plantuml-render

• Outcome: Pass
• Latest audit: Sep 16, 2026 · 8:01 AM UTC
• Version: 1.0.0

Overview

This skill appears to be a simple PlantUML renderer, with quality and setup issues but no evidence of hidden, destructive, persistent, or data-stealing behavior.

Before installing, confirm you have a trusted PlantUML JAR available and understand that the skill will create local files and run Java. Treat PlantUML source and included files as local input you control, and expect the published version to need setup fixes before it works reliably.

A.I.G

Vulnerability Patterns

• 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
• Unauthorized Access and Privilege Escalation: Obtains permissions beyond the task's legitimate needs

SkillSpector

Vulnerability Patterns

• Behavioral AST: exec() Call, eval() Call, Dynamic Import
• MCP Least Privilege: Underdeclared Capability, Wildcard Permission, Missing Permission Declaration
• MCP Tool Poisoning: Hidden Instructions, Unicode Deception, Parameter Description Injection
• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration

Findings (5)

Tp4

High

• Category: MCP Tool Poisoning
• Confidence: 88% confidence
• Finding: The code largely matches the declared core purpose: it uses a PlantUML JAR to render diagrams. However, there are notable description/behavior gaps. The implementation takes a file path (`tmp_file`) rather than source code content, and the commented-out code suggests direct source handling was intended but is not active. Also, the function docstring states it returns base64-encoded image data, but it actually returns nothing and only prints the output path. While format selection exists in the function via `fmt`, the provided CLI entry point does not expose alternative formats such as SVG/PDF. These differences are material enough to count as a mismatch, though the primary purpose remains aligned.

Lp3

Medium

• Category: MCP Least Privilege
• Confidence: 88% confidence
• Finding: The skill explicitly instructs use of a Python script and `java -jar`, which means it can invoke shell/subprocess execution, but it declares no `permissions` or `allowed-tools` scope. That omission weakens least-privilege controls and can cause the agent to run code-capable actions without clear policy boundaries or user awareness.

Missing User Warnings

Medium

• Confidence: 91% confidence
• Finding: The skill tells the agent to write files and execute a local JAR through Python/Java, but gives no warning about local file modification or subprocess execution. In an agent environment, undisclosed file writes and command execution increase the risk of unsafe operation, especially if user-supplied PlantUML content or file paths are passed through without explicit consent and bounds.

Intent-Code Divergence

Medium

• Confidence: 98% confidence
• Finding: The function documentation explicitly states 'Returns the base64-encoded image data.' However, the implementation invokes the PlantUML JAR, derives an output file path, and prints that path; it does not read the generated file, encode it, or return any value. This is an active contradiction between documented intent and actual behavior.

subprocess module call

Medium

• Category: Dangerous Code Execution

Content

if out_dir:
        cmd += ["-o", out_dir]
    cmd.append(tmp_file)
    subprocess.run(cmd, check=True)
    img_path = output_path or os.path.join(os.path.dirname(tmp_file), os.path.splitext(os.path.basename(tmp_file))[0]+f".{fmt}")
    print(f"image path {img_path}")

• Confidence: 70% confidence
• Finding: subprocess module calls execute external commands. Without careful input validation, this enables command injection.

Static analysis

No suspicious patterns detected.