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Security audit

Seedream 5.0 Lite 图片换背景

Security checks for vulnerabilities and agentic risk

Overview

The skill is a disclosed AI Hive image background replacement wrapper that uploads user-selected images and uses an API key, with manageable scoping notes but no hidden or destructive behavior.

Install this only if you are comfortable sending the selected images and prompts to AI Hive and storing an AI Hive API key locally. Use a virtual environment, prefer a pinned requests dependency, do not run it as root, and pass only documented background-replacement parameters for authorized images.

Vulnerability Patterns
  • Insecure DependenciesIntroduces malicious components through unsafe dependency sources
  • 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
Findings (1)

T08 · Insecure Dependencies

Warning
Location
SKILL.md:72
Finding

Unpinned Third-Party Dependency Installation

Content
View full analysis
Remediation
View remediation
``` 2. Generate and record cryptographic hashes for the pinned package and all transitive dependencies, then require verification: ```bash python3 -m pip install --require-hashes -r requirements.txt ``` 3. Use a lock-generation workflow such as `pip-tools` to resolve and pin the complete transitive dependency graph. 4. Update `SKILL.md` and the import-error message to reference the verified requirements file rather than recommending an unconstrained installation: ```bash python3 -m pip install --require-hashes -r "$SKILL_PATH/requirements.txt" ``` 5. Recommend installation inside a dedicated virtual environment and explicitly advise users not to run pip or the Skill with administrator/root privileges. 6. Document the expected trusted package index. In controlled deployments, use an authenticated internal mirror containing reviewed artifacts. 7. Add automated dependency scanning and scheduled review of pinned versions so security updates are adopted deliberately without sacrificing reproducibility. ]]>
Vulnerability Patterns
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
  • MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
Findings (6)

Undeclared Tool Scope

Medium
Category
MCP Least Privilege
Confidence
95% confidence
Finding

The skill invokes a Python script that can use shell execution, read local files, write outputs, access environment variables, and make network requests, yet the manifest declares no explicit tool scope or permissions boundary. In an agent environment, this increases the chance of overbroad invocation and unintended access to local data or secrets, especially because the skill handles user-specified image paths and communicates with an external API.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

The description lists broad invocation phrases such as '图片换背景', '场景替换', and '人物换环境' alongside marketplace names, without clear activation boundaries or exclusion conditions. In a manifest-style skill description, these generic phrases can match common everyday image-editing requests and may cause unintended invocation.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
97% confidence
Finding

The module docstring and all user-facing CLI guidance are written in Chinese, and the file contains no indication that other languages are supported or that the locale is intentionally restricted for a region-specific purpose. Under the policy, forcing a specific language without user opt-in is a natural-language policy violation.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium
Category
Not specified by scanner
Confidence
91% confidence
Finding

The code accepts arbitrary --param key=value pairs, parses them generically, and passes them directly into the backend params field without allowlisting. Even with a fixed model, undocumented parameters can enable modes or behaviors outside the advertised background-replacement function, weakening control boundaries and potentially bypassing product-level restrictions.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The CLI exposes generic generate, task, and upload subcommands and forwards user-controlled prompts/images to a fixed image-generation backend, while the skill is described narrowly as a background-replacement tool. This mismatch expands capability beyond the declared safety scope, making it easier for downstream agents or users to invoke broader image editing/generation behavior than policy reviewers may expect.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
95% confidence
Finding

The placeholder value contains Chinese text ('请替换为你的APIKey'), which imposes a specific language in user-facing configuration content. For a general-purpose skill artifact, this is a natural-language locale choice without opt-in or documented justification.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.