Instructions to use Canstralian/CyberAttackDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Canstralian/CyberAttackDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Canstralian/CyberAttackDetection")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("Canstralian/CyberAttackDetection", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Create prompts.py
Browse files- prompts.py +19 -0
prompts.py
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PROMPTS = {
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"open_ports": (
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"Analyze the following network scan report and identify open ports and their associated vulnerabilities. "
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"Suggest best practices to secure these ports: [Insert network scan report]."
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),
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"outdated_software": (
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"Given this list of installed software and services, identify outdated versions and known vulnerabilities. "
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"Provide recommendations for updates or patches to mitigate risks: [Insert software and service list]."
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),
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"default_credentials": (
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"Scan the following system configurations for any use of default credentials. Provide a list of affected services "
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"and recommendations for securing these credentials: [Insert system configuration details]."
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),
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"misconfigurations": (
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"Evaluate the provided system configuration for potential misconfigurations. Highlight risks and provide "
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"recommendations for secure setup: [Insert system configuration details]."
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),
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# Add more prompts as necessary
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}
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