Security audit

Amazon Listing 图片生成与编辑

Security checks for vulnerabilities and agentic risk

Overview

This skill is a coherent Amazon listing image generator that uses an AI Hive API key and user-provided images, with some ordinary integration risks users should understand.

Install this only if you are comfortable giving AI Hive an API key and uploading the product/reference images you choose. Use a virtual environment, consider pinning dependencies, avoid running it with elevated privileges, and be aware that generated files are downloaded to your local output directory from service-provided URLs.

A.I.G

Vulnerability Patterns

Insecure DependenciesIntroduces malicious components through unsafe dependency sources
Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
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

Findings (3)

T08 · Insecure Dependencies

Warning

Location: SKILL.md:72
Finding: Unpinned Third-Party Dependency Creates a Supply-Chain Risk
Content: View full analysis
Remediation: View remediation

T09 · Insecure Skill Coding Practices

Warning

Location: scripts/imagegen.py:203
Finding: API-Controlled Upload and Download Destinations Are Used Without Validation
Content: View full analysis
0: pct = int(downloaded * 100 / total) bar = "█" * (pct // 5) + "░" * (20 - pct // 5) print(f"\r {bar} {pct}% ({downloaded // 1024}KB)", end="", flush=True) print() size_mb = downloaded / (1024 * 1024) print(f"[ok] {out_path} ({size_mb:.1f} MB)") except requests.exceptions.RequestException as ...[truncated 3026 chars]
Remediation: View remediation

T09 · Insecure Skill Coding Practices

Note

Location: scripts/imagegen.py:198
Finding: Upload and Download Operations Have No Explicit Transfer-Size Limits
Content: View full analysis
0: pct = int(downloaded * 100 / total) bar = "█" * (pct // 5) + "░" * (20 - pct // 5) print(f"\r {bar} {pct}% ({downloaded // 1024}KB)", end="", flush=True) ``` ### Technical Analysis The upload path obtains the source file size but does not compare it against an application-defi ...[truncated 1981 chars]
Remediation: View remediation

SkillSpector

Vulnerability Patterns

Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access

Findings (4)

Undeclared Tool Scope

Medium

Category: MCP Least Privilege
Confidence: 91% confidence
Finding: The skill exposes capabilities that imply shell, file, environment, and network access, but it does not declare an explicit tool scope or permission boundary in the skill manifest. That increases the risk of unintended or overly broad execution paths, making it harder for a caller or platform to constrain what the skill may do if the backing script is modified or misused.
Content: No source excerpt is available for this finding.

Vague Triggers

Medium

Category: Not specified by scanner
Confidence: 90% confidence
Finding: The description says "Use this skill for Amazon Listing 图片生成与编辑" followed by a broad list of common image-task phrases, but it does not define specific trigger phrases, scope limits, or negative examples. This could cause unintended invocation for many ordinary Amazon image-editing requests that may or may not fit the intended workflow.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 87% confidence
Finding: The natural-language content is predominantly written in Chinese and presents the workflow as the required interaction mode, with no indication that users may choose another language. This can violate language/locale policy when a skill implicitly constrains communication language without explicit opt-in or documented justification.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 93% confidence
Finding: The module docstring and all user-facing prompts/messages are written only in Chinese, and the skill does not indicate any option to choose another language. This can violate a language/locale policy when users are not explicitly opted into Chinese-only interaction.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.