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Security audit

Hugging Face Gradio

Security checks for vulnerabilities and agentic risk

Overview

This is a Gradio reference skill with examples, and the sensitive behaviors are visible, purpose-related, and not automatic.

Use this skill as a Gradio reference, but review examples before copying them into real apps. Remote `gradio predict` calls can upload selected files to the target Space, webcam and microphone components can capture sensitive media, and toy health or finance examples should not be reused for real advice without proper consent, privacy controls, and domain safeguards.

Vulnerability Patterns
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
Findings (3)

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The skill explicitly demonstrates gradio predict against external Spaces and includes a file-upload example that sends a local path marked as gradio.FileData to a remote server. In an agent skill context, this can normalize or induce exfiltration of local files to third-party services without a clear warning, consent gate, or guidance on restricting uploads to non-sensitive data.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
91% confidence
Finding

The example presents a medical-style intake flow that collects symptoms and returns a diagnosis-like output ('covid' or 'flu') without any disclaimer, privacy notice, or statement that it is not medical advice. In a reusable example library, this can normalize unsafe handling of health data and encourage downstream developers to deploy symptom triage interfaces without appropriate consent, data minimization, or regulatory safeguards.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The webcam streaming demo enables live camera capture from the browser and continuously streams frames without any user-facing warning about what is being captured, processed, or retained. Although browser permissions gate access, example code like this can be copied into applications that handle sensitive visual data, leading to privacy surprises or over-collection without clear notice.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.