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---
language:
- en
task_categories:
- other
task_ids:
- tabular-multi-class-classification
- multi-class-classification
pretty_name: Honeypot Cybersecurity Dataset
size_categories:
- 100K<n<1M
source_datasets:
- original
license: bsd-3-clause
tags:
- cybersecurity
- honeypot
- threat-intelligence
multilinguality:
- monolingual
annotations_creators:
- machine-generated
dataset_info:
features:
- name: honeypot_hostname
dtype: string
- name: geoip
dtype: string
- name: dest_port
dtype: int64
- name: src_ip
dtype: string
- name: honeypot_ip_int
dtype: string
- name: event_type
dtype: string
- name: timestamp
dtype: string
- name: in_iface
dtype: string
- name: pkt_src
dtype: string
- name: '@timestamp'
dtype: string
- name: type
dtype: string
- name: honeypot_ip_ext
dtype: string
- name: dest_ip
dtype: string
- name: src_port
dtype: string
- name: rdp
dtype: string
- name: '@version'
dtype: string
- name: host
dtype: string
- name: flow_id
dtype: string
- name: tags
dtype: string
- name: geoip_ext
dtype: string
- name: proto
dtype: string
- name: mitre_techniques
dtype: string
- name: attack_vectors
dtype: string
- name: mitre_tactic
dtype: string
- name: mitre_technique
dtype: string
- name: confidence_score
dtype: string
- name: is_malicious
dtype: bool
- name: severity
dtype: string
- name: primary_label
dtype: string
- name: metadata
dtype: string
- name: os
dtype: string
- name: raw_sig
dtype: string
- name: subject
dtype: string
- name: mod
dtype: string
- name: dist
dtype: string
- name: params
dtype: string
- name: direction
dtype: string
- name: stream
dtype: string
- name: tx_id
dtype: string
- name: app_proto
dtype: string
- name: alert
dtype: string
- name: payload_printable
dtype: string
- name: flow
dtype: string
- name: payload
dtype: string
- name: tx_guessed
dtype: string
- name: tcp
dtype: string
- name: ip_rep
dtype: string
- name: attack_connection
dtype: string
- name: operation_mode
dtype: string
- name: end_time
dtype: string
- name: proxy_connection
dtype: string
- name: download_tries
dtype: string
- name: is_virtual
dtype: string
- name: download_count
dtype: string
- name: downloads
dtype: string
- name: start_time
dtype: string
- name: fatt_tls
dtype: string
- name: protocol
dtype: string
- name: link
dtype: string
- name: raw_mtu
dtype: string
- name: msg
dtype: string
- name: message
dtype: string
- name: session
dtype: string
- name: status
dtype: string
- name: session_duration
dtype: float64
- name: level
dtype: string
- name: username
dtype: string
- name: action
dtype: string
- name: password
dtype: string
- name: service
dtype: string
- name: client
dtype: string
- name: mstshash
dtype: string
- name: data
dtype: string
- name: tls
dtype: string
- name: fatt_rdp
dtype: string
- name: raw_hits
dtype: string
- name: reason
dtype: string
- name: input
dtype: string
- name: client_version
dtype: string
- name: environ
dtype: string
- name: ssh
dtype: string
- name: raw_freq
dtype: string
- name: uptime
dtype: string
- name: fileinfo
dtype: string
- name: http
dtype: string
- name: fatt_ssh
dtype: string
- name: output
dtype: string
- name: smb
dtype: string
- name: lang
dtype: string
- name: app
dtype: string
- name: ftp
dtype: string
- name: files
dtype: string
- name: anomaly
dtype: string
- name: fatt_http
dtype: string
- name: smtp
dtype: string
- name: app_proto_tc
dtype: string
- name: app_proto_ts
dtype: string
- name: response.metadata.provider
dtype: string
- name: request.headers.Accept
dtype: string
- name: request.headers.User-Agent
dtype: string
- name: request.protocol
dtype: string
- name: hostname
dtype: string
- name: request.headers.sorted
dtype: string
- name: request.bodySha256
dtype: string
- name: request.headers.Content-Type
dtype: string
- name: response.metadata.temperature
dtype: string
- name: response.metadata.model
dtype: string
- name: response.metadata.generationSource
dtype: string
- name: request.headers.Connection
dtype: string
- name: request.method
dtype: string
- name: request.requestURI
dtype: string
- name: sensorName
dtype: string
- name: response.body
dtype: string
- name: request.headers.X-Requested-With
dtype: string
- name: request.body
dtype: string
- name: request.headers.Accept-Language
dtype: string
- name: request.headers.Accept-Encoding
dtype: string
- name: request.headers.sortedSha256
dtype: string
- name: response.headers.Content-Type
