset 0
struct.add(ByteDataType(), "enabled", None)         # offset 4
struct.add(ArrayDataType(CharDataType(), 32, 1), "name", None)  # offset 5
# Apply and watch decompiler improve

7. Cross-Referencing

Find callers:

Right-click function → References → Show References to

Find call sites:

python

# @runtime Jython
func = getFunctionAt(currentAddress)
refs = getReferencesTo(func.getEntryPoint())
for ref in refs:
    if ref.getReferenceType().isCall():
        caller = getFunctionContaining(ref.getFromAddress())
        if caller:
            print("Called from: {}".format(caller.getName()))

Trace data flow:

python

# @runtime Jython
# From source to sink
# 1. Find all calls to source (e.g., recv)
# 2. Track where data goes
# 3. Check if reaches sink (e.g., system)
# See scripts/find_buffer_overflows.py for manual data-flow verification

Provided Scripts

All scripts in scripts/ run in Ghidra with the Jython runtime above:

find_crypto.py

Finds candidate constant prefixes and their direct references; absence is not evidence that crypto is absent:

First 16 bytes of the AES S-box
First four MD5 / SHA256 constants in either byte order
Auto-labels crypto tables
Finds functions referencing crypto data

Usage:

bash

"$GHIDRA_INSTALL_DIR/support/analyzeHeadless" /projects Project -scriptPath "$GHIDRA_SCRIPT_DIR" -process binary -postScript find_crypto.py

findauthfunctions.py

Discovers authentication logic via heuristics:

String analysis (password, login, auth keywords)
API calls (strcmp, crypt, verify)
Multi-return patterns (success/fail branches)
Scores and ranks candidates

Usage:

bash

"$GHIDRA_INSTALL_DIR/support/analyzeHeadless" /projects Project -scriptPath "$GHIDRA_SCRIPT_DIR" -process binary -postScript find_auth_functions.py

findbufferoverflows.py

Detects potential buffer overflow vulnerabilities:

Dangerous function calls (strcpy, sprintf, gets)
Source/sink co-occurrence (data flow unverified)
Stack buffer identification
Appends review notes at candidate locations without deleting analyst comments

Usage:

bash

"$GHIDRA_INSTALL_DIR/support/analyzeHeadless" /projects Project -scriptPath "$GHIDRA_SCRIPT_DIR" -process binary -postScript find_buffer_overflows.py

Scripting Patterns

Template Script

python

# @runtime Jython
# my_analysis.py
# Description: Custom analysis for firmware

from ghidra.program.model.symbol import SourceType

currentProgram = getCurrentProgram()
listing = currentProgram.getListing()
fm = currentProgram.getFunctionManager()
mem = currentProgram.getMemory()

# Your analysis logic
for func in fm.getFunctions(True):
    # Process each function
    pass

Common Operations

python

# @runtime Jython
# Navigate
addr = toAddr("0x00400000")
func = getFunctionAt(addr)
func = getFunctionContaining(addr)

# Modify
func.setName("new_name", SourceType.USER_DEFINED)
createFunction(addr, "function_name")
createLabel(addr, "label_name", True)

# Data types
from ghidra.program.model.data import *
DWordDataType()
PointerDataType(CharDataType())
StructureDataType("struct_name", 0)

# Instructions
instr = listing.getInstructionAt(addr)
instr.getMnemonicString()  # "bl", "mov", etc.
instr.getReferencesFrom()

# Decompiler
from ghidra.app.decompiler import DecompInterface
decompiler = DecompInterface()
decompiler.openProgram(currentProgram)
results = decompiler.decompileFunction(func, 30, monitor)
high_func = results.getHighFunction()

Stripped Binary Techniques

Function Discovery

Method 1: Prologue Scanning

python

# @runtime Jython
# ARM: push {r11, lr} = 0xe92d4800
# MIPS: addiu sp,sp,-XX
# x86: push ebp; mov ebp,esp

# Search for patterns in executable memory
# See references/stripped-analysis.md for complete implementation

Method 2: Cross-Reference Analysis

python

# @runtime Jython
# Find all call instructions
# Target addresses likely are function starts
# See references/stripped-analysis.md

Method 3: String References

python

# @runtime Jython
# Functions that reference strings
# Use string content to infer function purpose
# See references/stripped-analysis.md

Automatic Renaming Heuristics

python

# @runtime Jython
# Pattern-based naming
def infer_name(func):
    strings = get_function_strings(func)
    called = get_called_functions(func)
    
    # Authentication
    if any("password" in s.lower() for s in strings):
        if "strcmp" in called:
            return "check_password"
    
    # Network
    if "socket" in called or "recv" in called:
        return "network_handler"
    
    # Crypto
    if "aes" in "".join(strings).lower():
        return "crypto_aes"
    
    return None

Integration with Emulation

Workflow:

Static analysis in Ghidra (this skill)
Identify interesting functions
Set breakpoints in GDB at those addresses
Run in QEMU (firmware-emulation skill)
Observe behavior at breakpoints
Return to Ghidra with insights

Example:

python

# @runtime Jython
# In Ghidra: Find auth function
auth_func = getFunctionAt(toAddr("0x00401234"))

# Note address: 0x00401234. For PIE/shared objects, translate using the actual
# runtime load bias; do not use a static address unchanged.

