T05 · Unauthorized Access and Privilege Escalation
- Location
scripts/qc_tool.py:611- Finding
Annotation-Controlled Path Traversal Allows Unauthorized Local Image Access
- Content
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- Remediation
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Security audit
Security checks for vulnerabilities and agentic risk
The skill is a coherent image-annotation QC tool, but crafted annotation files can make it read images outside the chosen image folder and can place unsafe values into Excel reports.
Review before installing or using on untrusted annotation files. Run it in a dedicated project directory or sandbox, keep visualization disabled for untrusted datasets until image-path containment is fixed, avoid opening generated XLSX files from untrusted labels, and prefer pinned dependency versions in an isolated Python environment.
scripts/qc_tool.py:611Annotation-Controlled Path Traversal Allows Unauthorized Local Image Access
scripts/qc_tool.py:693Attacker-Controlled Annotation Labels Can Cause Excel Formula Injection
SKILL.md:5Unpinned Third-Party Dependencies Create Supply-Chain Risk
The skill advertises and describes behavior that reads inputs and writes reports/visualizations, but it does not declare any explicit tool scope or permissions. That gap can cause users or orchestrators to invoke it without clear awareness of its filesystem access, increasing the risk of unintended writes, output placement in sensitive directories, or over-broad execution privileges.
This code file contains user-facing natural language in the module docstring and throughout CLI help/output that assumes Chinese as the only supported language. The policy requires flagging forced language or locale behavior when no opt-in or justified region-specific scope is provided.
The file’s user-facing content is entirely in Chinese, including the title, labels, and status, with no indication that language selection is optional or constrained by a documented regional requirement. This can violate a language/locale policy when users are not given an opt-in or alternative locale.
The skill states that reports are auto-saved and later notes output locations, but it does not present a clear upfront warning that execution will create files and visualization artifacts in the annotation or chosen output directory. This can lead to surprising side effects, clutter, accidental overwrites, or writes into directories containing sensitive or production data.
This code performs file-system modifications by creating a qc_report directory and later saving TXT, JSON, XLSX, and PNG outputs. Although there are print statements after writing, the skill lacks an upfront user warning or disclosure in its main description/help that running it will create directories and write files to disk.
No suspicious patterns detected.