Azure Storage Blob Py

• Outcome: Pass
• Latest audit: Sep 10, 2026 · 7:19 AM UTC
• Version: 0.1.0

Overview

This is a straightforward Azure Blob Storage Python reference skill; its cloud upload and deletion examples are expected for the stated purpose, though users should apply normal safeguards.

Install in a virtual environment, consider pinning dependency versions, and only run upload or delete examples against Azure accounts, containers, and blobs you intend to modify. Enable soft delete, versioning, or backups before using deletion examples on important storage.

A.I.G

Vulnerability Patterns

• Insecure Dependencies: Introduces malicious components through unsafe dependency sources
• Skill Instruction Hijacking: Alters the agent's session goals or safety constraints when the skill loads
• Agent Memory Poisoning: Writes attacker-controlled rules into memory that affect later sessions
• Remote Payload Retrieval and Execution: Fetches external code whose behavior can change after review
• Embedded Malicious Code: Ships malicious scripts inside the skill and executes them locally

Findings (1)

T08 · Insecure Dependencies

Warning

• Location: SKILL.md:12

Finding

Unpinned Third-Party Dependency Installation

Content

View full analysis

Vulnerability Details

File Location: SKILL.md, lines 12-16
Vulnerability Type: Unpinned third-party dependencies
Risk Level: Medium

markdown

## Installation

```bash
pip install azure-storage-blob azure-identity

text

### Technical Analysis

The installation command specifies `azure-storage-blob` and `azure-identity` without exact versions or integrity hashes. Consequently, each installation may resolve to different, mutable package releases that were not reviewed as part of this skill.

The package names are consistent with the skill's declared Azure Blob Storage functionality, and the file does not specify an untrusted package index or demonstrate dependency confusion or typosquatting. Nevertheless, a compromised upstream release, package-distribution channel, or unexpectedly incompatible future version could introduce malicious or unsafe behavior.

### Attack Path

1. An attacker compromises an upstream dependency release, maintainer account, or package-distribution path.
2. A user follows the documented command after the compromised release becomes eligible for dependency resolution.
3. `pip` downloads and installs the mutable package release without verifying a project-supplied version or cryptographic hash.
4. Malicious package behavior may execute during package build or later when the installed Azure modules are imported.
5. The payload operates with the permissions and accessible credentials of the user or environment running Python.

This path depends on an upstream or distribution-channel compromise; no directly malicious dependency source was found in the audited file.

### Impact Assessment

Successful exploitation could execute code with the privileges of the account performing installation or running the resulting Python environment. The accessible scope could include local files, environment variables, Azure credentials exposed through `DefaultAzureCredential`, and network resource
...[truncated 139 chars]

Remediation

View remediation

Remediation Suggestions

• Pin every direct dependency to an explicitly reviewed version, for example through a version-controlled requirements.txt or lock file.
• Record cryptographic hashes for all resolved distributions and install them with pip install --require-hashes -r requirements.txt.
• Include and audit transitive dependencies in the lock file rather than constraining only direct dependencies.
• Regularly scan locked dependencies for known vulnerabilities and update them through a controlled review process.
• Install dependencies in an isolated virtual environment using a trusted package index.
• Where feasible, prevent source builds and prefer reviewed binary distributions to reduce installation-time code-execution exposure.

SkillSpector

Vulnerability Patterns

• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Privilege Escalation: Excessive Permissions, Sudo/Root Execution, Credential Access
• Supply Chain: Unpinned Dependencies, External Script Fetching, Obfuscated Code
• Excessive Agency: Unrestricted Tool Access, Autonomous Decision Making, Scope Creep

Findings (6)

Cloud Storage Exfiltration

Medium

• Category: Data Exfiltration
• Confidence: 55% confidence

Finding

Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.

Content

Scanner excerpt · SKILL.md (reported line 66)May include surrounding context.

md

)

with open("./local-file.txt", "rb") as data:
    blob_client.upload_blob(data, overwrite=True)

# From bytes/string
blob_client.upload_blob(b"Hello, World!", overwrite=True)

Cloud Storage Exfiltration

Medium

• Category: Data Exfiltration
• Confidence: 55% confidence

Finding

Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.

Content

Scanner excerpt · SKILL.md (reported line 69)May include surrounding context.

md

)

with open("./local-file.txt", "rb") as data:
    blob_client.upload_blob(data, overwrite=True)

# From bytes/string
blob_client.upload_blob(b"Hello, World!", overwrite=True)

Cloud Storage Exfiltration

Medium

• Category: Data Exfiltration
• Confidence: 55% confidence

Finding

Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.

Content

Scanner excerpt · SKILL.md (reported line 74)May include surrounding context.

md

)

with open("./local-file.txt", "rb") as data:
    blob_client.upload_blob(data, overwrite=True)

# From bytes/string
blob_client.upload_blob(b"Hello, World!", overwrite=True)

Cloud Storage Exfiltration

Medium

• Category: Data Exfiltration
• Confidence: 55% confidence

Finding

Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.

Content

Scanner excerpt · SKILL.md (reported line 143)May include surrounding context.

md

)

with open("./local-file.txt", "rb") as data:
    blob_client.upload_blob(data, overwrite=True)

# From bytes/string
blob_client.upload_blob(b"Hello, World!", overwrite=True)

Cloud Storage Exfiltration

Medium

• Category: Data Exfiltration
• Confidence: 55% confidence

Finding

Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.

Content

Scanner excerpt · SKILL.md (reported line 200)May include surrounding context.

md

)

with open("./local-file.txt", "rb") as data:
    blob_client.upload_blob(data, overwrite=True)

# From bytes/string
blob_client.upload_blob(b"Hello, World!", overwrite=True)

Missing User Warnings

Medium

• Category: Not specified by scanner
• Confidence: 95% confidence

Finding

The skill documentation includes delete_blob() examples that can permanently remove data, including snapshots, but it does not warn users about data loss or recommend confirmation/safeguards. For markdown files, destructive operations that affect user data should be accompanied by explicit warnings about their impact.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.