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detect-gcp-model-artifact-download

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Actualizado9 de julio de 2026 a las 16:16

Detect successful GCS object downloads that look like model-weight or checkpoint artifact collection. Consumes OCSF 1.8 API Activity emitted by ingest-gcp-audit-ocsf and fires only on successful storage.googleapis.com/storage.objects.get events whose object path matches explicit model-artifact filename or suffix heuristics. Emits OCSF Detection Finding 2004 by default, with a native output mode for repo-local pipelines. Use when the user wants to spot suspicious model artifact collection from Cloud Storage. Do NOT use for generic bucket access monitoring, generic data exfiltration, or Azure/AWS object-store reads.

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msaad00/cloud-ai-security-skills

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SKILL.md

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name	detect-gcp-model-artifact-download
description	Detect successful GCS object downloads that look like model-weight or checkpoint artifact collection. Consumes OCSF 1.8 API Activity emitted by ingest-gcp-audit-ocsf and fires only on successful storage.googleapis.com/storage.objects.get events whose object path matches explicit model-artifact filename or suffix heuristics. Emits OCSF Detection Finding 2004 by default, with a native output mode for repo-local pipelines. Use when the user wants to spot suspicious model artifact collection from Cloud Storage. Do NOT use for generic bucket access monitoring, generic data exfiltration, or Azure/AWS object-store reads.
purpose	Detect successful GCS object downloads that look like model-weight or checkpoint artifact collection.
capability	detect
persistence	none
telemetry	stderr_jsonl
privilege_escalation	none
license	Apache-2.0
approval_model	none
execution_modes	jit, ci, mcp, persistent
side_effects	none
input_formats	ocsf, native
output_formats	ocsf, native
concurrency_safety	stateless
compatibility	Requires Python 3.11+. Input must be the OCSF / native API Activity stream from ingest-gcp-audit-ocsf. The detector is read-only and deterministic.
metadata	{"author":"msaad00","homepage":"https://github.com/msaad00/cloud-ai-security-skills","source":"https://github.com/msaad00/cloud-ai-security-skills/tree/main/skills/detection/detect-gcp-model-artifact-download","version":"0.1.0","frameworks":["OCSF 1.8","MITRE ATT&CK v14","MITRE ATLAS","OWASP LLM Top 10"],"cloud":"gcp","capability":"read-only"}

detect-gcp-model-artifact-download

What it does

Flags successful GCS object reads that look like model weights, checkpoints, or other ML artifact collection.

The detector is intentionally narrow:

only ingest-gcp-audit-ocsf input
only successful storage.objects.get
only explicit model-artifact filename / suffix matches

It does not claim generic GCS exfiltration coverage.

Mappings

MITRE ATT&CK: T1530 Data from Cloud Storage
MITRE ATLAS: AML.T0035 ML Artifact Collection

Input contract

Reads JSONL API Activity records and expects:

metadata.product.feature.name = ingest-gcp-audit-ocsf
api.service.name = storage.googleapis.com
api.operation = storage.objects.get
resources[].name carrying a GCS-style resource path such as: projects/_/buckets/<bucket>/objects/<object>

The detector URL-decodes the object path before applying artifact matching.

Artifact heuristics

High-confidence model artifact hits include:

.safetensors, .pt, .pth, .ckpt, .onnx, .gguf, .tflite, .keras, .h5
exact filenames like pytorch_model.bin, adapter_model.bin, saved_model.pb
.bin only when the path also contains model hints such as model, checkpoint, weights, vertex, or aiplatform

Output

default: OCSF Detection Finding 2004
optional: native repo finding via --output-format native

Example

python skills/ingestion/ingest-gcp-audit-ocsf/src/ingest.py gcp-audit.jsonl \
  | python skills/detection/detect-gcp-model-artifact-download/src/detect.py

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name	detect-gcp-model-artifact-download
description	Detect successful GCS object downloads that look like model-weight or checkpoint artifact collection. Consumes OCSF 1.8 API Activity emitted by ingest-gcp-audit-ocsf and fires only on successful storage.googleapis.com/storage.objects.get events whose object path matches explicit model-artifact filename or suffix heuristics. Emits OCSF Detection Finding 2004 by default, with a native output mode for repo-local pipelines. Use when the user wants to spot suspicious model artifact collection from Cloud Storage. Do NOT use for generic bucket access monitoring, generic data exfiltration, or Azure/AWS object-store reads.
purpose	Detect successful GCS object downloads that look like model-weight or checkpoint artifact collection.
capability	detect
persistence	none
telemetry	stderr_jsonl
privilege_escalation	none
license	Apache-2.0
approval_model	none
execution_modes	jit, ci, mcp, persistent
side_effects	none
input_formats	ocsf, native
output_formats	ocsf, native
concurrency_safety	stateless
compatibility	Requires Python 3.11+. Input must be the OCSF / native API Activity stream from ingest-gcp-audit-ocsf. The detector is read-only and deterministic.
metadata	{"author":"msaad00","homepage":"https://github.com/msaad00/cloud-ai-security-skills","source":"https://github.com/msaad00/cloud-ai-security-skills/tree/main/skills/detection/detect-gcp-model-artifact-download","version":"0.1.0","frameworks":["OCSF 1.8","MITRE ATT&CK v14","MITRE ATLAS","OWASP LLM Top 10"],"cloud":"gcp","capability":"read-only"}

detect-gcp-model-artifact-download

What it does

Flags successful GCS object reads that look like model weights, checkpoints, or other ML artifact collection.

The detector is intentionally narrow:

only ingest-gcp-audit-ocsf input
only successful storage.objects.get
only explicit model-artifact filename / suffix matches

It does not claim generic GCS exfiltration coverage.

Mappings

MITRE ATT&CK: T1530 Data from Cloud Storage
MITRE ATLAS: AML.T0035 ML Artifact Collection

Input contract

Reads JSONL API Activity records and expects:

metadata.product.feature.name = ingest-gcp-audit-ocsf
api.service.name = storage.googleapis.com
api.operation = storage.objects.get
resources[].name carrying a GCS-style resource path such as: projects/_/buckets/<bucket>/objects/<object>

The detector URL-decodes the object path before applying artifact matching.

Artifact heuristics

High-confidence model artifact hits include:

.safetensors, .pt, .pth, .ckpt, .onnx, .gguf, .tflite, .keras, .h5
exact filenames like pytorch_model.bin, adapter_model.bin, saved_model.pb
.bin only when the path also contains model hints such as model, checkpoint, weights, vertex, or aiplatform

Output

default: OCSF Detection Finding 2004
optional: native repo finding via --output-format native

Example

python skills/ingestion/ingest-gcp-audit-ocsf/src/ingest.py gcp-audit.jsonl \
  | python skills/detection/detect-gcp-model-artifact-download/src/detect.py