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Build the audit as a read-only pull request check: parse proposed source as data, apply explicit syntax rules, and emit findings in a stable order. For ordinary contributions, use GitHub Actions’ pull_request event with only the permissions the job needs. Do not run pull request code in a privileged workflow. An AST can identify patterns in syntax; it cannot prove that code is safe.

Choose the workflow event before designing the audit

The trust boundary is the first design decision. A useful AST check usually needs to read proposed source, not credentials or write access. That makes pull_request the appropriate starting point for ordinary contribution checks. GitHub documents that fork pull requests under this event receive a read-only GITHUB_TOKEN and have secrets withheld by default.

pull_request_target runs with the base repository’s trust and privileges. The danger is not checkout by itself: it is checking out untrusted pull request content and then executing it with those privileges. That includes running a Makefile, tests, build scripts, dependency installation hooks, or attacker-controlled configuration.

  • Use pull_request when the audit only needs to inspect files and report a check result.
  • Use pull_request_target only when a genuine requirement needs its elevated context. Keep the inspection isolated, do not execute checked-out content, and restrict secrets and token permissions.
  • Do not treat AI-generated changes as a special trust category. Apply the same untrusted-input boundary to all proposed code, regardless of who or what produced it.

GitHub’s security guidance warns that code checked out in a pull_request_target workflow must only be inspected as data, never executed. Review the complete workflow path, not just the parser command, for any step that could run pull request content.

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Give the job the least authority it needs

Set workflow permissions explicitly. For a read-only source inspection, a typical baseline is contents: read; when one or more permissions are specified, GitHub sets omitted permission scopes to none. Do not grant write access merely because another workflow uses it.

If the check must create a comment or publish a result through the API, identify the precise permission that operation requires and grant it only to the job that performs it. Keep credentials out of the parser process where possible. A parser that reads files and writes a local report should not need repository secrets.

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Pin the inputs that define parsing

“Deterministic” should mean that the same source, parser/runtime version, options, and rule set produce the same findings in the same order. It is an engineering contract, not a property GitHub Actions or an AST parser guarantees automatically.

  • Pin the language runtime and parser. Record the version used for each run. Python’s abstract syntax grammar can change between releases, so an unpinned interpreter can change what the audit accepts or how it represents syntax.
  • Specify parser options. Choose the parse mode and relevant options explicitly rather than inheriting mutable defaults. In Python, ast.parse accepts a filename, mode, and options including feature_version and optimize; behavior and available options are version-sensitive.
  • Version the policy separately. A rule change and a parser upgrade are different changes. Make each reviewable on its own and include the policy version alongside the parser/runtime version in the report.
  • Pin workflow dependencies too. Declare runtime versions and action references in the workflow. Review third-party actions and use immutable, reviewed references for production workflows rather than relying on a moving version tag.

For example, a Python audit should parse a file in a declared mode such as exec, with the runtime and options fixed by the workflow. Python’s documentation also notes that parsing to an AST does not guarantee the source can be compiled or executed successfully; compilation can still raise SyntaxError. Keep the claim narrow: the audit finds syntax patterns covered by its rules.

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Define what an AST rule can and cannot establish

Rules should name the syntax nodes and relationships they inspect, including allowed as well as disallowed cases. For example, a rule could flag a call whose syntactic callee is a direct name such as eval. That detects that particular spelling in the parsed tree; it does not automatically catch aliases, dynamic lookup, wrapper functions, or equivalent runtime behavior.

Do not describe a syntactic match as proof of malicious intent, and do not claim comprehensive semantic analysis unless the implementation actually resolves aliases and runtime dispatch. AST checks are useful as a predictable gate for narrowly stated policies, such as rejecting specified constructs or requiring a particular form. They do not establish runtime safety, semantic correctness, or harmless behavior.

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Emit findings in a stable, reviewable format

Use machine-readable output so reviewers and later automation can consume the same result. A practical finding can include:

  • repository-relative file path;
  • start and end line and column, when available;
  • stable rule identifier and policy version;
  • severity; and
  • a concise explanation of the matched syntax.

Sort findings by a documented key, for example path, start line, start column, and rule ID. Do not let traversal order, timestamps, runner IDs, or unordered data structures affect the comparison. Python’s AST can expose source-location attributes when requested, but neither Python nor GitHub prescribes a universal audit report schema; choose one, document it, and keep it stable.

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Keep parser failures distinct from policy violations. A syntax error should identify the path and parser error and state that inspection of that file failed. A policy violation should identify the matched location and rule. If a file is excluded, unsupported, too large, or cannot be parsed because of a resource limit, report that outcome rather than silently implying that it passed. Decide in advance whether each such condition fails the check or marks the audit incomplete.

Keep the inspection path non-executing

The audit job should read source files as data and invoke only the pinned parser and audit code. Do not add dependency installation, project tests, builds, configuration loading, or other commands that may execute pull request-controlled content to a privileged inspection flow. Parsing is not a sandbox; resource limits and hostile inputs still need an explicit policy.

Review every step that consumes pull request data, including shell arguments, artifacts, caches, dependency resolution, and third-party actions. Avoid placing values such as a pull request title or branch name directly into shell code. Keep workflow configuration visible at .github/workflows/ so maintainers can review the trigger, permissions, runtime, action references, and commands as one trust boundary.

Review GitHub’s current pull_request_target policy

GitHub’s documentation currently says the default policy for affected public repositories using pull_request_target is in evaluate mode, with enforcement scheduled for November 2, 2026. This is a changing platform policy, not a permanent workflow guarantee. Check GitHub’s policy insights and current documentation before changing a live workflow; repositories that need elevated behavior should determine whether to move to pull_request or configure an applicable policy.

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