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Insecure output handling

Skill thejefflarson/soundcheck/.claude/skills/insecure-output-handling

Detects unsafe rendering or execution of LLM output that enables XSS, command injection, or second-order injection. Use when writing code that renders LLM output to a UI, executes LLM-generated code or shell commands, or passes LLM responses to downstream APIs or databases. Also invoke when displaying markdown or HTML from an LLM response.From its SKILL.md

Install
npx -y skills add thejefflarson/soundcheck --skill insecure-output-handling

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

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SKILL.md

3.3 KB, as published. Nobody here has run it

Insecure Output Handling Security Check (OWASP LLM02:2025)

What this checks

Protects against XSS, command injection, and second-order injection that arise when LLM output is treated as trusted. The model may produce malicious content through prompt injection or hallucination; downstream systems must sanitize it the same way they would sanitize raw user input.

Vulnerable patterns

  • LLM response assigned to a raw-HTML sink (innerHTML, dangerouslySetInnerHTML, v-html, server-side mark_safe) without sanitization
  • LLM-generated code or shell string passed to eval, exec, or a subprocess call with shell expansion enabled
  • LLM output interpolated into a SQL or NoSQL query string instead of bound as a parameter
  • LLM-produced markdown rendered to HTML without an allowlist-based sanitizer
  • LLM response forwarded to a downstream API or webhook without re-validating against the destination's schema

Fix immediately

Flag the vulnerable code and explain the risk. Translate the principles below to the audited file's language, UI framework, and database driver — use that stack's documented escaping, sanitizer, and parameter-binding APIs.

For each finding, establish these properties:

  1. Treat LLM output as untrusted input at every consumption point. The same escaping, parameterization, and allowlisting rules that apply to user input apply here — prompt injection makes the model a proxy for attacker content.
  2. HTML rendering uses a safe sink. Plain-text sink or auto-escaping template for prose; an allowlist-based sanitizer for rich content. Never a raw-HTML sink with an unsanitized LLM string.
  3. Shell and code execution require an allowlist. If the LLM picks an action, the handler validates it against a static set of permitted commands and invokes them with argv arrays — never with shell expansion enabled, never through a dynamic-evaluation primitive.
  4. Database queries are parameterized. LLM output lands in bind variables, not string-interpolated into the statement. For injection details, see the injection skill.

Verification

Confirm the response:

  • No LLM string is assigned to a raw-HTML sink without going through an allowlist-based sanitizer
  • Shell execution uses an allowlist; shell-expansion modes are never used with LLM-derived input
  • If the code routes LLM output into a database query, the query uses parameterized placeholders — not string interpolation or concatenation with the LLM-derived value. Skip this criterion when the code does not execute any database query.
  • LLM output is treated as untrusted user input at every consumption point

References

Keep looking

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