dtype: string
- name: request.userAgent
dtype: string
- name: response.headers.Server
dtype: string
- name: request.headers.X-Support-Http-Auth
dtype: string
- name: request.headers.X-Transcend-Version
dtype: string
- name: response.headers.X-Powered-By
dtype: string
- name: duration
dtype: string
- name: eventid
dtype: string
- name: sensor
dtype: string
- name: icmp_type
dtype: string
- name: icmp_code
dtype: string
- name: user-agent_os
dtype: string
- name: user-agent
dtype: string
- name: header_user-agent
dtype: string
- name: trapped
dtype: string
- name: header_connection
dtype: string
- name: user-agent_browser_version
dtype: string
- name: request_uri
dtype: string
- name: header_accept
dtype: string
- name: request_method
dtype: string
- name: header_accept-encoding
dtype: string
- name: header_accept-language
dtype: string
- name: user-agent_browser
dtype: string
- name: user-agent_os_version
dtype: string
- name: user-agent_device_brand
dtype: string
- name: user-agent_device_model
dtype: string
- name: response.headers.Connection
dtype: string
- name: outfile
dtype: string
- name: shasum
dtype: string
- name: filename
dtype: string
- name: src_url
dtype: string
- name: request.headers.Origin
dtype: string
- name: request.headers.Upgrade-Insecure-Requests
dtype: string
- name: id
dtype: string
- name: version
dtype: string
- name: request
dtype: string
- name: sensorid
dtype: string
- name: response
dtype: string
- name: public_ip
dtype: string
- name: data_type
dtype: string
- name: request.headers.Referer
dtype: string
- name: request.headers.Accept-Charset
dtype: string
- name: response.headers.Date
dtype: string
- name: response.headers.Content-Length
dtype: string
- name: caller
dtype: string
- name: device_brand
dtype: string
- name: os_version
dtype: string
- name: qs
dtype: string
- name: browser_version
dtype: string
- name: user_agent
dtype: string
- name: method
dtype: string
- name: browser
dtype: string
- name: device
dtype: string
- name: phase
dtype: string
- name: header_content-length
dtype: string
- name: header_content-type
dtype: string
- name: collected_method
dtype: string
- name: app_version
dtype: string
- name: app_name
dtype: string
- name: sip_method
dtype: string
- name: created_by_node_id
dtype: string
- name: sip_message
dtype: string
- name: transport_type
dtype: string
- name: event_uuid
dtype: string
- name: sip_user_agent
dtype: string
- name: called_number
dtype: string
- name: request.headers.Cache-Control
dtype: string
- name: request.headers.Pragma
dtype: string
- name: trapped_for
dtype: string
- name: dnp3
dtype: string
- name: commands
dtype: string
splits:
- name: train
num_bytes: 2906010096
num_examples: 243181
download_size: 2906010096
dataset_size: 2906010096
config_name: default
---
# attacks-monthly
## 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
```python
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("pyToshka/attacks-monthly")
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 189 features across several categories:
### Network Features
- `geoip`: Network-related information
- `dest_port`: Network-related information
- `src_ip`: Network-related information
- `honeypot_ip_int`: Network-related information
- `honeypot_ip_ext`: Network-related information
- ... and 14 more network features
### Behavioral Features
- `session`: Behavioral analysis data
- `session_duration`: Behavioral analysis data
- `username`: Behavioral analysis data
- `request.headers.User-Agent`: Behavioral analysis data
- `request.userAgent`: Behavioral analysis data
- ... and 12 more behavioral features
### Temporal Features
- `timestamp`: Time-based information
- `@timestamp`: Time-based information
- `end_time`: Time-based information
- `start_time`: Time-based information
- `session_duration`: Time-based information
- ... and 3 more temporal features
### Security Features
- `mitre_techniques`: Security and threat intelligence
- `attack_vectors`: Security and threat intelligence
- `mitre_tactic`: Security and threat intelligence
- `mitre_technique`: Security and threat intelligence
- `is_malicious`: Security and threat intelligence
- ... and 2 more security features
## Data Splits
| Split | Examples |
|-------|----------|
| train | 243,181 |
## Dataset Statistics
- **Total size**: ~2771.4 MB
- **Average record size**: ~11950 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
|