| Base score | 100 |
| CRITICAL Overlapping tensor data regions (1 pairs) | -40 |
| LOW Sparse __metadata__: missing author, license, source/model_name | -3 |
| MEDIUM Misaligned tensor data (1 tensor(s)) | -8 |
| Penalty subtotal | 49/100 |
| Final | D / 49 |
| Runtime | Status | Quant | Architecture | Context |
|---|---|---|---|---|
| HuggingFace Transformers |
✓
Direct
|
? | ✓ | Native format -- safetensors is the default weight format for HF models. |
|
vLLM
Verify arch support
|
? | ? | ? verify |
vLLM targets decoder-only LLMs; this architecture may require a custom backend. |
| llama.cpp |
⚡
Via conversion
|
? | ✗ | Requires GGUF conversion. Use convert_hf_to_gguf.py from the llama.cpp repository. |
|
ONNX Runtime
Verify arch support
|
⚡
Via conversion
|
? | ? verify |
Requires ONNX export (e.g., optimum-cli export onnx or torch.onnx.export). |
| Parameters ~ Estimated total number of weight values; determines VRAM needed at inference | 448 |
| Tensors Total number of weight tensors stored in the file | 4 |
| SHA-256 | 8ed50ec8cdb4027f2f63f46afeeb81233e7919e2463a336452e42515092e20ff |
| SHA-512 | b6e2799c983f6f6a553ca30ac76d7901c84108ff9b9c2c3369abaee69af281244c982402c782e4c9… |
| File size | 2,182 bytes (0.0 MB) |
| Header size | 382 bytes (0.37 KB) |
| Tensor data sum | 1,792 bytes |
| Padding / overhead | 0.0 MB |
| Offsets monotone | ✓ OK |
| Overlapping regions | ⚠ 1 |
| DType | Count | Total bytes | Total MB | Avg bits/elem |
|---|---|---|---|---|
| F32 | 4 | 1,792 | 0.0 | 32.0 |
| # | Name | Shape | DType | Offset | Bytes | bits/elem |
|---|---|---|---|---|---|---|
| 0 | token_embd.weight | [32, 8] | F32 | 0 | 1,024 | 32.0 |
| 1 | blk.0.attn_q.weight | [8, 8] | F32 | 1,024 | 256 | 32.0 |
| 2 | blk.0.attn_k.weight | [8, 8] | F32 | 1,028 | 256 | 32.0 |
| 3 | blk.0.attn_v.weight | [8, 8] | F32 | 1,536 | 256 | 32.0 |
| format | pt |
{
"compatibility": [
{
"arch": true,
"context": "Native format -- safetensors is the default weight format for HF models.",
"direct_supported": true,
"runtime": "HuggingFace Transformers"
},
{
"arch": null,
"context": "vLLM targets decoder-only LLMs; this architecture may require a custom backend.",
"conversion_possible": null,
"direct_supported": null,
"runtime": "vLLM",
"verification_required": true
},
{
"arch": false,
"context": "Requires GGUF conversion. Use convert_hf_to_gguf.py from the llama.cpp repository.",
"conversion_possible": true,
"direct_supported": false,
"runtime": "llama.cpp"
},
{
"arch": null,
"context": "Requires ONNX export (e.g., optimum-cli export onnx or torch.onnx.export).",
"conversion_possible": true,
"direct_supported": false,
"runtime": "ONNX Runtime"
}
],
"format": "LLM-SCAN",
"format_version": "1.0",
"generator": {
"name": "llmscan-engine",
"version": "2.0.0"
},
"model": {
"arch": null,
"dtype_histogram": {
"F32": 4
},
"dtype_stats": {
"F32": {
"avg_bits_per_elem": 32.0,
"bytes": 1792,
"count": 4,
"mb": 0.0
}
},
"file_size_bytes": 2182,
"file_size_mb": 0.0,
"format": "safetensors",
"has_metadata": true,
"header_size_bytes": 382,
"kv_meta": {},
"metadata": {
