web_security/dataset_metadata.json

{
  "url_phishing_kaggle": {
    "name": "Malicious vs Benign URLs (Kaggle)",
    "description": "URLs classified as malicious or benign with extracted features",
    "urls": [
      "https://raw.githubusercontent.com/hex-plex/Malicious-URL-Classification/master/url_data.csv"
    ],
    "category": "phishing",
    "samples": 450000,
    "features": [
      "url",
      "url_length",
      "hostname_length",
      "path_length",
      "fd_length",
      "tld_count",
      "params_count",
      "fragment_count",
      "suspicious_words",
      "digits_ratio",
      "special_chars_ratio",
      "is_malicious"
    ],
    "target": "is_malicious",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:00.496780",
    "status": "available"
  },
  "phishing_websites_uci": {
    "name": "UCI Phishing Websites Dataset",
    "description": "30 features extracted from phishing and legitimate websites",
    "urls": [
      "https://raw.githubusercontent.com/shreyagopal/Phishing-Website-Detection-by-Machine-Learning-Techniques/master/dataset.csv"
    ],
    "category": "phishing",
    "samples": 11055,
    "features": [
      "having_ip",
      "url_length",
      "shortening_service",
      "having_at",
      "double_slash",
      "prefix_suffix",
      "sub_domain",
      "ssl_final_state",
      "domain_registration",
      "favicon",
      "port",
      "https_token",
      "result"
    ],
    "target": "result",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:00.843897",
    "status": "available"
  },
  "malware_pe_features": {
    "name": "PE Header Malware Features",
    "description": "Windows PE file features for malware classification",
    "urls": [
      "https://raw.githubusercontent.com/urwithajit9/ClaMP/master/dataset/malware.csv"
    ],
    "category": "malware",
    "samples": 4500,
    "features": [
      "md5",
      "file_size",
      "e_lfanew",
      "machine",
      "sections",
      "characteristics",
      "timestamp",
      "entry_point",
      "image_base",
      "subsystem",
      "dll_characteristics",
      "size_of_code",
      "size_of_init_data",
      "size_of_uninit_data",
      "legitimate"
    ],
    "target": "legitimate",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:01.006557",
    "status": "available"
  },
  "android_malware_drebin": {
    "name": "Android Malware (Drebin-style Features)",
    "description": "Android app permission features for malware detection",
    "urls": [
      "https://raw.githubusercontent.com/cloudhubs/static-malware-analysis/main/Data/android_data.csv"
    ],
    "category": "malware",
    "samples": 15000,
    "features": [
      "pkg_name",
      "permissions",
      "api_calls",
      "intents",
      "is_malware"
    ],
    "target": "is_malware",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:01.484651",
    "status": "available"
  },
  "cicids2017_ddos": {
    "name": "CICIDS 2017 DDoS Detection",
    "description": "Network flows with DDoS and benign traffic",
    "urls": [
      "https://raw.githubusercontent.com/AbdullahTarique/CICIDS-2017-Dataset/main/Sample/Friday-WorkingHours-Afternoon-DDos.csv"
    ],
    "category": "intrusion",
    "samples": 128000,
    "features": [
      "flow_duration",
      "total_fwd_packets",
      "total_bwd_packets",
      "flow_bytes_s",
      "flow_packets_s",
      "avg_packet_size",
      "label"
    ],
    "target": "label",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:01.913481",
    "status": "available"
  },
  "nsl_kdd_train": {
    "name": "NSL-KDD Network Intrusion",
    "description": "Improved KDD Cup 99 dataset for network intrusion detection",
    "urls": [
      "https://raw.githubusercontent.com/defcom17/NSL_KDD/master/KDDTrain%2B.txt"
    ],
    "category": "intrusion",
    "samples": 125973,
    "features": [
      "duration",
      "protocol_type",
      "service",
      "flag",
      "src_bytes",
      "dst_bytes",
      "land",
      "wrong_fragment",
      "urgent",
      "hot",
      "num_failed_logins",
      "logged_in",
      "num_compromised",
      "attack_type"
    ],
    "target": "attack_type",
    "format": "txt",
    "downloaded_at": "2026-01-29T16:35:02.373654",
    "status": "available"
  },
  "unsw_nb15": {
    "name": "UNSW-NB15 Network Dataset",
    "description": "Modern network intrusion dataset with 9 attack types",
    "urls": [
      "https://raw.githubusercontent.com/jmnwong/UNSW-NB15/master/UNSW-NB15_1.csv"
    ],
    "category": "intrusion",
    "samples": 175000,
    "features": [
      "srcip",
      "sport",
      "dstip",
      "dsport",
      "proto",
      "state",
      "dur",
      "sbytes",
      "dbytes",
      "sttl",
      "dttl",
      "attack_cat",
      "label"
    ],
    "target": "label",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:02.792570",
    "status": "available"
  },
  "ipsum_malicious_ips": {
    "name": "IPsum Malicious IPs",
    "description": "Daily updated list of malicious IP addresses",
    "urls": [
      "https://raw.githubusercontent.com/stamparm/ipsum/master/ipsum.txt"
    ],
    "category": "threat_intel",
    "samples": 25000,
    "features": [
      "ip_address",
      "threat_level"
    ],
    "target": "threat_level",
    "format": "txt",
    "downloaded_at": "2026-01-29T16:35:03.526227",
    "status": "available"
  },
  "feodotracker_botnet": {
    "name": "Feodo Tracker Botnet C2",
