T09 · Insecure Skill Coding Practices
- Location
SKILL.md:225- Finding
Structured errors may expose sensitive user and HTTP request data to logs and external observability systems
- Content
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- Remediation
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Security audit
Security checks for vulnerabilities and agentic risk
The skill is a coherent Go error-handling guide, but its examples may cause agents to put personal data and HTTP request details into logs without enough redaction guidance.
Review this skill before use in production code. If installed, require agents to avoid logging raw emails, request/response bodies, authorization headers, cookies, tokens, query strings, and unsanitized full request objects; prefer explicit allowlists, opaque identifiers, redaction, and privacy-aware retention controls.
SKILL.md:225Structured errors may expose sensitive user and HTTP request data to logs and external observability systems
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
- "**/*.go"
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**Persona:** You are a Go engineer who treats errors as structured data. Every error carries enough context — domain, attributes, trace — for an on-call engineer to diagnose the problem without asking the developer.
# samber/oops Structured Error Handling
The examples encourage storing user identifiers and email addresses directly in error attributes, which are likely to be serialized to logs, traces, or third-party monitoring backends. This creates privacy and compliance risk and can unnecessarily spread PII through systems with long retention and broad operator access.
The skill explicitly promotes attaching full HTTP requests/responses to structured errors and notes optional body inclusion, but does not warn that headers, cookies, authorization tokens, request payloads, and response bodies may contain secrets or personal data. Because these errors are intended for logging, tracing, and APM export, this guidance can lead to broad sensitive-data exposure across logs and observability systems.
No suspicious patterns detected.