Pros of ParrotSec Mimikatz

• More frequent updates and maintenance
• Tailored for Parrot OS, potentially offering better integration
• May include additional features or optimizations specific to Parrot OS

Cons of ParrotSec Mimikatz

• Limited to Parrot OS ecosystem, potentially less versatile
• Smaller community and less widespread adoption
• May lag behind the original in terms of new feature implementations

Code Comparison

Mimikatz (original):

BOOL APIENTRY DllMain(HMODULE hModule, DWORD ul_reason_for_call, LPVOID lpReserved)
{
	switch (ul_reason_for_call)
	{
		case DLL_PROCESS_ATTACH:
			kuhl_m_sekurlsa_utils_my_LdrEnumModulesCallback(NULL, 0, NULL);
			break;
		case DLL_PROCESS_DETACH:
			break;
	}
	return TRUE;
}

ParrotSec Mimikatz:

BOOL APIENTRY DllMain(HMODULE hModule, DWORD ul_reason_for_call, LPVOID lpReserved)
{
	switch (ul_reason_for_call)
	{
		case DLL_PROCESS_ATTACH:
			kuhl_m_sekurlsa_utils_my_LdrEnumModulesCallback(NULL, 0, NULL);
			// Additional Parrot OS specific initialization
			break;
		case DLL_PROCESS_DETACH:
			// Parrot OS specific cleanup
			break;
	}
	return TRUE;
}

Note: The code comparison is hypothetical, as the actual differences may vary. The ParrotSec version might include additional OS-specific optimizations or features.

Pros of pypykatz

• Written in Python, making it more portable and easier to integrate with other Python-based tools
• Can be used as a library, allowing for more flexible integration in custom scripts
• Supports parsing offline memory dumps and hibernation files

Cons of pypykatz

• Generally slower performance compared to the C-based Mimikatz
• May have less comprehensive coverage of Windows security features
• Potentially less frequently updated than the original Mimikatz

Code Comparison

Mimikatz (C):

BOOL WINAPI kuhl_m_sekurlsa_acquireLSA()
{
    NTSTATUS status = STATUS_NOT_FOUND;
    KULL_M_MEMORY_TYPE Type;
    PKULL_M_MEMORY_HANDLE hMemLSA = NULL;
    KUHL_M_SEKURLSA_CONTEXT cLsass = {NULL, {0, 0, 0}};

pypykatz (Python):

def get_lsa_decryptor(reader, lsa_decryptor_factory):
    lsa_dec = lsa_decryptor_factory(reader)
    lsa_dec.load()
    return lsa_dec

def get_wdigest(sysinfo, reader, lsa_decryptor):
    wdigest = wdigest_decryptor(sysinfo, reader, lsa_decryptor)
    wdigest.start()
    return wdigest

Pros of LaZagne

• Multi-platform support (Windows, Linux, macOS)
• Broader scope of credential retrieval (browsers, email clients, databases, etc.)
• Modular architecture allowing easy addition of new modules

Cons of LaZagne

• Less focused on deep Windows credential extraction
• May require more setup and dependencies
• Not as widely recognized or battle-tested as Mimikatz

Code Comparison

LaZagne (Python):

def run_lazagne(category_selected="all", subcategories={}, password=None):
    for category in category_selected:
        for module in get_categories()[category]:
            try:
                mod = import_module(module)
                pwd_found = mod.run(password)
                # Process and store results
            except Exception:
                pass

Mimikatz (C):

NTSTATUS kuhl_m_sekurlsa_msv(int argc, wchar_t * argv[])
{
    return kuhl_m_sekurlsa_getLogonData(lsasrv, kuhl_m_sekurlsa_enum_logon_callback_msv, NULL);
}

The code snippets highlight LaZagne's modular approach using Python, while Mimikatz employs low-level C for direct Windows API interaction.

Pros of BloodHound

• Provides a comprehensive visual representation of Active Directory relationships
• Offers powerful path-finding capabilities for identifying attack vectors
• Supports extensibility through custom queries and data ingestion

Cons of BloodHound

• Requires more setup and configuration compared to Mimikatz
• May generate significant network traffic during data collection
• Limited to Active Directory environments, while Mimikatz has broader application

Code Comparison

BloodHound (Cypher query example):

MATCH p = shortestPath((u:User)-[r:MemberOf|HasSession|AdminTo*1..]->(c:Computer))
WHERE u.name = 'JohnDoe'
RETURN p

Mimikatz (command example):

privilege::debug
sekurlsa::logonpasswords

While BloodHound focuses on graph-based analysis of Active Directory, Mimikatz is primarily used for extracting credentials and performing various authentication-related tasks. The code examples highlight their different approaches: BloodHound uses Cypher queries for relationship analysis, while Mimikatz employs direct system commands for credential extraction.

Pros of PowerSploit

• Written in PowerShell, making it more accessible and easier to integrate into existing Windows environments
• Offers a wider range of post-exploitation tools and modules beyond just credential harvesting
• Can be run entirely in memory, reducing the risk of detection by antivirus software

Cons of PowerSploit

• Less effective at extracting credentials from memory compared to Mimikatz
• May be more easily detected by modern security solutions due to PowerShell's increased scrutiny
• Requires PowerShell to be enabled on the target system, which may not always be the case

Code Comparison

Mimikatz (C):

BOOL WINAPI sekurlsa::AcquireKeys(PKIWI_BCRYPT_KEY_DATA *pKeys, PVOID pContext)
{
    BOOL status = FALSE;
    PKIWI_BCRYPT_KEY_DATA keys = NULL;
    // ... (additional code)
}

PowerSploit (PowerShell):

function Get-Keystrokes
{
    [CmdletBinding()] Param (
        [Parameter(Position = 0, Mandatory = $False)] [Int32] $LogLength = 0,
        [Parameter(Position = 1, Mandatory = $False)] [Int32] $Timeout = 0
    )
    # ... (additional code)
}