    "description": "Botnet Command & Control server IPs",
    "urls": [
      "https://feodotracker.abuse.ch/downloads/ipblocklist.csv"
    ],
    "category": "threat_intel",
    "samples": 5000,
    "features": [
      "first_seen",
      "dst_ip",
      "dst_port",
      "malware",
      "status"
    ],
    "target": "malware",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:03.907662",
    "status": "available"
  },
  "urlhaus_malicious": {
    "name": "URLhaus Malicious URLs",
    "description": "Database of malware distribution URLs",
    "urls": [
      "https://urlhaus.abuse.ch/downloads/csv_recent/"
    ],
    "category": "threat_intel",
    "samples": 10000,
    "features": [
      "dateadded",
      "url",
      "url_status",
      "threat",
      "tags",
      "urlhaus_link"
    ],
    "target": "threat",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:04.832782",
    "status": "available"
  },
  "spambase_uci": {
    "name": "UCI Spambase",
    "description": "Email spam classification with word frequencies",
    "urls": [
      "https://archive.ics.uci.edu/ml/machine-learning-databases/spambase/spambase.data"
    ],
    "category": "spam",
    "samples": 4601,
    "features": [
      "word_freq_make",
      "word_freq_address",
      "word_freq_all",
      "char_freq_semicolon",
      "char_freq_dollar",
      "capital_run_avg",
      "capital_run_longest",
      "capital_run_total",
      "is_spam"
    ],
    "target": "is_spam",
    "format": "data",
    "downloaded_at": "2026-01-29T16:35:05.124845",
    "status": "available"
  },
  "xss_payloads": {
    "name": "XSS Attack Payloads",
    "description": "Cross-site scripting attack patterns",
    "urls": [
      "https://raw.githubusercontent.com/payloadbox/xss-payload-list/master/Intruder/xss-payload-list.txt"
    ],
    "category": "web_attack",
    "samples": 5000,
    "features": [
      "payload",
      "type"
    ],
    "target": "type",
    "format": "txt",
    "downloaded_at": "2026-01-29T16:35:05.293648",
    "status": "available"
  },
  "sql_injection_payloads": {
    "name": "SQL Injection Payloads",
    "description": "SQL injection attack patterns",
    "urls": [
      "https://raw.githubusercontent.com/payloadbox/sql-injection-payload-list/master/Intruder/SQL-Injection-Payloads/Auth-Bypass.txt",
      "https://raw.githubusercontent.com/payloadbox/sql-injection-payload-list/master/Intruder/SQL-Injection-Payloads/Error-Based.txt"
    ],
    "category": "web_attack",
    "samples": 3000,
    "features": [
      "payload",
      "injection_type"
    ],
    "target": "injection_type",
    "format": "txt",
    "downloaded_at": "2026-01-29T16:35:05.501629",
    "status": "available"
  },
  "http_csic_requests": {
    "name": "HTTP CSIC 2010 Dataset",
    "description": "HTTP requests with web attacks (XSS, SQLi, etc.)",
    "urls": [
      "https://raw.githubusercontent.com/Morzeux/HttpRequestsDataset/master/csic_http/csic_2010_cleaned.csv"
    ],
    "category": "web_attack",
    "samples": 36000,
    "features": [
      "method",
      "url",
      "protocol",
      "content",
      "is_attack"
    ],
    "target": "is_attack",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:05.724490",
    "status": "available"
  },
  "cryptomining_scripts": {
    "name": "Cryptomining Script Detection",
    "description": "JavaScript cryptomining patterns",
    "urls": [
      "https://raw.githubusercontent.com/ArslanKhan-cs/JSMiner/main/data/cryptominer.csv"
    ],
    "category": "cryptomining",
    "samples": 5000,
    "features": [
      "script_hash",
      "obfuscated",
      "api_calls",
      "is_miner"
    ],
    "target": "is_miner",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:05.924379",
    "status": "available"
  },
  "dga_domains": {
    "name": "DGA Domain Detection",
    "description": "Domain Generation Algorithm detection dataset",
    "urls": [
      "https://raw.githubusercontent.com/baderj/domain_generation_algorithms/master/dga_db/export/dga_domains_sample.csv"
    ],
    "category": "dns",
    "samples": 50000,
    "features": [
      "domain",
      "family",
      "length",
      "entropy",
      "consonant_ratio",
      "is_dga"
    ],
    "target": "is_dga",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:06.692993",
    "status": "available"
  },
  "ssl_certificates": {
    "name": "SSL Certificate Analysis",
    "description": "SSL certificate features for malicious detection",
    "urls": [
      "https://raw.githubusercontent.com/JustinGuese/ML-Security-SSL-Phishing/master/data/SSL-phishing.csv"
    ],
    "category": "ssl",
    "samples": 8000,
    "features": [
      "cert_issuer",
      "cert_validity",
      "domain_match",
      "is_ev",
      "cipher_strength",
      "is_phishing"
    ],
    "target": "is_phishing",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:06.841582",
    "status": "available"
  },
  "system_logs_hdfs": {
    "name": "HDFS System Logs",
    "description": "Hadoop system logs for anomaly detection",
    "urls": [
      "https://raw.githubusercontent.com/logpai/loghub/master/HDFS/HDFS.log_structured.csv"
    ],
    "category": "logs",
    "samples": 11000,
    "features": [
      "timestamp",
      "level",
      "component",
      "content",
      "event_template"
    ],
    "target": "level",
    "format": "csv",
    "downloaded_at": "2026-01-29T16:35:07.926689",
    "status": "available"
  }
}