Generate randomized and edge-case inputs to detect unexpected failures, bugs, and security vulnerabilities through fuzz testing. Use when creating test cases for robustness testing, generating adversarial inputs, testing error handling, finding edge cases, or security testing. Produces Python test code with fuzzing inputs for strings, numbers, and structured data focusing on edge cases, invalid inputs, and random valid inputs. Triggers when users ask to generate fuzz tests, create randomized test inputs, test edge cases, find bugs through fuzzing, or generate adversarial test cases.
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Validation for skill structure
Generate comprehensive fuzz testing inputs to uncover bugs, crashes, and security vulnerabilities by systematically testing functions with edge cases, invalid inputs, and randomized data.
Understand what needs to be fuzzed:
Identify input types:
Understand expected behavior:
Extract function signature:
def process_user_input(name: str, age: int, email: str) -> dict:
"""Process user registration data."""
# Analyze: expects string, int, string
# Constraints: name non-empty, age > 0, email formatChoose appropriate fuzzing approaches:
Test boundary conditions and special values:
Test with malformed or incorrect data:
Generate random but technically valid inputs:
Test for vulnerabilities:
Create Python test functions with fuzzing inputs.
import pytest
import random
import string
def fuzz_<function_name>():
"""Fuzz test for <function_name>."""
# Edge cases
edge_cases = [
# Add specific edge case inputs
]
# Invalid inputs
invalid_inputs = [
# Add invalid inputs
]
# Random valid inputs
def generate_random_valid():
# Generate random but valid input
pass
# Test edge cases
for input_data in edge_cases:
try:
result = function_under_test(input_data)
# Check result or at least that it doesn't crash
except Exception as e:
# Document or assert expected exceptions
pass
# Test invalid inputs
for input_data in invalid_inputs:
# Similar testing pattern
pass
# Test random inputs
for _ in range(100):
random_input = generate_random_valid()
# Test with random inputCreate comprehensive input sets for each parameter type. See fuzzing-patterns.md for extensive patterns.
def generate_string_fuzz_inputs():
"""Generate fuzz inputs for string parameters."""
return [
# Empty and whitespace
"",
" ",
" ",
"\t",
"\n",
"\r\n",
# Length edge cases
"a", # Single char
"a" * 100, # Medium
"a" * 10000, # Long
"a" * 1000000, # Very long
# Special characters
"!@#$%^&*()",
"'",
"\"",
"\\",
"<script>alert(1)</script>",
# Unicode
"🔥",
"你好",
"مرحبا",
# Injection patterns
"'; DROP TABLE users--",
"../../../etc/passwd",
"${var}",
# Format strings
"%s%s%s",
"{0}{1}{2}",
# Null bytes
"\x00",
"test\x00test",
]def generate_number_fuzz_inputs():
"""Generate fuzz inputs for numeric parameters."""
return [
# Integers
0,
1,
-1,
2**31 - 1, # Max 32-bit int
-2**31, # Min 32-bit int
2**63 - 1, # Max 64-bit int
-2**63, # Min 64-bit int
# Floats
0.0,
-0.0,
float('inf'),
float('-inf'),
float('nan'),
1e308, # Near max float
1e-308, # Near min float
0.1 + 0.2, # Precision issue
# Edge cases
None,
"123", # String number
"not a number",
[],
{},
]def generate_json_fuzz_inputs():
"""Generate fuzz inputs for JSON/dict parameters."""
return [
# Empty
{},
[],
None,
# Type confusion
{"number": "123"},
{"bool": "true"},
{"array": "[]"},
# Deep nesting
{"a": {"b": {"c": {"d": {"e": "deep"}}}}},
[[[[["nested"]]]]],
# Large structures
{f"key{i}": i for i in range(1000)},
[i for i in range(10000)],
# Special keys
{"": "empty key"},
{"key with spaces": "value"},
{"key.with.dots": "value"},
# Mixed types
{"str": "text", "num": 123, "bool": True, "null": None, "arr": [1, 2]},
# Invalid JSON strings
"{invalid}",
'{"unclosed": ',
'{"key": undefined}',
]Generate executable test code:
import pytest
import random
import string
def test_fuzz_process_username():
"""Fuzz test for username processing."""
def process_username(username: str) -> str:
"""Function under test."""
