Agent Native

sensitive-logging-audit

The skill helps audit and fix sensitive data leaks in Python SDK logging, exceptions, and telemetry by collecting candidate sinks, manually tracing values…

by OpenAIOfficial publisher

Identity proven by GitHub's verified organisation badge (openai)

Agents
Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode
License
MIT (permissive)
Pin
125efa0pinned Oct 9, 2026
Context cost
about 970 tokenswhen the skill loads
GitHub stars
29,916on openai/openai-agents-python
Scripts
2 scripts

What it does

“Audit or fix sensitive-data exposure in Python SDK diagnostics, exceptions, logging, and telemetry.”
The author's description, from SKILL.md

Generated summary from the skill's own text

The skill helps audit and fix sensitive data leaks in Python SDK logging, exceptions, and telemetry by collecting candidate sinks, manually tracing values, applying redaction logic at runtime boundaries, and validating fixes with tests.

When to use it

  • Reviewing SDK diagnostics for credential or model data exposure
  • Implementing data redaction in debug logs and error handlers
  • Validating that sensitive information respects logging policy flags
  • Testing exception chains and telemetry for unintended data leakage

When not to

  • Applying automatic, policy-agnostic data redaction without manual review
  • Using collector results alone as proof of safe logging practices

Install

These commands install from the publisher's repository and need no account.

skills CLI

npx skills add openai/openai-agents-python --skill sensitive-logging-audit

Installs from the repository's default branch, which may have changed since the commit we checked.

GitHub CLI 2.90 or later

gh skill install openai/openai-agents-python sensitive-logging-audit@125efa029b4bfd84238bd2c4fd69c3406f802663

Installs the commit we checked (125efa0).

Copy by hand

Download the folder at 125efa0 and put it in .claude/skills/sensitive-logging-audit for Claude Code and in .agents/skills/sensitive-logging-audit for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.

Skill folder on GitHub at 125efa0

Copy for your agent

A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.

Prompt

Install the agent skill "sensitive-logging-audit" by OpenAI.

Source, pinned to commit 125efa029b4bfd84238bd2c4fd69c3406f802663:
https://github.com/openai/openai-agents-python/tree/125efa029b4bfd84238bd2c4fd69c3406f802663/.agents/skills/sensitive-logging-audit

1. Download that folder at exactly this commit. Do not use the default branch.
2. Copy every file unchanged, keeping the folder structure, into .claude/skills/sensitive-logging-audit/ for Claude Code and .agents/skills/sensitive-logging-audit/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist.
3. Do not edit the files, and do not run any script in the folder unless I ask you to.
4. When you are done, list the files you copied and where you put them.

Listing and checks: https://www.agentnative.dev/skills/openai/sensitive-logging-audit-openai-agents-python

SKILL.md at the pin

---
name: sensitive-logging-audit
description: Audit or fix sensitive-data exposure in Python SDK diagnostics, exceptions, logging, and telemetry.
---

# Sensitive Logging Audit

## Objective

Find candidate output sinks, trace their values manually, fix demonstrated leaks at shared runtime boundaries, and prove redaction with adversarial tests.

The collector is only a syntax-based search aid. It does not resolve Python aliases or control flow, certify policy guards, or prove that an absent candidate is safe.

## Workflow

### 1. Establish the review surface

- Work in the current checkout and preserve unrelated changes.
- Read `src/agents/_debug.py`, `src/agents/logger.py`, and the affected callers.
- Treat exception messages, arguments, tracebacks, causes, contexts, notes, names, URLs, and arbitrary values as potentially sensitive.
- Read [the Python redaction validation matrix](references/redaction-validation.md).

Run the collector tests, then collect candidates:

```bash
uv run python .agents/skills/sensitive-logging-audit/scripts/test_inventory.py
uv run python .agents/skills/sensitive-logging-audit/scripts/inventory_logging.py \
  --format json --output /tmp/sensitive-logging-candidates.json
```

The report intentionally contains no `policy`, `safe`, or guard classification.

### 2. Supplement the collector with source search

The collector does not follow assignments such as `emit = logger.error`. Search the source directly and inspect aliases, callbacks, wrappers, and reflective dispatch:

```bash
rg -n '\.(debug|info|warning|warn|error|exception|critical|fatal|log)\b' src/agents
rg -n '\b(print|pprint|pp|warn|warn_explicit|write|writelines|print_exc|print_exception)\b' src/agents
rg -n 'DONT_LOG_(MODEL|TOOL)_DATA|log_(model|tool|model_and_tool)_action' src/agents
```

Do not turn collector coverage or a textual guard into a security conclusion. Trace producers and callers.

### 3. Classify manually

Assign each reviewed path one disposition:

- `model`: model requests, responses, Realtime events, or derived values.
- `tool`: tool arguments, outputs, MCP data, tool events, or derived values.
- `model+tool`: either class may reach the sink.
- `operational`: demonstrated to contain only non-sensitive SDK metadata.
- `intentional-output`: explicitly user-facing output rather than diagnostics.
- `uncertain`: source tracing is incomplete.

Record evidence in the audit report. The script does not validate or inherit dispositions.

