a-pandas-ex-memorydump-to-df


Namea-pandas-ex-memorydump-to-df JSON
Version 0.11 PyPI version JSON
download
home_pagehttps://github.com/hansalemaos/a_pandas_ex_memorydump_to_df
SummaryLoad a ProcDump memory dump into a Pandas DataFrame
upload_time2022-12-27 00:56:32
maintainer
docs_urlNone
authorJohannes Fischer
requires_python
licenseMIT
keywords hacking debug debugging
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            
<h1>ProcDump memory dump to Pandas DataFrame</h1>



```python



# Download ProcDump: https://learn.microsoft.com/pt-br/sysinternals/downloads/procdump

# I had to make some changes to winappdbg

# If you get an Exception, download https://github.com/hansalemaos/a_pandas_ex_memorydump_to_df/blob/main/winappdbg.zip

# and overwrite all files in Lib\site-packages\winappdbg



$pip install a-pandas-ex-memorydump-to-df



import pandas as pd

from a_pandas_ex_memorydump_to_df import pd_add_memorydf

pd_add_memorydf()



df = pd.Q_df_from_memory(

    pid=9132, procdumppath=r"C:\Program Files\procdump.exe", with_utf8_bytes=False

)  # with_utf8_bytes=True takes much more time!





The method will convert all bytes to every possible format which means, the DataFrame 

might get huge. 







# Notepad.exe

#       aa_address1_hex aa_address2_hex  ...  aa_ascii_int_63  aa_ascii_int_66

# 0            00000000        00010000  ...               46               46

# 1            00000000        00010010  ...               46               46

# 2            00000000        00010020  ...               46               46

# 3            00000000        00010030  ...               46               46

# 4            00000000        00010040  ...               46               46

#                ...             ...  ...              ...              ...

# 64014        00007ff5        fffb0fc0  ...               46               46

# 64015        00007ff5        fffb0fd0  ...               46               46

# 64016        00007ff5        fffb0fe0  ...               46               46

# 64017        00007ff5        fffb0ff0  ...               46               46

# 64018        00007ff5        fffb1000  ...                0                0

# [64019 rows x 304 columns]



# df.size

# Out[16]: 19461776



# explorer.exe

# df

# Out[10]:

#         aa_address1_hex aa_address2_hex  ...  aa_ascii_int_63  aa_ascii_int_66

# 0              00000000        00010000  ...               46               46

# 1              00000000        00010010  ...               46               46

# 2              00000000        00010020  ...               46               46

# 3              00000000        00010030  ...               46               46

# 4              00000000        00010040  ...               46               46

#                  ...             ...  ...              ...              ...

# 3234712        00007ff5        fffb0fc0  ...               46               46

# 3234713        00007ff5        fffb0fd0  ...               46               46

# 3234714        00007ff5        fffb0fe0  ...               46               46

# 3234715        00007ff5        fffb0ff0  ...               46               46

# 3234716        00007ff5        fffb1000  ...                0                0

#

# [3234717 rows x 304 columns]

#

# df.size

# Out[11]: 983353968



# Location of the temp file (procdump)

# df.tmp_file_path

# Out[14]: 'C:\\Users\\Gamer\\AppData\\Local\\Temp\\tmpsypcc1g5.dmp'

# df.tmp_delete_file()  $ file must be closed before



```



### Let's compare the converted values with the ones from CheatEngine



<img title="" src="https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000001.png" alt="">



<img title="" src="https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000002.png" alt="">



<img title="" src="https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000003.png" alt="">



<img title="" src="https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000004.png" alt="">



<img title="" src="https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000005.png" alt="">



<img title="" src="https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000006.png" alt="">



<img title="" src="https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000007.png" alt="">



<img title="" src="https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000008.png" alt="">