# In QEMU with GDB:
# gdb-multiarch binary
# (gdb) target remote :1234
# (gdb) break *0x00401234
# (gdb) continue
# ... trigger auth ...
# (gdb) info registers  # See actual values

# Return to Ghidra with understanding of runtime behavior

Best Practices

Start Automated - Run scripts before manual analysis
Name Incrementally - Don't try to name everything at once
Trust Decompiler, Verify Assembly - Decompiler is good but not perfect
Document Assumptions - Use comments liberally
Version Control - Use a shared Ghidra Server project for program versioning; use Git for exported scripts and notes
Cross-Reference Constantly - Understand call graphs
Type Everything - Proper types improve decompilation dramatically
Script Repetitive Tasks - Don't do the same thing 100 times manually

Keyboard Shortcuts

G                Go to address
L                Label/rename
;                EOL comment
Ctrl-;           Pre-comment
D                Disassemble
P                Create function
X                Show references to
Ctrl-Shift-E     Edit function signature
T                Set data type

Troubleshooting

Decompiler fails:

Check for unimplemented instructions
Simplify function (may be too complex)
Try different decompiler options

Auto-analysis misses functions:

Use scripts from scripts/ folder
Manual prologue search (see references/stripped-analysis.md)

Poor decompilation quality:

Set proper function signatures
Define structures for complex data types
Add type information to variables

References

Stripped Analysis: references/stripped-analysis.md - Complete techniques for analyzing stripped binaries, type recovery, function discovery
Workflow: references/workflow.md - Expert workflow patterns, scripting examples, integration tips

Quick Command Reference

bash

# Headless analysis with scripts
"$GHIDRA_INSTALL_DIR/support/analyzeHeadless" /projects Firmware -scriptPath "$GHIDRA_SCRIPT_DIR" -import binary.elf \
  -postScript find_crypto.py -postScript find_auth_functions.py

# Import without auto-analysis (manual control)
"$GHIDRA_INSTALL_DIR/support/analyzeHeadless" /projects Firmware -scriptPath "$GHIDRA_SCRIPT_DIR" -import binary.elf -noanalysis

# Export analysis results (first save the JSON example in references/workflow.md
# as export_results.py in GHIDRA_SCRIPT_DIR; it is not a bundled script)
"$GHIDRA_INSTALL_DIR/support/analyzeHeadless" /projects Firmware -scriptPath "$GHIDRA_SCRIPT_DIR" -process binary.elf \
  -postScript export_results.py

python

# @runtime Jython
# Essential Ghidra Python APIs
currentProgram                              # Program object
getFunctionAt(addr)                         # Get function
createFunction(addr, name)                  # Create function
toAddr("0x00400000")                        # String to address
listing.getInstructions(body, True)         # Iterate instructions
getReferencesTo(addr)                       # Get xrefs to
func.setName(name, SourceType.USER_DEFINED) # Rename function

Next Steps After Ghidra Analysis

Document findings - Create analysis report with key functions, vulnerabilities
Test hypotheses - Use firmware-emulation to verify static findings
Develop exploits - If vulnerabilities found, create PoCs
Report - Prepare comprehensive security assessment

This skill assumes expert RE knowledge and focuses on firmware-specific analysis patterns. For general Ghidra basics, consult official documentation.

Ghidra Reverse Engineering for Firmware

Skill Scope

Analysis Workflow

1. Project Setup

2. Initial Analysis (Stripped Binary Focus)

3. Target-Specific Analysis

4. Deep Function Analysis

5. Vulnerability Analysis

6. Type and Structure Recovery

7. Cross-Referencing

Provided Scripts

find_crypto.py

findauthfunctions.py

findbufferoverflows.py

Scripting Patterns

Template Script

Common Operations

Stripped Binary Techniques

Function Discovery

Automatic Renaming Heuristics

Integration with Emulation

Best Practices

Keyboard Shortcuts

Troubleshooting

References

Quick Command Reference

Next Steps After Ghidra Analysis

Weitere Skills

firmware-static-analysis