README.md

metadata

language:
  - en
task_categories:
  - other
task_ids:
  - tabular-multi-class-classification
  - multi-class-classification
pretty_name: Honeypot Cybersecurity Dataset
size_categories:
  - 10K<n<100K
source_datasets:
  - original
license: bsd-3-clause
tags:
  - cybersecurity
  - honeypot
  - threat-intelligence
multilinguality:
  - monolingual
annotations_creators:
  - machine-generated
dataset_info:
  features:
    - name: dest_port
      dtype: int64
    - name: rdp
      dtype: float64
    - name: app_proto
      dtype: string
    - name: proto
      dtype: string
    - name: metadata
      dtype: string
    - name: tx_guessed
      dtype: bool
    - name: dest_ip
      dtype: string
    - name: '@version'
      dtype: int64
    - name: timestamp
      dtype: string
    - name: honeypot_ip_ext
      dtype: string
    - name: event_type
      dtype: string
    - name: pkt_src
      dtype: string
    - name: tx_id
      dtype: float64
    - name: geoip_ext
      dtype: string
    - name: geoip
      dtype: string
    - name: alert
      dtype: string
    - name: type
      dtype: string
    - name: in_iface
      dtype: string
    - name: '@timestamp'
      dtype: string
    - name: src_ip
      dtype: string
    - name: flow_id
      dtype: float64
    - name: src_port
      dtype: int64
    - name: direction
      dtype: string
    - name: host
      dtype: string
    - name: payload
      dtype: string
    - name: honeypot_hostname
      dtype: string
    - name: stream
      dtype: float64
    - name: payload_printable
      dtype: string
    - name: flow
      dtype: string
    - name: honeypot_ip_int
      dtype: string
    - name: tags
      dtype: float64
    - name: mitre_techniques
      dtype: string
    - name: attack_vectors
      dtype: string
    - name: mitre_tactic
      dtype: string
    - name: mitre_technique
      dtype: string
    - name: confidence_score
      dtype: float64
    - name: is_malicious
      dtype: bool
    - name: severity
      dtype: string
    - name: primary_label
      dtype: string
    - name: tcp
      dtype: string
    - name: subject
      dtype: string
    - name: uptime
      dtype: string
    - name: mod
      dtype: string
    - name: raw_freq
      dtype: string
    - name: raw_mtu
      dtype: float64
    - name: link
      dtype: string
    - name: params
      dtype: string
    - name: raw_sig
      dtype: string
    - name: dist
      dtype: float64
    - name: os
      dtype: string
    - name: ip_rep
      dtype: string
    - name: operation_mode
      dtype: float64
    - name: attack_connection
      dtype: string
    - name: end_time
      dtype: string
    - name: start_time
      dtype: string
    - name: download_tries
      dtype: float64
    - name: download_count
      dtype: float64
    - name: is_virtual
      dtype: bool
    - name: downloads
      dtype: string
    - name: proxy_connection
      dtype: string
    - name: reason
      dtype: string
    - name: raw_hits
      dtype: string
    - name: protocol
      dtype: string
    - name: action
      dtype: string
    - name: mstshash
      dtype: string
    - name: data
      dtype: string
    - name: fatt_rdp
      dtype: string
    - name: tls
      dtype: string
    - name: http
      dtype: float64
    - name: fileinfo
      dtype: float64
    - name: anomaly
      dtype: float64
    - name: files
      dtype: float64
    - name: fatt_tls
      dtype: float64
    - name: ssh
      dtype: float64
    - name: client
      dtype: float64
    - name: password
      dtype: float64
    - name: session
      dtype: float64
    - name: level
      dtype: float64
    - name: message
      dtype: float64
    - name: service
      dtype: float64
    - name: status
      dtype: float64
    - name: msg
      dtype: float64
    - name: username
      dtype: float64
    - name: fatt_ssh
      dtype: float64
    - name: lang
      dtype: float64
    - name: app
      dtype: float64
    - name: pgsql
      dtype: float64
    - name: input
      dtype: float64
    - name: output
      dtype: float64
    - name: environ
      dtype: float64
    - name: session_duration
      dtype: float64
    - name: smb
      dtype: float64
    - name: response.headers.Content-Type
      dtype: float64
    - name: response.metadata.provider
      dtype: float64
    - name: request.requestURI
      dtype: float64
    - name: request.method
      dtype: float64
    - name: request.headers.sortedSha256
      dtype: float64
    - name: response.body
      dtype: float64
    - name: response.metadata.temperature
      dtype: float64
    - name: response.headers.Server
      dtype: float64
    - name: request.body
      dtype: float64
    - name: request.headers.sorted
      dtype: float64
    - name: request.userAgent
      dtype: float64
    - name: hostname
      dtype: float64
    - name: response.metadata.generationSource
      dtype: float64
    - name: response.metadata.model
      dtype: float64
    - name: request.bodySha256
      dtype: float64
    - name: sensorName
      dtype: float64
    - name: request.protocol
      dtype: float64
    - name: fatt_http
      dtype: float64
    - name: commands
      dtype: float64
  splits:
    - name: train
      num_bytes: 189242
      num_examples: 100
  download_size: 65428
  dataset_size: 189242
config_name: default
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

