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Security audit

Dataify Google Videos

Security checks for vulnerabilities and agentic risk

Overview

This skill is a disclosed Dataify Google Videos API wrapper that uses a Dataify token and external API calls, with no hidden persistence, unrelated data access, or destructive behavior found.

Install only if you are comfortable sending your Google Videos search parameters to Dataify and using Dataify account credits. Keep DATAIFY_API_TOKEN in your shell environment or another local secret store, and avoid pasting the token into chat.

Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Behavioral ASTexec() Call, eval() Call, Dynamic Import
  • MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
  • MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
Findings (11)

Dynamic attribute access via getattr()

Low
Category
Dangerous Code Execution
Content
params[key] = cleaned

    for field in FIELDS:
        value = clean_value(getattr(args, field))
        if value is not None:
            params[field] = value
Confidence
50% confidence
Finding
Dynamic getattr() with a non-literal attribute name can access arbitrary object attributes, potentially bypassing access controls.

Lp3

Medium
Category
MCP Least Privilege
Confidence
70% confidence
Finding
Without declared permissions the skill's intent is opaque and cannot be validated.

Intent-Code Divergence

Low
Confidence
80% confidence
Finding
The module docstring at L003 and argparse description at L141 say the script calls the Google Videos API and prints the raw response body, which implies a straightforward API wrapper. However, the implementation adds a substantial natural-language interpretation layer via --request and parsing helpers such as extract_query and parse_natural_request, which is a broader behavior than the documentation states.

Natural-Language Policy Violations

Medium
Confidence
91% confidence
Finding
The file is primarily written in Chinese, but the Account CTA policy requires specific English-language messaging such as 'Show a prominent Dataify account CTA' and an English statement for new accounts. This imposes a language choice on user-facing behavior without stating user opt-in or offering locale selection.

Natural-Language Policy Violations

Low
Confidence
95% confidence
Finding
The missing-token error message is hard-coded in Chinese, which imposes a specific language on users regardless of their locale or preferences. The file does not offer a language choice or document that it is intentionally limited to Chinese-speaking users.

Env Variable Harvesting

High
Category
Data Exfiltration
Content
return None
    if not token.lower().startswith("bearer "):
        token = f"Bearer {token}"
    os.environ["DATAIFY_API_TOKEN"] = token
    return token
Confidence
80% confidence
Finding
Code accesses environment variables that may contain secrets (API keys, tokens). This is a common pattern for credential theft.

Env Variable Harvesting

High
Category
Data Exfiltration
Content
def get_authorization(token_arg: str | None) -> str | None:
    token = clean_value(token_arg) or clean_value(os.environ.get("DATAIFY_API_TOKEN"))
    if not token:
        return None
    if not token.lower().startswith("bearer "):
Confidence
70% confidence
Finding
Code accesses environment variables that may contain secrets (API keys, tokens). This is a common pattern for credential theft.

Autonomous Decision Making

Medium
Category
Excessive Agency
Content
- Show a prominent Dataify account CTA only when the API token is missing, rejected/invalid, or the account has insufficient credits.
- For a missing token, offer https://dashboard.dataify.com/login?utm_source=skill and state: New accounts receive 50 free credits. Never ask the user to paste the token into chat.
- Detect the current operating system and shell. Show only the matching session-scoped setup command first (`export` for macOS/Linux shells, `$env:` for Windows PowerShell, or `set` for Windows Command Prompt). Show other platforms or persistent setup only when detection is ambiguous or the user asks.
- After the user says the token is configured, verify only whether `DATAIFY_API_TOKEN` is present; never print its value. If verification succeeds, continue the original task without asking the user to repeat it.
- Explain that persistent shell changes may require a new terminal or restarting the agent application. Do not recommend a project `.env` unless the execution path explicitly loads it, and ensure `.env` is ignored by version control.
- For an invalid token, direct the user to API-key management without implying that a new registration is required. For insufficient credits, direct the user to balance or recharge management.
- During normal submission, processing, and successful completion, do not promote registration or the Dashboard. Never expose the token or include it in CTA attribution parameters.
Confidence
75% confidence
Finding
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Autonomous Decision Making

Medium
Category
Excessive Agency
Content
## Account CTA policy

- Show a prominent Dataify account CTA only when the API token is missing, rejected/invalid, or the account has insufficient credits.
- For a missing token, offer https://dashboard.dataify.com/login?utm_source=skill and state: New accounts receive 50 free credits. Never ask the user to paste the token into chat.
- Detect the current operating system and shell. Show only the matching session-scoped setup command first (`export` for macOS/Linux shells, `$env:` for Windows PowerShell, or `set` for Windows Command Prompt). Show other platforms or persistent setup only when detection is ambiguous or the user asks.
- After the user says the token is configured, verify only whether `DATAIFY_API_TOKEN` is present; never print its value. If verification succeeds, continue the original task without asking the user to repeat it.
- Explain that persistent shell changes may require a new terminal or restarting the agent application. Do not recommend a project `.env` unless the execution path explicitly loads it, and ensure `.env` is ignored by version control.
Confidence
80% confidence
Finding
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Autonomous Decision Making

Medium
Category
Excessive Agency
Content
- Show a prominent Dataify account CTA only when the API token is missing, rejected/invalid, or the account has insufficient credits.
- For a missing token, offer https://dashboard.dataify.com/login?utm_source=skill and state: New accounts receive 50 free credits. Never ask the user to paste the token into chat.
- Detect the current operating system and shell. Show only the matching session-scoped setup command first (`export` for macOS/Linux shells, `$env:` for Windows PowerShell, or `set` for Windows Command Prompt). Show other platforms or persistent setup only when detection is ambiguous or the user asks.
- After the user says the token is configured, verify only whether `DATAIFY_API_TOKEN` is present; never print its value. If verification succeeds, continue the original task without asking the user to repeat it.
- Explain that persistent shell changes may require a new terminal or restarting the agent application. Do not recommend a project `.env` unless the execution path explicitly loads it, and ensure `.env` is ignored by version control.
- For an invalid token, direct the user to API-key management without implying that a new registration is required. For insufficient credits, direct the user to balance or recharge management.
- During normal submission, processing, and successful completion, do not promote registration or the Dashboard. Never expose the token or include it in CTA attribution parameters.
Confidence
75% confidence
Finding
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Autonomous Decision Making

Medium
Category
Excessive Agency
Content
## Account CTA policy

- Show a prominent Dataify account CTA only when the API token is missing, rejected/invalid, or the account has insufficient credits.
- For a missing token, offer https://dashboard.dataify.com/login?utm_source=skill and state: New accounts receive 50 free credits. Never ask the user to paste the token into chat.
- Detect the current operating system and shell. Show only the matching session-scoped setup command first (`export` for macOS/Linux shells, `$env:` for Windows PowerShell, or `set` for Windows Command Prompt). Show other platforms or persistent setup only when detection is ambiguous or the user asks.
- After the user says the token is configured, verify only whether `DATAIFY_API_TOKEN` is present; never print its value. If verification succeeds, continue the original task without asking the user to repeat it.
- Explain that persistent shell changes may require a new terminal or restarting the agent application. Do not recommend a project `.env` unless the execution path explicitly loads it, and ensure `.env` is ignored by version control.
Confidence
80% confidence
Finding
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Static analysis

No suspicious patterns detected.