Run any Skill in Manus with one click

detect-gcp-model-artifact-download

Stars3

Forks0

UpdatedJuly 9, 2026 at 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.

Installation

Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.

Run Skill in Manus

Source

msaad00

msaad00/cloud-ai-security-skills

View GitHub Repository View Creator Repositories

Download

Run Skill in Manus

Related occupationsSOC

Based on SOC occupation classification

Information Security AnalystsComputer and Mathematical Occupations·SOC 15-1212

File Explorer

4 files

SKILL.md

readonly

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

More from this repository

same repository

cspm-azure-cis-benchmark

msaad00/cloud-ai-security-skills

Assess Azure subscriptions against a curated subset of CIS Azure Foundations Benchmark v2.1. Automates 32 high-impact read-only checks across Identity, Defender for Cloud, Storage, Database, Logging, Networking, Compute, Key Vault, and App Service (~53% of the v2.1 benchmark). Use when the user mentions Azure CIS benchmark, Azure storage security, or unrestricted SSH/RDP detection in NSGs. Do NOT use for AWS or GCP; do NOT use to remediate findings (assessment-only, Reader role only); do NOT claim full CIS Azure coverage — only 32 of 60 controls are implemented, see the Roadmap section in this file for the gap.

2026-07-113

ingest-entra-directory-audit-ocsf

msaad00/cloud-ai-security-skills

Convert verified Microsoft Entra directoryAudit events into OCSF 1.8 API Activity (6003). The first slice maps Microsoft Graph directory audit events for service-principal credential changes, app-role grants, and federated identity credential creation into deterministic OCSF records while preserving Entra natural IDs such as id, correlationId, and activityDateTime for SIEM dedupe and downstream correlation. Use when the user mentions Entra audit log ingestion, Microsoft Graph directoryAudit normalization, or feeding Entra identity telemetry into an OCSF pipeline. Do NOT use for Okta System Log, Azure Activity Logs, or as a detector or policy engine — this skill only normalizes verified Microsoft Graph directoryAudit payloads.

2026-07-113

ingest-k8s-audit-ocsf

msaad00/cloud-ai-security-skills

Convert raw Kubernetes audit logs (`audit.k8s.io/v1`) into normalized API activity records, with OCSF as the default wire format and native output as an option. Maps user, source IP, verb, objectRef, and response status with enough fidelity for K8s privilege-escalation and secret-access detectors. Use when the user mentions Kubernetes audit logs, kube-apiserver audit sinks, K8s detection engineering, or feeding K8s audit into a SIEM. Do NOT use for container runtime logs, kubelet logs, or CloudTrail / GCP audit / Azure Activity. Do NOT use as a detection skill; this only normalizes events.

2026-07-113

ingest-okta-system-log-ocsf

msaad00/cloud-ai-security-skills

Convert verified Okta System Log events into OCSF 1.8 or native Identity & Access Management records. The first slice maps session and SSO events to Authentication (3002), user lifecycle and account-control changes to Account Change (3001), app/group membership updates to User Access Management (3005), and a narrow verified set of Okta Verify MFA challenge and denial events to Authentication (3002). It preserves Okta natural IDs such as uuid, published, transaction.id, and authenticationContext.externalSessionId for SIEM-friendly dedupe and correlation. Use when the user mentions Okta System Log ingestion, Okta audit log normalization, cross-vendor identity telemetry, or feeding Okta identity events into an OCSF pipeline or native canonical-first flow. Do NOT use for raw Azure Entra, Google Workspace, or AWS IAM logs. Do NOT use as a detector or policy engine — this skill only normalizes verified Okta event payloads into OCSF or native output.

2026-07-113

detect-aws-access-key-creation

msaad00/cloud-ai-security-skills

Detect successful AWS IAM `CreateAccessKey` API calls against IAM users from OCSF 1.8 API Activity records emitted by ingest-cloudtrail-ocsf. Emits an OCSF 1.8 Detection Finding (class 2004) tagged with MITRE ATT&CK T1098.001 (Additional Cloud Credentials) when a principal creates an access key for an IAM user. Use when the user mentions "AWS access key created", "IAM user key issuance", "additional cloud credentials in AWS", or "T1098.001 via CloudTrail". Do NOT use as a posture-at-rest access-key inventory check, to infer console-password or login-profile creation, or to claim every AWS identity-pivot path. This first slice only covers successful `CreateAccessKey` operations.

2026-07-103

detect-mcp-tool-drift

msaad00/cloud-ai-security-skills

Detect MCP tool schema drift mid-session — the MCP tool-poisoning / rug-pull attack pattern. Reads OCSF 1.8 Application Activity (class 6002) or the native application-activity projection produced by ingest-mcp-proxy-ocsf, groups them by session, and flags any tool whose fingerprint (sha256 over name + description + inputSchema + annotations) changes between tools/list responses in the same session. Emits OCSF 1.8 Detection Finding (class 2004) with MITRE ATT&CK T1195.001 (Compromise Software Supply Chain) inside finding_info.attacks. Use when the user mentions MCP security, tool drift, tool poisoning, prompt injection via tool schema, or supply chain compromise of an MCP server. Do NOT use on raw MCP proxy logs — feed them through ingest-mcp-proxy-ocsf first. Do NOT use for cross-session drift (same tool, different sessions) — that is a legitimate MCP server update, not an attack; a separate detector will cover it. Do NOT use for divergence against an out-of-band server-registered baseline — that is detect-m

2026-07-103

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