korean-character-count
Fail
Audited by Gen Agent Trust Hub on Sep 12, 2026
Risk Level: HIGHREMOTE_CODE_EXECUTIONEXTERNAL_DOWNLOADSCOMMAND_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [REMOTE_CODE_EXECUTION]: The skill's primary instructions in
SKILL.mdandinstruction.mdrequire the agent to download and execute code from an external, untrusted source using the commandnpx -y @nomadamas/k-skill@0.2.4. This executes unverified software from the npm registry at runtime, which is a significant security risk as the package content is not controlled or audited within the skill itself. - [EXTERNAL_DOWNLOADS]: The skill fetches instructions and execution logic from the
@nomadamas/k-skillpackage on npm. This external dependency is not from a trusted organization, and the skill forces the agent to treat the remote output as the primary source of instructions. - [COMMAND_EXECUTION]: The workflow involves constructing and running shell commands that incorporate user-provided text (e.g.,
npx ... --text "$TEXT"orcat $FILE | npx ...). This presents a high risk of command injection if the agent interpolates untrusted user content directly into the shell command without rigorous escaping of shell metacharacters. - [INDIRECT_PROMPT_INJECTION]: The skill is designed to process untrusted user data (e.g., resumes, essays) which could contain malicious instructions.
- Ingestion points: User text is ingested through the
--textargument, file paths provided to--file, or data piped via--stdinas shown ininstruction.mdand handled inscripts/korean_character_count.js. - Boundary markers: The instructions do not specify any delimiters or boundary markers to separate untrusted data from the command logic.
- Capability inventory: The skill utilizes shell execution (via
npx) to run a Node.js script that performs file reading (fs.readFileSync) and standard output printing. - Sanitization: There are no sanitization or escaping protocols described for handling user-supplied text when constructing the execution commands, leaving the agent vulnerable to shell-based injection attacks.
Recommendations
- AI detected serious security threats
Audit Metadata