if not username:
raise ValueError("Username cannot be empty")
if len(username) > 50:
raise ValueError("Username too long")
return username.strip().lower()
# Edge case inputs
edge_cases = [
"", # Empty
" ", # Space only
"a", # Single char
"A" * 50, # Max length
"A" * 51, # Over max
" user ", # Surrounding spaces
"User123", # Mixed case
"user@name", # Special chars
"user\nname", # Newline
"🔥user", # Unicode
"\x00user", # Null byte
]
# Invalid inputs
invalid_inputs = [
None,
123,
[],
{},
True,
]
# Test edge cases
for username in edge_cases:
try:
result = process_username(username)
assert isinstance(result, str)
assert len(result) <= 50
except ValueError as e:
# Expected for empty or too long
assert "empty" in str(e) or "too long" in str(e)
except Exception as e:
pytest.fail(f"Unexpected exception for '{username}': {e}")
# Test invalid types
for username in invalid_inputs:
try:
result = process_username(username)
pytest.fail(f"Should reject invalid type: {type(username)}")
except (TypeError, AttributeError):
pass # Expected
# Random fuzzing
for _ in range(100):
length = random.randint(0, 100)
chars = string.ascii_letters + string.digits + " !@#$"
random_username = ''.join(random.choice(chars) for _ in range(length))
try:
result = process_username(random_username)
# Verify properties that should always hold
if random_username.strip():
assert result.islower()
assert len(result) <= 50
except ValueError:
# Expected for empty or too long
passimport pytest
import math
def test_fuzz_validate_age():
"""Fuzz test for age validation."""
def validate_age(age: int) -> bool:
"""Function under test."""
return 0 <= age <= 150
# Edge case inputs
edge_cases = [
0, # Min valid
1,
150, # Max valid
-1, # Just below min
151, # Just above max
18, # Common value
65, # Another common
2**31 - 1, # Max int
-2**31, # Min int
]
# Invalid/special inputs
special_inputs = [
None,
"25", # String
25.5, # Float
float('inf'),
float('-inf'),
float('nan'),
[],
{},
True, # 1 in Python
False, # 0 in Python
]
# Test edge cases
for age in edge_cases:
try:
result = validate_age(age)
assert isinstance(result, bool)
if 0 <= age <= 150:
assert result is True
else:
assert result is False
except Exception as e:
pytest.fail(f"Unexpected exception for {age}: {e}")
# Test invalid types
for age in special_inputs:
try:
result = validate_age(age)
# Document behavior with non-int types
except (TypeError, ValueError):
pass # May be expected
# Random fuzzing
for _ in range(100):
random_age = random.randint(-1000, 1000)
try:
result = validate_age(random_age)
assert result == (0 <= random_age <= 150)
except Exception as e:
pytest.fail(f"Failed for random age {random_age}: {e}")import pytest
import json
import random
def test_fuzz_parse_user_data():
"""Fuzz test for JSON user data parsing."""
def parse_user_data(data: dict) -> dict:
"""Function under test."""
name = data["name"]
age = int(data["age"])
email = data.get("email", "")
if not name:
raise ValueError("Name required")
if age < 0:
raise ValueError("Age must be non-negative")
return {"name": name.strip(), "age": age, "email": email}
# Edge case inputs
edge_cases = [
{"name": "John", "age": 25}, # Valid
{"name": "John", "age": 25, "email": "j@e.com"}, # With optional
{"name": " John ", "age": 0}, # Whitespace
{"name": "A" * 1000, "age": 150}, # Long name
{"name": "🔥", "age": 1}, # Unicode
{}, # Empty
{"name": ""}, # Empty name
{"name": "John", "age": -1}, # Negative age
{"name": "John", "age": "25"}, # String age
{"name": None, "age": 25}, # None value
{"extra": "field", "name": "John", "age": 25}, # Extra fields
]
# Test edge cases
for data in edge_cases:
try:
result = parse_user_data(data)
assert isinstance(result, dict)
assert "name" in result
assert "age" in result
assert isinstance(result["age"], int)
assert result["age"] >= 0
except (KeyError, ValueError, TypeError) as e:
# Expected for invalid inputs
pass
except Exception as e:
pytest.fail(f"Unexpected exception for {data}: {e}")
# Random fuzzing
name_chars = string.ascii_letters + " "
for _ in range(100):
random_data = {
"name": ''.join(random.choice(name_chars) for _ in range(random.randint(0, 50))),
"age": random.randint(-10, 200),
"email": f"test{random.randint(0, 1000)}@example.com"
}
try:
result = parse_user_data(random_data)
# Verify invariants
if random_data["name"].strip() and random_data["age"] >= 0:
assert result["name"] == random_data["name"].strip()
assert result["age"] == random_data["age"]
except (KeyError, ValueError, TypeError):
# Expected for invalid random inputs
passCreate a complete test suite:
# test_fuzz_suite.py
import pytest
import random
import string
from your_module import function_to_test
class TestFuzzSuite:
"""Comprehensive fuzz testing suite."""
def test_edge_cases(self):
"""Test boundary conditions and special values."""