network-intrusion-detection

Dataset Description

This dataset contains cybersecurity events collected from honeypot infrastructure.

The data has been processed and feature-engineered for machine learning applications in threat detection and security analytics.

Feature Categories

Network Features

• Connection flow statistics (bytes, packets, duration)
• Protocol-specific metrics
• Geographic information
• IP reputation data

Behavioral Features

• Session patterns and command sequences
• User-agent analysis
• Attack pattern identification
• Protocol fingerprinting

Temporal Features

• Time-based aggregations
• Frequency analysis
• Campaign detection indicators
• Attack timing patterns

Security Labels

• MITRE ATT&CK technique mappings
• Alert severity classifications
• Automatic threat categorization
• Binary maliciousness indicators

Usage Example

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("pyToshka/network-intrusion-detection")
train_data = dataset["train"]

# Basic exploration
print("Dataset features:", list(train_data.features.keys()))
print("Total samples:", len(train_data))

from collections import Counter

# Example: Filter RDP attacks
rdp_events = train_data.filter(lambda x: x['app_proto'] == 'rdp')
print("RDP events:", len(rdp_events))

# Example: Analyze attack vectors
if len(rdp_events) > 0:
    attack_vectors = Counter([event['attack_vectors'] for event in rdp_events if event['attack_vectors']])
    print("RDP Attack vectors:")
    for vector, count in attack_vectors.most_common():
        print(f"  {vector}: {count}")

# Example: Analyze protocol distribution
protocols = Counter([event['app_proto'] for event in train_data if event['app_proto']])
print("Protocol distribution:")
for proto, count in protocols.most_common():
    print(f"  {proto if proto else '(empty)'}: {count}")

# Example: Malicious events analysis
malicious_count = sum(1 for event in train_data if event['is_malicious'])
print(f"Malicious events: {malicious_count}/{len(train_data)} ({malicious_count/len(train_data)*100:.1f}%)")

Data Fields

The dataset contains 77 features across several categories:

Network Features

• dest_ip: Network-related information
• src_ip: Network-related information
• dest_port: Network-related information
• geoip_ext: Network-related information
• honeypot_ip_int: Network-related information
• ... and 7 more network features

Behavioral Features

• commands: Behavioral analysis data

Temporal Features

• @timestamp: Time-based information
• timestamp: Time-based information
• uptime: Time-based information

Security Features

• alert: Security and threat intelligence
• mitre_techniques: Security and threat intelligence
• attack_vectors: Security and threat intelligence
• mitre_tactic: Security and threat intelligence
• mitre_technique: Security and threat intelligence
• ... and 1 more security features

Data Splits

Split	Examples
train	29,545

Dataset Statistics

• Total size: ~139.0 MB
• Average record size: ~4932 bytes
• Feature completeness: 100.0%

Ethical Considerations

This dataset contains real honeypot data representing actual attack attempts. Users should:

• Privacy: Respect anonymization measures implemented in the dataset
• Research Use: Use data only for legitimate cybersecurity research and education
• Responsible Disclosure: Follow responsible disclosure practices for any findings
• Legal Compliance: Comply with applicable laws and regulations in your jurisdiction
• No Reidentification: Do not attempt to identify or contact attackers
• Defensive Purpose: Use insights for defensive security improvements only