@@ -26,8 +26,8 @@ save_preferences = true
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[System Settings]
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# Do not play with these settings unless you know what you are doing
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# Dev Mode allows a safe way to modify these settings!!
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- version = 3.5.1
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- files = " bluetooth_details.py, bluetooth_logger.py, browser_miner.ps1, cmd_commands.py, config.ini, dir_list.py, dump_memory.py, event_log.py, Logicytics.py, log_miner.py, media_backup.py, netadapter.ps1, network_psutil.py, packet_sniffer.py, property_scraper.ps1, registry.py, sensitive_data_miner.py, ssh_miner.py, sys_internal.py, tasklist.py, tree.ps1, vulnscan.py, wifi_stealer.py, window_feature_miner.ps1, wmic.py, logicytics\Checks.py, logicytics\Config.py, logicytics\Execute.py, logicytics\FileManagement.py, logicytics\Flag.py, logicytics\Get.py, logicytics\Logger.py, logicytics\User_History.json.gz, vulnscan\SenseMini.3n3 .pth, vulnscan\vectorizer.3n3.pkl "
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+ version = 3.6.0
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+ files = " bluetooth_details.py, bluetooth_logger.py, browser_miner.ps1, cmd_commands.py, config.ini, dir_list.py, dump_memory.py, encrypted_drive_audit.py, event_log.py, Logicytics.py, log_miner.py, media_backup.py, netadapter.ps1, network_psutil.py, packet_sniffer.py, property_scraper.ps1, registry.py, sensitive_data_miner.py, ssh_miner.py, sys_internal.py, tasklist.py, tree.ps1, usb_history.py, vulnscan.py, wifi_stealer.py, window_feature_miner.ps1, wmic.py, logicytics\Checks.py, logicytics\Config.py, logicytics\Execute.py, logicytics\FileManagement.py, logicytics\Flag.py, logicytics\Get.py, logicytics\Logger.py, logicytics\User_History.json.gz, vulnscan\Model_SenseMacro.4n1 .pth"
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# If you forked the project, change the USERNAME to your own to use your own fork as update material,
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# I dont advise doing this however
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config_url = https://raw.githubusercontent.com/DefinetlyNotAI/Logicytics/main/CODE/config.ini
@@ -100,93 +100,15 @@ timeout = 10
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max_retry_time = 30
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# ##################################################
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+
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[VulnScan Settings]
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- # Following extensions to be skipped by the model
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- # Format: comma-separated list with dots (e.g., .exe, .dll)
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- unreadable_extensions = .exe, .dll, .so, .zip, .tar, .gz, .7z, .rar, .jpg, .jpeg, .png, .gif, .bmp, .tiff, .webp, .mp3, .wav, .flac, .aac, .ogg, .mp4, .mkv, .avi, .mov, .wmv, .flv, .pdf, .doc, .docx, .xls, .xlsx, .ppt, .pptx, .odt, .ods, .odp, .bin, .dat, .iso, .class, .pyc, .o, .obj, .sqlite, .db, .ttf, .otf, .woff, .woff2, .lnk, .url
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- # In MB, max file size that the model is allowed to scan, if commented out disables the limit, you can also just say None
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- max_file_size_mb = None
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- # Max workers to be used, either integer or use auto to make it decide the best value
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+ # Max characters of text from each file to analyze. Set an integer or None to disable truncation.
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+ text_char_limit = None
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+ # Max workers to be used, either integer or use "auto" to make it decide the best value
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max_workers = auto
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-
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- [VulnScan.generate Settings]
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- # The following settings are for the Generate module for fake training data
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- extensions = .txt, .log, .md, .csv, .json, .xml, .html, .yaml, .ini, .pdf, .docx, .xlsx, .pptx
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- save_path = PATH
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-
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- # Options include:
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- # 'Sense' - Generates 50k files, each 25KB in size.
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- # 'SenseNano' - Generates 5 files, each 5KB in size.
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- # 'SenseMacro' - Generates 1m files, each 10KB in size.
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- # 'SenseMini' - Generates 10k files, each 10KB in size.
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- # 'SenseCustom' - Uses custom size settings from the configuration file.
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- code_name = SenseMini
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-
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- # This allows more randomness in the file sizes, use 0 to disable
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- # this is applied randomly every time a file is generated
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- # Variation is applied in the following way:
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- # size +- (size */ variation) where its random weather to add or subtract and divide or multiply
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- size_variation = 0.1
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-
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- # Set to SenseCustom to use below size settings
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- min_file_size = 5KB
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- max_file_size = 50KB
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-
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- # Chances for the following data types in files:
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- # 0.0 - 1.0, the rest will be for pure data
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- full_sensitive_chance = 0.07
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- partial_sensitive_chance = 0.2
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-
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- [VulnScan.vectorizer Settings]
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- # The following settings are for the Vectorizer module for vectorizing data
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- # Usually it automatically vectorizes data, but this is for manual vectorization
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-
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- # We advise to use this vectorization, although not knowing the vectorizer is not advised
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- # as this may lead to ValueErrors due to different inputs
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- # Use the vectorizer supplied for any v3 model on SenseMini
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-
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- # The path to the data to vectorize, either a file or a directory
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- data_path = PATH
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- # The path to save the vectorized data - It will automatically be appended '\Vectorizer.pkl'
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- # Make sure the path is a directory, and it exists
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- output_path = PATH
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-
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- # Vectorizer to use, options include:
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- # tfidf or count - The code for the training only supports tfidf - we advise to use tfidf
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- vectorizer_type = tfidf
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-
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- [VulnScan.train Settings]
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- # The following settings are for the Train module for training models
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- # NeuralNetwork seems to be the best choice for this task
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- # Options: "NeuralNetwork", "LogReg",
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- # "RandomForest", "ExtraTrees", "GBM",
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- # "XGBoost", "DecisionTree", "NaiveBayes"
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- model_name = NeuralNetwork
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-
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- # General Training Parameters
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- epochs = 10
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- batch_size = 32
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- learning_rate = 0.001
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- use_cuda = true
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-
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- # Paths to train and save data
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- train_data_path = PATH
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- # If all models are to be trained, this is the path to save all models,
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- # and will be appended with the model codename and follow naming convention
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- save_model_path = PATH
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-
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- [VulnScan.study Settings]
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- # Here is the basics of the study module
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- # This is useful to generate graphs and data that may help in understanding the model
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- # Everything is found online pre-studied, so this is not necessary
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- # But it is useful for understanding the model locally
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- # All files be saved here, and can't be changed, PATH is "NN features/"
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-
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- # This is the path to the model, and the vectorizer
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- model_path = PATH
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- vectorizer_path = PATH
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- # Number of features to visualise in the SVG Bar graph, maximum is 3000 due to limitations
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- # Placing -1 will visualise first 3000 features. Bar will be a color gradient heatmap.
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- number_of_features = -1
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+ # Sensitivity threshold (0.0–1.0) for the model to flag content as sensitive
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+ threshold = 0.6
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+ # Paths for required files
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+ model = vulnscan/Model_SenseMacro.4n1.pth
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# #################################################
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