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# Dynamic Analysis
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Dynamic analysis capabilities for runtime analysis and modification of Android applications using Frida integration. The Pentest module provides comprehensive dynamic analysis functionality including tracing, hooking, and runtime manipulation.
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## Capabilities
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### Pentest Engine
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The main dynamic analysis engine providing Frida integration and runtime analysis capabilities.
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```python { .api }
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class Pentest:
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    def __init__(self):
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        """Initialize the dynamic analysis engine."""
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def connect_default_usb(self) -> bool:
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    """
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    Connect to the default USB device for dynamic analysis.
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    Returns:
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        bool: True if connection successful, False otherwise
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    """
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def attach_package(self, package_name: str, list_file_scripts: list, pid=None) -> bool:
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    """
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    Attach to a running package for dynamic analysis.
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    Parameters:
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    - package_name: Android package name to attach to
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    - list_file_scripts: List of Frida script files to inject
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    - pid: Process ID (optional, will find automatically if None)
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    Returns:
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        bool: True if attachment successful
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    """
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def start_trace(self, filename: str, session: Session, list_modules: list, list_packages: list = None) -> None:
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    """
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    Start runtime tracing of specified modules and packages.
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    Parameters:
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    - filename: Output file for trace results
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    - session: Androguard session object
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    - list_modules: List of modules to trace
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    - list_packages: List of packages to monitor (optional)
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    """
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def dump(self, package_name: str) -> dict:
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    """
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    Dump runtime information from a running package.
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    Parameters:
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    - package_name: Target package name
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    Returns:
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        dict: Dumped runtime information
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    """
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```
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### Message System
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Event-driven message system for handling dynamic analysis events and communications.
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```python { .api }
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class Message:
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    """Base message class for dynamic analysis communication."""
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class MessageEvent(Message):
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    """Event-based message for dynamic analysis events."""
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class MessageSystem(Message):
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    """System-level message for dynamic analysis operations."""
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```
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### Usage Examples
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#### Basic Dynamic Analysis Setup
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```python
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from androguard.pentest import Pentest
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from androguard.session import Session
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# Initialize dynamic analysis engine
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pentest = Pentest()
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# Connect to USB device
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if pentest.connect_default_usb():
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    print("Connected to device successfully")
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    # Attach to target package with Frida scripts
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    scripts = ["hooks.js", "trace.js"]
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    if pentest.attach_package("com.example.app", scripts):
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        print("Successfully attached to package")
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```
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#### Runtime Tracing
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```python
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from androguard.pentest import Pentest
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from androguard.session import Session
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# Setup session and pentest engine
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session = Session()
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pentest = Pentest()
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# Start tracing specific modules
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modules_to_trace = ["libnative.so", "libssl.so"]
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packages_to_monitor = ["com.example.app"]
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pentest.start_trace(
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    filename="trace_output.log",
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    session=session,
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    list_modules=modules_to_trace,
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    list_packages=packages_to_monitor
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)
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```
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#### Package Information Dumping
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```python
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from androguard.pentest import Pentest
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pentest = Pentest()
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# Connect and dump package information
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if pentest.connect_default_usb():
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    package_info = pentest.dump("com.example.target")
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    print("Package dump results:")
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    for key, value in package_info.items():
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        print(f"  {key}: {value}")
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```
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### Frida Integration
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The dynamic analysis module integrates with Frida for advanced runtime analysis capabilities including:
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- **Method hooking**: Intercept and modify method calls at runtime
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- **Memory manipulation**: Read and write application memory
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- **API tracing**: Monitor system and library API calls
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- **Code injection**: Execute custom JavaScript code in target process
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- **SSL pinning bypass**: Disable certificate pinning mechanisms
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- **Anti-debugging bypass**: Circumvent common anti-analysis techniques
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### Common Use Cases
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#### Security Analysis
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```python
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# Hook sensitive API calls
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frida_script = """
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Java.perform(function() {
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    var CryptoClass = Java.use("javax.crypto.Cipher");
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    CryptoClass.doFinal.implementation = function(input) {
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        console.log("Crypto operation detected: " + input);
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        return this.doFinal(input);
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    };
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});
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"""
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# Inject script into target
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pentest.attach_package("com.banking.app", ["crypto_hooks.js"])
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```
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#### Behavioral Analysis
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```python
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# Trace network communications
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network_trace_modules = ["libssl.so", "libc.so"]
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pentest.start_trace(
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    "network_trace.log",
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    session,
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    network_trace_modules,
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    ["com.suspicious.app"]
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)
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```
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#### Reverse Engineering
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```python
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# Dump runtime class information
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package_dump = pentest.dump("com.target.app")
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# Extract loaded classes and methods
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if "classes" in package_dump:
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    for class_name, methods in package_dump["classes"].items():
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        print(f"Class: {class_name}")
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        for method in methods:
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            print(f"  Method: {method}")
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```
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## Integration with Static Analysis
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Dynamic analysis complements static analysis by providing runtime verification of static findings:
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```python
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from androguard.misc import AnalyzeAPK
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from androguard.pentest import Pentest
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# Static analysis
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a, d, dx = AnalyzeAPK("app.apk")
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# Find suspicious methods statically
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suspicious_methods = dx.find_methods(method_name="encrypt.*")
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# Verify with dynamic analysis
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pentest = Pentest()
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pentest.connect_default_usb()
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# Hook the methods found in static analysis
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for method in suspicious_methods:
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    hook_script = f"hook_{method.name}.js"
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    pentest.attach_package(a.get_package(), [hook_script])
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```