            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/hansalemaos/a_pandas_ex_memorydump_to_df",
    "name": "a-pandas-ex-memorydump-to-df",
    "maintainer": "",
    "docs_url": null,
    "requires_python": "",
    "maintainer_email": "",
    "keywords": "hacking,debug,debugging",
    "author": "Johannes Fischer",
    "author_email": "<aulasparticularesdealemaosp@gmail.com>",
    "download_url": "https://files.pythonhosted.org/packages/6a/e5/6327980bff9a2218eda4db7b29065eb1ddc189d9b74b19950617d2119e36/a_pandas_ex_memorydump_to_df-0.11.tar.gz",
    "platform": null,
    "description": "\n<h1>ProcDump memory dump to Pandas DataFrame</h1>\n\n\n\n```python\n\n\n\n# Download ProcDump: https://learn.microsoft.com/pt-br/sysinternals/downloads/procdump\n\n# I had to make some changes to winappdbg\n\n# If you get an Exception, download https://github.com/hansalemaos/a_pandas_ex_memorydump_to_df/blob/main/winappdbg.zip\n\n# and overwrite all files in Lib\\site-packages\\winappdbg\n\n\n\n$pip install a-pandas-ex-memorydump-to-df\n\n\n\nimport pandas as pd\n\nfrom a_pandas_ex_memorydump_to_df import pd_add_memorydf\n\npd_add_memorydf()\n\n\n\ndf = pd.Q_df_from_memory(\n\n    pid=9132, procdumppath=r\"C:\\Program Files\\procdump.exe\", with_utf8_bytes=False\n\n)  # with_utf8_bytes=True takes much more time!\n\n\n\n\n\nThe method will convert all bytes to every possible format which means, the DataFrame \n\nmight get huge. \n\n\n\n\n\n\n\n# Notepad.exe\n\n#       aa_address1_hex aa_address2_hex  ...  aa_ascii_int_63  aa_ascii_int_66\n\n# 0            00000000        00010000  ...               46               46\n\n# 1            00000000        00010010  ...               46               46\n\n# 2            00000000        00010020  ...               46               46\n\n# 3            00000000        00010030  ...               46               46\n\n# 4            00000000        00010040  ...               46               46\n\n#                ...             ...  ...              ...              ...\n\n# 64014        00007ff5        fffb0fc0  ...               46               46\n\n# 64015        00007ff5        fffb0fd0  ...               46               46\n\n# 64016        00007ff5        fffb0fe0  ...               46               46\n\n# 64017        00007ff5        fffb0ff0  ...               46               46\n\n# 64018        00007ff5        fffb1000  ...                0                0\n\n# [64019 rows x 304 columns]\n\n\n\n# df.size\n\n# Out[16]: 19461776\n\n\n\n# explorer.exe\n\n# df\n\n# Out[10]:\n\n#         aa_address1_hex aa_address2_hex  ...  aa_ascii_int_63  aa_ascii_int_66\n\n# 0              00000000        00010000  ...               46               46\n\n# 1              00000000        00010010  ...               46               46\n\n# 2              00000000        00010020  ...               46               46\n\n# 3              00000000        00010030  ...               46               46\n\n# 4              00000000        00010040  ...               46               46\n\n#                  ...             ...  ...              ...              ...\n\n# 3234712        00007ff5        fffb0fc0  ...               46               46\n\n# 3234713        00007ff5        fffb0fd0  ...               46               46\n\n# 3234714        00007ff5        fffb0fe0  ...               46               46\n\n# 3234715        00007ff5        fffb0ff0  ...               46               46\n\n# 3234716        00007ff5        fffb1000  ...                0                0\n\n#\n\n# [3234717 rows x 304 columns]\n\n#\n\n# df.size\n\n# Out[11]: 983353968\n\n\n\n# Location of the temp file (procdump)\n\n# df.tmp_file_path\n\n# Out[14]: 'C:\\\\Users\\\\Gamer\\\\AppData\\\\Local\\\\Temp\\\\tmpsypcc1g5.dmp'\n\n# df.tmp_delete_file()  $ file must be closed before\n\n\n\n```\n\n\n\n### Let's compare the converted values with the ones from CheatEngine\n\n\n\n<img title=\"\" src=\"https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000001.png\" alt=\"\">\n\n\n\n<img title=\"\" src=\"https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000002.png\" alt=\"\">\n\n\n\n<img title=\"\" src=\"https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000003.png\" alt=\"\">\n\n\n\n<img title=\"\" src=\"https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000004.png\" alt=\"\">\n\n\n\n<img title=\"\" src=\"https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000005.png\" alt=\"\">\n\n\n\n<img title=\"\" src=\"https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000006.png\" alt=\"\">\n\n\n\n<img title=\"\" src=\"https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000007.png\" alt=\"\">\n\n\n\n<img title=\"\" src=\"https://github.com/hansalemaos/screenshots/raw/main/debugdf/debugdf_00000008.png\" alt=\"\">\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "Load a ProcDump memory dump into a Pandas DataFrame",
    "version": "0.11",
    "split_keywords": [
        "hacking",
        "debug",
        "debugging"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "b35e729c855f99cc2a115714107b70b6",
                "sha256": "a885450697e4fce25c2a16b381835d37b1a154edc88b877ca25958c653f63b8a"
            },
            "downloads": -1,
            "filename": "a_pandas_ex_memorydump_to_df-0.11-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "b35e729c855f99cc2a115714107b70b6",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 9982,
            "upload_time": "2022-12-27T00:56:31",
            "upload_time_iso_8601": "2022-12-27T00:56:31.286661Z",
            "url": "https://files.pythonhosted.org/packages/80/73/e36daeccc68247b32e0176b8f5d7c4e0f02c8ca03331bea63efd6a6d3c5e/a_pandas_ex_memorydump_to_df-0.11-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "md5": "62761942c9d7ecd72811ecd445266157",
                "sha256": "e45c9b3d17a2088b67f1cbff1b7579a662b5bd67bd7c7b6036a1c37074b68d23"
            },
            "downloads": -1,
            "filename": "a_pandas_ex_memorydump_to_df-0.11.tar.gz",
            "has_sig": false,
            "md5_digest": "62761942c9d7ecd72811ecd445266157",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 9094,
            "upload_time": "2022-12-27T00:56:32",
            "upload_time_iso_8601": "2022-12-27T00:56:32.671666Z",
            "url": "https://files.pythonhosted.org/packages/6a/e5/6327980bff9a2218eda4db7b29065eb1ddc189d9b74b19950617d2119e36/a_pandas_ex_memorydump_to_df-0.11.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2022-12-27 00:56:32",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "github_user": "hansalemaos",
    "github_project": "a_pandas_ex_memorydump_to_df",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "requirements": [],
    "lcname": "a-pandas-ex-memorydump-to-df"
}
        
Elapsed time: 0.07832s