"format": "pt"
},
"offsets_monotone": true,
"oob_tensor_count": 0,
"overlapping_regions": 1,
"param_estimate": 448,
"params_estimate": 448,
"quantization": null,
"scanner_model_info": {
"dtype_histogram": {
"F32": 4
},
"dtype_percentage": {
"F32": 100.0
},
"dtype_stats": {
"F32": {
"avg_bits_per_elem": 32.0,
"bytes": 1792,
"count": 4,
"mb": 0.0
}
},
"file_size_bytes": 2182,
"file_size_mb": 0.0,
"has_metadata": true,
"header_size_bytes": 382,
"inferred_arch": null,
"metadata": {
"format": "pt"
},
"nan_inf_scan": {
"affected_tensors": [],
"inf_count": 0,
"method": "full",
"nan_count": 0,
"performed": true,
"tensors_scanned": 4,
"total_float_tensors": 4,
"values_scanned": 448
},
"offsets_monotone": true,
"oob_tensor_count": 0,
"overlapping_regions": 1,
"param_estimate": 448,
"scalar_tensor_count": 0,
"sha256": "8ed50ec8cdb4027f2f63f46afeeb81233e7919e2463a336452e42515092e20ff",
"sha512": "b6e2799c983f6f6a553ca30ac76d7901c84108ff9b9c2c3369abaee69af281244c982402c782e4c96c789ae0973789f5b61b8a5bb0291c3d3847a28df3af0efc",
"tensor_bytes_sum": 1792,
"tensor_count": 4,
"tensor_delta_bytes": 0,
"tensor_delta_mb": 0.0,
"tensor_preview": [
{
"bits_per_elem": 32.0,
"byte_len": 1024,
"dims": [
32,
8
],
"dtype_name": "F32",
"index": 0,
"name": "token_embd.weight",
"offset": 0
},
{
"bits_per_elem": 32.0,
"byte_len": 256,
"dims": [
8,
8
],
"dtype_name": "F32",
"index": 1,
"name": "blk.0.attn_q.weight",
"offset": 1024
},
{
"bits_per_elem": 32.0,
"byte_len": 256,
"dims": [
8,
8
],
"dtype_name": "F32",
"index": 2,
"name": "blk.0.attn_k.weight",
"offset": 1028
},
{
"bits_per_elem": 32.0,
"byte_len": 256,
"dims": [
8,
8
],
"dtype_name": "F32",
"index": 3,
"name": "blk.0.attn_v.weight",
"offset": 1536
}
],
"total_bytes_declared": 1792,
"unknown_dtypes": []
},
"sha256": "8ed50ec8cdb4027f2f63f46afeeb81233e7919e2463a336452e42515092e20ff",
"sha512": "b6e2799c983f6f6a553ca30ac76d7901c84108ff9b9c2c3369abaee69af281244c982402c782e4c96c789ae0973789f5b61b8a5bb0291c3d3847a28df3af0efc",
"tensor_bytes_sum": 1792,
"tensor_count": 4,
"tensor_delta_mb": 0.0,
"tensor_preview": [
{
"bits_per_elem": 32.0,
"byte_len": 1024,
"dims": [
32,
8
],
"dtype_name": "F32",
"index": 0,
"name": "token_embd.weight",
"offset": 0
},
{
"bits_per_elem": 32.0,
"byte_len": 256,
"dims": [
8,
8
],
"dtype_name": "F32",
"index": 1,
"name": "blk.0.attn_q.weight",
"offset": 1024
},
{
"bits_per_elem": 32.0,
"byte_len": 256,
"dims": [
8,
8
],
"dtype_name": "F32",
"index": 2,
"name": "blk.0.attn_k.weight",
"offset": 1028
},
{
"bits_per_elem": 32.0,
"byte_len": 256,
"dims": [
8,
8
],
"dtype_name": "F32",
"index": 3,
"name": "blk.0.attn_v.weight",
"offset": 1536
}
]
},
"report": {
"bullets": [
"Safetensors unknown arch | F32 | 4 tensors | ~0M params | 0 MB | 1 blocking issue / 2 warnings / 3 informational",
"SHA256: 8ed50ec8cdb4027f..."
],
"recommendations": [
"Overlapping regions enable aliasing attacks where two tensors share memory; reject this file",
"Re-export using the official safetensors library to ensure correct alignment.",
"Add author, license, and source fields to __metadata__ when exporting."
