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repo_id
stringlengths
15
44
security_score
int64
0
184
risk_level
stringclasses
4 values
total_warnings
int64
0
67
critical_count
int64
0
0
high_count
int64
0
3
medium_count
int64
0
3
low_count
int64
0
66
scan_date
stringdate
2025-12-15 02:45:52
2025-12-16 10:23:59
palisade_version
stringclasses
1 value
model_url
stringlengths
38
67
threat_categories
stringclasses
7 values
policy_compliance
stringclasses
1 value
top_validators
stringclasses
7 values
mitre_techniques
stringclasses
2 values
google/gemma-3-270m-it
0
safe
0
0
0
0
0
2025-12-15T02:45:52.194529
0.4.0
https://huggingface.co/google/gemma-3-270m-it
{}
{}
[]
[]
matrixportalx/Llama-2-7b-chat-hf-Q4_K_M-GGUF
184
high
8
0
3
3
2
2025-12-15T03:58:52.761612
0.4.0
https://huggingface.co/matrixportalx/Llama-2-7b-chat-hf-Q4_K_M-GGUF
{"buffer_overflow": 3, "model_integrity": 1, "behavior_analysis": 1, "gguf_safety": 2, "tool_call_security": 1}
{}
[{"name": "BufferOverflowValidator", "count": 3}, {"name": "GGUFSafetyValidator", "count": 2}, {"name": "ModelIntegrityValidator", "count": 1}, {"name": "BehaviorAnalysisValidator", "count": 1}, {"name": "ToolCallSecurityValidator", "count": 1}]
["AML.T0051.002"]
sentence-transformers/all-MiniLM-L6-v2
52
medium
2
0
1
0
1
2025-12-16T09:56:30.009045
0.4.0
https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2
{"buffer_overflow": 2}
{}
[{"name": "BufferOverflowValidator", "count": 2}]
[]
sentence-transformers/all-mpnet-base-v2
12
low
2
0
0
1
1
2025-12-16T09:56:38.382227
0.4.0
https://huggingface.co/sentence-transformers/all-mpnet-base-v2
{"buffer_overflow": 2}
{}
[{"name": "BufferOverflowValidator", "count": 2}]
[]
BAAI/bge-small-en-v1.5
0
safe
0
0
0
0
0
2025-12-16T09:56:42.575240
0.4.0
https://huggingface.co/BAAI/bge-small-en-v1.5
{}
{}
[]
[]
BAAI/bge-base-en-v1.5
0
safe
0
0
0
0
0
2025-12-16T09:56:57.875568
0.4.0
https://huggingface.co/BAAI/bge-base-en-v1.5
{}
{}
[]
[]
microsoft/phi-2
22
low
7
0
0
1
6
2025-12-16T09:59:02.416238
0.4.0
https://huggingface.co/microsoft/phi-2
{"buffer_overflow": 4, "backdoor": 3}
{}
[{"name": "BufferOverflowValidator", "count": 4}, {"name": "BackdoorDetectionValidator", "count": 3}]
[]
google/gemma-2b
0
safe
0
0
0
0
0
2025-12-16T10:00:33.218509
0.4.0
https://huggingface.co/google/gemma-2b
{}
{}
[]
[]
TinyLlama/TinyLlama-1.1B-Chat-v1.0
0
safe
0
0
0
0
0
2025-12-16T10:01:12.960671
0.4.0
https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0
{}
{}
[]
[]
google/gemma-2b-it
0
safe
0
0
0
0
0
2025-12-16T10:02:43.022206
0.4.0
https://huggingface.co/google/gemma-2b-it
{}
{}
[]
[]
Qwen/Qwen3-1.7B
0
safe
0
0
0
0
0
2025-12-16T10:03:51.267202
0.4.0
https://huggingface.co/Qwen/Qwen3-1.7B
{}
{}
[]
[]
meta-llama/Llama-2-7b-hf
8
safe
4
0
0
0
4
2025-12-16T10:08:29.696766
0.4.0
https://huggingface.co/meta-llama/Llama-2-7b-hf
{"buffer_overflow": 4}
{}
[{"name": "BufferOverflowValidator", "count": 4}]
[]
mistralai/Mistral-7B-v0.1
2
safe
1
0
0
0
1
2025-12-16T10:12:46.000206
0.4.0
https://huggingface.co/mistralai/Mistral-7B-v0.1
{"buffer_overflow": 1}
{}
[{"name": "BufferOverflowValidator", "count": 1}]
[]
tiiuae/falcon-7b
0
safe
0
0
0
0
0
2025-12-16T10:16:54.693046
0.4.0
https://huggingface.co/tiiuae/falcon-7b
{}
{}
[]
[]
EleutherAI/gpt-neo-2.7B
142
low
67
0
0
1
66
2025-12-16T10:20:11.297110
0.4.0
https://huggingface.co/EleutherAI/gpt-neo-2.7B
{"model_integrity": 1, "buffer_overflow": 2, "backdoor": 64}
{}
[{"name": "BackdoorDetectionValidator", "count": 64}, {"name": "BufferOverflowValidator", "count": 2}, {"name": "ModelIntegrityValidator", "count": 1}]
[]
codellama/CodeLlama-7b-hf
0
safe
0
0
0
0
0
2025-12-16T10:23:59.580858
0.4.0
https://huggingface.co/codellama/CodeLlama-7b-hf
{}
{}
[]
[]

Palisade Model Security Scans

This dataset contains security scan results for popular ML models, generated by Palisade.

Dataset Structure

  • data/train.parquet: Leaderboard table with security metrics
  • sarif/: SARIF 2.1.0 scan reports organized by org/model-name

Metrics

  • Security Score: Weighted sum of findings (lower is better)
  • Risk Level: safe, low, medium, high, critical
  • Severity Counts: critical, high, medium, low breakdowns

Usage

from datasets import load_dataset

ds = load_dataset("palisade-security/model-scans", split="train")
df = ds.to_pandas()

# Get safest models
safe_models = df[df['risk_level'] == 'safe'].sort_values('security_score')

License

Public Domain (CC0)

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