Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add fatihkan/badi --skill sc-data-exposuregit clone --depth 1 https://github.com/fatihkan/badiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/fatihkan/badi/sc-data-exposure)<a href="https://agentmods.dev/skills/fatihkan/badi/sc-data-exposure"><img src="https://agentmods.dev/badge/skills/fatihkan/badi/sc-data-exposure.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.01073 |
| Opus 5 | $0.00012 | $0.00536 |
| Sonnet 5 | $0.00005 | $0.00215 |
| Haiku 4.5 | $0.00002 | $0.00107 |
Grade A, and why
sc-data-exposure scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
95% identical to sc-data-exposure — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SC: Sensitive Data Exposure
Purpose
Detects sensitive data exposure including PII in logs, stack traces in production responses, debug mode enabled in production, sensitive data in URLs, source maps deployed to production, exposed .git directories, backup files, and excessive data in API responses. Focuses on data leaving the application boundary unintentionally.
Activation
Called by sc-orchestrator during Phase 2. Always runs.
Phase 1: Discovery
Keyword Patterns to Search
# Debug/verbose modes
"DEBUG = True", "debug: true", "NODE_ENV.*development",
"FLASK_DEBUG", "APP_DEBUG", "RAILS_ENV.*development",
"stackTrace", "stack_trace", "printStackTrace"
# PII in logs
"logger.*email", "log.*password", "console.log.*token",
"logging.*credit", "log.*ssn", "print.*secret"
# Sensitive data in URLs
"?token=", "?api_key=", "?password=", "?secret=",
"?access_token=", "?session="
# Information disclosure
".git/", "phpinfo()", "server_info", "X-Powered-By",
".env", "wp-config.php", "web.config", "application.properties"
# Source maps
".map", "sourceMappingURL", "//# sourceMappingURL"
# Verbose error responses
"res.status(500).send(err)", "return error.message",
"traceback.format_exc()", "e.getMessage()"
Vulnerability Patterns
1. Stack Trace in Production:
// VULNERABLE: Raw error sent to client
app.use((err, req, res, next) => {
res.status(500).json({ error: err.stack });
});
// SAFE: Generic error in production
app.use((err, req, res, next) => {
console.error(err.stack); // Log internally
res.status(500).json({ error: 'Internal server error' });
});
2. PII in Logs:
# VULNERABLE: Logging sensitive data
logger.info(f"User login: email={email}, password={password}")
logger.debug(f"Payment: card={card_number}, cvv={cvv}")
# SAFE: Redact sensitive fields
logger.info(f"User login: email={mask_email(email)}")
logger.debug(f"Payment: card=****{card_number[-4:]}")
3. Debug Mode in Production:
# VULNERABLE: Django debug mode
# settings.py
DEBUG = True # Exposes full stack traces, SQL queries, template context
# SAFE
DEBUG = os.environ.get('DEBUG', 'False') == 'True'
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 129 lines · 23 tokens per session scan A fe66f113cbca
sc-data-exposure is a skill published in the GitHub repository fatihkan/badi (7 stars, last pushed 2d ago), licensed MIT. It adds 23 tokens to every session and 1,073 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to sc-data-exposure, differing in 1 line, and is treated as a copy.
Other skills, from other repositories
pr-triage
4-phase PR backlog management with audit, deep code review, validated comments, and optional worktree setup. Use when triaging pull requests, catching up on pending code reviews, or managing a backlog of open PRs. Args: 'all' to review all, PR numbers to focus (e.g. '42 57'), 'en'/'fr' for language, no arg = audit…
audit-agents-skills
Audit Claude Code agents, skills, and commands for quality and production readiness. Use when evaluating skill quality, checking production readiness scores, or comparing agents against best-practice templates.
eval-agents
Audit Claude Code agents defined in .claude/agents/ for description specificity, model tier appropriateness, tools scoping, and system prompt quality. Detects dispatch ambiguity between agents, flags over-permissive tool grants, and checks for human-in-the-loop patterns that break programmatic orchestration. Use when…
issue-triage
3-phase issue backlog management with audit, deep analysis, and validated triage actions. Use when triaging GitHub issues, sorting bug reports, cleaning up stale tickets, or detecting duplicate issues. Args: 'all' to analyze all, issue numbers to focus (e.g. '42 57'), 'en'/'fr' for language, no arg = audit only.
check-cache-bugs
Audit Claude Code setup for cache bugs (CC#40524): sentinel, --resume/--continue, attribution header + ArkNill B3/B4/B5.
git-ai-archaeology
Analyze AI config evolution in a git repo. Use when mapping AI adoption history, finding when configs were first introduced, charting commit velocity by month, or identifying maturity phases in a project's AI tooling.