Pros of Mimikatz

• More comprehensive functionality, supporting various credential extraction techniques
• Cross-platform support (Windows, Linux, macOS)
• Actively maintained with frequent updates

Cons of Mimikatz

• Larger codebase, potentially more complex to use
• Higher likelihood of being flagged by antivirus software
• Requires administrative privileges on Windows systems

Code Comparison

Mimipenguin (Python):

def dump_target(target):
    if target == "gnome-keyring":
        # Gnome Keyring dump logic
    elif target == "kde-wallet":
        # KDE Wallet dump logic
    # ... other targets

Mimikatz (C):

NTSTATUS kuhl_m_sekurlsa_genericCredsOutput(PKIWI_GENERIC_PRIMARY_CREDENTIAL mesCreds, PLUID luid, PWSTR sid)
{
    // Complex credential extraction and output logic
}

Mimipenguin focuses on Linux-specific credential extraction, with a simpler Python codebase. Mimikatz offers a more comprehensive set of features for Windows systems, implemented in C with a more complex structure. While Mimipenguin is easier to use and less likely to trigger antivirus alerts, Mimikatz provides broader functionality and cross-platform support at the cost of increased complexity and potential detection.

Pros of LaZagne

• Multi-platform support (Windows, Linux, macOS)
• Retrieves passwords from a wide range of applications and browsers
• Actively maintained with regular updates

Cons of LaZagne

• Larger codebase, potentially more complex to use
• May trigger antivirus software due to its comprehensive nature

Code Comparison

LaZagne:

def run_lazagne(category_selected="all", subcategories={}, password=None):
    for category in category_selected:
        for r in runModule(category):
            yield r

mimipenguin:

if [[ $(id -u) -ne 0 ]]; then
    echo "Got root?"
    exit 1
fi

Key Differences

• LaZagne is a more comprehensive tool, targeting multiple platforms and applications
• mimipenguin focuses specifically on extracting Linux user credentials from memory
• LaZagne is written in Python, while mimipenguin is primarily a Bash script
• mimipenguin is more lightweight and focused on a single task
• LaZagne offers more flexibility in terms of password retrieval options

Both tools serve different purposes and can be valuable in their respective domains. LaZagne is better suited for broader password recovery tasks across multiple platforms, while mimipenguin excels at quickly extracting Linux credentials from memory.

Pros of Internal-Monologue

• Focuses on extracting NTLM hashes from memory without touching lsass.exe
• Works on Windows systems, expanding the range of target environments
• Utilizes built-in Windows APIs, potentially making it more stealthy

Cons of Internal-Monologue

• Limited to extracting NTLM hashes, while MimiPenguin can extract various credential types
• Requires administrative privileges on the target Windows system
• May be less effective against modern Windows security features

Code Comparison

MimiPenguin (Python):

def dump_process(pid):
    with open("/proc/%d/maps" % pid, "r") as maps:
        for line in maps:
            m = re.search(r"([0-9A-Fa-f]+)-([0-9A-Fa-f]+) ([-r])", line)
            if m:
                start, end, perms = int(m.group(1), 16), int(m.group(2), 16), m.group(3)
                if 'r' in perms:
                    mem = read_memory(pid, start, end - start)

Internal-Monologue (C#):

public static string InvokeNetNTLMFromMemory()
{
    IntPtr hProcess = GetCurrentProcess();
    IntPtr pNtlmCredential = IntPtr.Zero;
    uint cbNtlmCredential = 0;
    LsaEnumerateLogonSessions(out uint luidCount, out IntPtr pLogonSessionList);

Pros of pypykatz

• Written in Python, offering better cross-platform compatibility
• Supports multiple credential extraction methods beyond just memory dumping
• More actively maintained with frequent updates and improvements

Cons of pypykatz

• Larger codebase, potentially more complex to use and modify
• May have higher system resource requirements due to Python runtime

Code Comparison

mimipenguin:

#!/bin/bash
# Bash implementation for simple credential extraction
grep -R -i "password" /proc/*/environ 2>/dev/null

pypykatz:

from pypykatz.pypykatz import pypykatz

mimi = pypykatz.go_live()
for luid in mimi.logon_sessions:
    print(mimi.logon_sessions[luid])

Summary

pypykatz offers a more comprehensive and flexible approach to credential extraction, with broader platform support and active development. However, mimipenguin's simplicity and lightweight nature may be preferable in certain scenarios. pypykatz's Python implementation allows for more advanced features and easier integration with other tools, while mimipenguin's bash script is more straightforward for quick, targeted extractions on Linux systems.

Pros of lsassy

• Written in Python, making it more portable and easier to modify
• Supports remote dumping of credentials over the network
• Offers more extensive output options, including JSON and SQLite

Cons of lsassy

• Requires more dependencies and setup compared to mimipenguin
• May be slower in execution due to being written in Python rather than C

Code Comparison

mimipenguin (C):

void dump_from_binary(char *binary_path) {
    FILE *fp = fopen(binary_path, "rb");
    if (fp == NULL) {
        printf("Error opening file %s\n", binary_path);
        return;
    }
    // ... (rest of the function)
}

lsassy (Python):

def dump_lsass(self, dump_name=None, method="comsvcs"):
    if dump_name is None:
        dump_name = f"lsass_{random_string()}.dmp"
    dump_path = ntpath.join(self.temp_dir, dump_name)
    # ... (rest of the function)

Both projects aim to extract credentials from memory, but lsassy offers more flexibility and features at the cost of increased complexity. mimipenguin is simpler and potentially faster, but with fewer options for customization and remote capabilities.