],
"summary": "Safetensors unknown arch | F32 | 4 tensors | ~0M params | 0 MB | 1 blocking issue / 2 warnings / 3 informational"
},
"scan_context": {
"duration_ms": 1,
"ended_at": "2026-08-10T20:38:48+00:00Z",
"limits": {
"sandbox": true,
"timeout_ms": 60000
},
"mode": "static-deep",
"started_at": "2026-08-10T20:38:48+00:00Z"
},
"security": {
"findings": [
{
"category": "Integrity",
"detail": "Pairs: [(\u0027blk.0.attn_q.weight\u0027, \u0027blk.0.attn_k.weight\u0027)]",
"recommendation": "Overlapping regions enable aliasing attacks where two tensors share memory; reject this file",
"severity": "CRITICAL",
"title": "Overlapping tensor data regions (1 pairs)"
},
{
"category": "Precision",
"detail": "All 4 tensors use 32-bit float. Higher numerical fidelity but 2\u00d7 the memory of F16 and 4-8\u00d7 of quantized variants.",
"recommendation": "Consider converting to BF16 or INT8 for production inference if accuracy allows.",
"severity": "INFO",
"title": "Full-precision weights (F32) \u2014 not quantized"
},
{
"category": "Provenance",
"detail": "Embedded metadata has 1 key(s) but lacks: author, license, source/model_name. Without provenance, the model origin cannot be verified from the file alone.",
"recommendation": "Add author, license, and source fields to __metadata__ when exporting.",
"severity": "LOW",
"title": "Sparse __metadata__: missing author, license, source/model_name"
},
{
"category": "Structure",
"detail": "4 tensors, ~448 parameters",
"recommendation": "Verify dtype matches expected model precision",
"severity": "INFO",
"title": "Dtype breakdown: {\u0027F32\u0027: 4}"
},
{
"category": "Format",
"detail": "Unlike pickle-based formats, safetensors cannot execute arbitrary code during loading",
"recommendation": "Safetensors is the recommended format for sharing model weights safely",
"severity": "INFO",
"title": "Safetensors format provides strong sandboxing"
},
{
"category": "Memory Alignment",
"detail": "Tensors not aligned to 8-byte boundary: [\u0027blk.0.attn_k.weight\u0027]. Misalignment can cause SIGBUS on ARM and degrade SIMD performance on x86. Likely indicates manual file editing or a non-standard exporter.",
"recommendation": "Re-export using the official safetensors library to ensure correct alignment.",
"severity": "MEDIUM",
"title": "Misaligned tensor data (1 tensor(s))"
}
],
"grade": "D",
"score": 49
},
"source": {
"filename": "overlapping-tensors.safetensors",
"hashes": {
"sha256": "8ed50ec8cdb4027f2f63f46afeeb81233e7919e2463a336452e42515092e20ff"
},
"input_type": "file",
"size_bytes": 2182
},
"tensors": {
"count": 4,
"dtype_histogram": {
"F32": 4
},
"dtype_stats": {
"F32": {
"avg_bits_per_elem": 32.0,
"bytes": 1792,
"count": 4,
"mb": 0.0
}
},
"integrity": {
"header_size_bytes": 382,
"offsets_monotone": true,
"oob_tensor_count": 0,
"overlapping_regions": 1,
"tensor_bytes_sum": 1792,
"tensor_delta_mb": 0.0
},
"preview": [
{
"bits_per_elem": 32.0,
"byte_len": 1024,
"dims": [
32,
8
],
"dtype_name": "F32",
"index": 0,
"name": "token_embd.weight",
"offset": 0
},
{
"bits_per_elem": 32.0,
"byte_len": 256,
"dims": [
8,
8
],
"dtype_name": "F32",
"index": 1,
"name": "blk.0.attn_q.weight",
"offset": 1024
},
{
"bits_per_elem": 32.0,
"byte_len": 256,
"dims": [
8,
8
],
"dtype_name": "F32",
"index": 2,
"name": "blk.0.attn_k.weight",
"offset": 1028
},
{
"bits_per_elem": 32.0,
"byte_len": 256,
"dims": [
8,
8
],
"dtype_name": "F32",
"index": 3,
"name": "blk.0.attn_v.weight",
"offset": 1536
}
]
},
"tokenizer": {}
}