### 4. Fix runtime boundaries

Before changing runtime behavior, use `$implementation-strategy`.

- Check the relevant `_debug.DONT_LOG_MODEL_DATA` and `_debug.DONT_LOG_TOOL_DATA` flags before formatting or inspecting sensitive values.
- Redact mixed model/tool values when either flag disables data logging.
- In redacted mode, emit a fixed message and omit sensitive `args`, `extra`, and `exc_info`.
- Build diagnostic-only context lazily so redacted mode never reads it.
- Preserve useful diagnostics when sensitive-data logging is explicitly enabled.
- Keep logging failure from changing fallback, cleanup, event, rejection, or cancellation behavior.
- For MCP URLs, remove credentials, query parameters, and fragments in diagnostic mode; never use sanitized names as a substitute for fixed redacted messages.

### 5. Prove caller behavior

Add tests at every changed caller boundary. Inspect the complete `LogRecord`, not only rendered text. Test both redacted policies, diagnostic mode, hostile objects, exception chains, and the caller's observable fallback or cleanup behavior as applicable.

### 6. Re-run and close out

Re-run the collector, the manual searches, focused tests, and applicable repository gates. Use `$code-change-verification` for runtime or test changes and `$pr-draft-summary` when required.

Report candidate counts as search coverage only. Lead with confirmed leaks fixed, retained intentional output, reviewed uncertainty, and verification results. Never report a clean collector result as proof that no sensitive logging path exists.

From openai/openai-agents-python at 125efa0, shown as plain text under its license: MIT (permissive). The license text is in LICENSE.

View SKILL.md on GitHub at 125efa0

Files

5 files, 26 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.

Skill folder on GitHub at 125efa0
All 50 skills from OpenAI

More from OpenAI

  • code-change-verification

    Runs formatting, linting, type checking, and test verification for SDK code changes after review.

    Contains scripts

    Codex · about 1.3K tokens · pinned 7 days ago

  • docs-sync

    This skill audits English SDK documentation by comparing features and configuration options in the codebase against the current docs, then proposes or…

    Claude Code, Codex, Cursor +4 · about 1.2K tokens · pinned 7 days ago

  • examples-run-analysis

    Analyzes logs and artifacts from manual examples runs to validate example behaviors, identify failures, and classify issues.

    Claude Code, Codex, Cursor +4 · about 1K tokens · pinned 7 days ago

  • final-release-review

    Audits Python SDK release candidates or plans against the previous release, comparing diffs for regressions, API changes, and version compatibility.

    Contains scripts

    Claude Code, Codex, Cursor +3 · about 5.4K tokens · pinned 7 days ago

  • implementation-final-review

    This skill guides agents through a structured review process for completed implementation changes before final verification.

    Contains scripts

    Claude Code, Codex, Cursor +3 · about 1.9K tokens · pinned 7 days ago

  • implementation-kickoff

    This skill manages an isolated implementation workflow using a dedicated git worktree, keeping the user's original checkout unchanged while building a…

    Contains scripts

    Codex · about 2.9K tokens · pinned 7 days ago

All Security skills
  • django-access-review

    This skill guides agents through investigating Django and Django REST Framework code for IDOR and access control vulnerabilities.

    by SentryOfficial publisher

    Claude Code, Codex, Cursor +4 · about 2.5K tokens · pinned 7 days ago

  • secret-serialization

    This skill detects credential leaks through generated serialization when types storing secrets are converted to strings or dictionaries by logging, tracing…

    by SentryOfficial publisher

    Claude Code, Codex, Cursor +4 · about 2.4K tokens · pinned 7 days ago

  • ai-inventory

    This skill generates an AI Bill of Materials (AIBOM) for Python projects by identifying AI models, datasets, frameworks, and tools using the Snyk AIBOM API.

    by SnykOfficial publisher

    Claude Code, Codex, Cursor +4 · about 1.7K tokens · pinned 7 days ago

  • authoring

    This skill helps agents author Falcon Fusion workflow YAML files by discovering action IDs from the live API, validating YAML against the schema, and…

    by CrowdStrikeOfficial publisher

    Contains scripts

    Claude Code · about 5.2K tokens · pinned 7 days ago

  • aig-scanner

    This skill submits security scanning tasks to Tencent AI-Infra-Guard via Python CLI, analyzing AI infrastructure, tools, skills, agents, and LLM jailbreak…

    by TencentCommunity

    Contains scripts

    Agents not labelled yet · about 3.5K tokens · pinned 7 days ago

  • security-reviewer

    This skill performs multi-language security reviews of web applications, APIs, and CLIs by checking code for common vulnerabilities across eight categories…

    by Security-Phoenix-demoCommunity

    Claude Code · about 1.1K tokens · pinned 7 days ago

Open roles at OpenAI

5 of 239 open roles on the jobs board

The skills listed here are third-party software, collected from public GitHub repositories as a catalog of recent skills and provided as is. Agent Native does not write or control them and is not responsible for any harm, loss or damage caused by installing or using them. Labels and checks describe what we saw at one commit and are not a guarantee. Read a skill's files before you run it. Terms of use