# Edge case tests
pass
def test_invalid_inputs(self):
"""Test with malformed and invalid inputs."""
# Invalid input tests
pass
def test_random_valid(self):
"""Test with randomized valid inputs."""
# Random fuzzing tests
pass
def test_security(self):
"""Test for injection and security issues."""
# Security tests
pass
@pytest.mark.slow
def test_extensive_fuzzing(self):
"""Extended fuzzing with many iterations."""
# Run 10000+ iterations
passRun the tests:
# Run all fuzz tests
pytest test_fuzz_suite.py -v
# Run with coverage
pytest test_fuzz_suite.py --cov=your_module
# Run only fast tests
pytest test_fuzz_suite.py -m "not slow"
# Run extensive fuzzing
pytest test_fuzz_suite.py -m slowWhen fuzzing finds failures:
Document the failure:
Create regression tests:
def test_regression_issue_123():
"""Regression test for crash with null byte."""
# This input was found by fuzzing
problematic_input = "test\x00data"
# Should handle gracefully
with pytest.raises(ValueError, match="null byte"):
process_input(problematic_input)Fix the code:
def process_input(data: str) -> str:
# Add validation found necessary by fuzzing
if "\x00" in data:
raise ValueError("null byte not allowed")
# ... rest of functionUser request:
"Generate fuzz tests for this function"
def divide(a: float, b: float) -> float:
return a / bResponse:
import pytest
import math
def test_fuzz_divide():
"""Fuzz test for divide function."""
# Edge cases
edge_cases = [
(10, 2), # Normal
(0, 1), # Zero numerator
(1, 0), # Division by zero
(-10, 2), # Negative
(10, -2), # Negative divisor
(float('inf'), 1), # Infinity
(1, float('inf')), # Divide by infinity
(float('nan'), 1), # NaN
(1, float('nan')), # Divide by NaN
(1e308, 1e-308), # Extreme values
]
for a, b in edge_cases:
try:
result = divide(a, b)
# Check result properties
if b == 0:
pytest.fail(f"Should raise ZeroDivisionError for b=0")
if not math.isnan(result):
assert math.isclose(result, a / b, rel_tol=1e-9)
except ZeroDivisionError:
assert b == 0 # Expected
except Exception as e:
pytest.fail(f"Unexpected exception for ({a}, {b}): {e}")
# Random fuzzing
for _ in range(1000):
a = random.uniform(-1e10, 1e10)
b = random.uniform(-1e10, 1e10)
try:
result = divide(a, b)
if abs(b) > 1e-10: # Avoid near-zero denominators
expected = a / b
if not math.isnan(expected):
assert math.isclose(result, expected, rel_tol=1e-6)
except ZeroDivisionError:
assert abs(b) < 1e-10 # Expected for small denominatorsUser request:
"Create fuzz tests to find path traversal vulnerabilities"
def test_fuzz_file_path_security():
"""Fuzz test for path traversal vulnerabilities."""
def safe_read_file(filename: str) -> str:
"""Function under test - should prevent path traversal."""
# Implementation would validate filename
pass
# Path traversal attacks
path_traversal_inputs = [
"../../../etc/passwd",
"..\\..\\..\\windows\\system32\\config\\sam",
"....//....//etc/passwd",
"%2e%2e%2f%2e%2e%2fetc%2fpasswd",
"..%252f..%252fetc%252fpasswd",
"file://etc/passwd",
"/etc/passwd",
"C:\\Windows\\System32",
"~/../../etc/passwd",
".",
"..",
"/",
"\\",
"",
"\x00",
"file\x00.txt",
"con", # Windows reserved
"nul",
"prn",
"a" * 1000, # Very long path
"a/" * 500 + "file.txt", # Very deep path
]
for path in path_traversal_inputs:
try:
result = safe_read_file(path)
# Should either reject or sanitize
assert not any(danger in path.lower() for danger in ["etc/passwd", "system32", ".."])
except (ValueError, PermissionError, FileNotFoundError):
# Expected rejection
pass
except Exception as e:
pytest.fail(f"Unexpected exception for path '{path}': {e}")Start with known edge cases:
Think like an attacker:
Use property-based testing:
decode(encode(x)) == xf(f(x)) == f(x)f(x, y) == f(y, x)Monitor coverage:
# Use coverage.py to find untested code paths
pytest --cov=module --cov-report=html test_fuzz.pyIterate based on findings:
Balance breadth and depth:
For comprehensive fuzzing patterns and edge cases, see fuzzing-patterns.md.
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