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Run a coding agent as an untrusted, least-privileged contributor—not as a release operator. Give it an isolated job, read-only repository access where possible, no production or signing secrets, tightly limited tools and network egress, and a reviewable branch or pull request as its only output. Keep tests, security checks, merge approval, and deployment in separate controls that the agent cannot bypass.
The safe operating model
A coding agent can read files, execute commands, call external tools, and propose or apply code changes. Those capabilities make it useful in CI/CD and also make it a potentially manipulable process. An agent does not become trusted because it is labeled “AI,” runs inside a workflow, or comes from a vendor that documents safeguards. Treat the agent and everything it reads as an untrusted workload.
The practical pattern is a staged pipeline:
- Untrusted analysis job: check out the code, issue, or pull request with the minimum read permissions and run the agent in a disposable environment.
- Proposal output: let the agent write only to a dedicated branch, patch artifact, comment, or draft pull request. Validate the output before any privileged operation.
- Independent verification: run normal tests, static analysis, dependency checks, secret scanning, and policy checks outside the agent’s own claims.
- Human-controlled promotion: require a qualified reviewer to approve merge, release, signing, or deployment. Put credentials for those actions in a separate downstream job.
This design limits the blast radius if a prompt is injected, a dependency is malicious, the agent makes a bad change, or the runner is compromised.
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Begin with work that produces a proposal rather than an irreversible side effect. Suitable first tasks include review comments, CI-failure investigation, documentation edits, test suggestions, issue triage, and a patch on a dedicated branch. Do not begin by granting merge, release, signing, production, or broad cloud authority.
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Define the task contract
- State exactly which repository, branch, directories, and files the agent may inspect.
- Specify whether it may edit files, create a branch, open a draft pull request, or only report findings.
- Define a maximum runtime, tool list, and network destinations.
- Require machine-readable output such as a patch, test report, or structured review rather than an instruction to “do whatever is necessary.”
- Make failure safe: a timeout or malformed output should stop the workflow, not trigger a fallback deployment.
Use a dedicated branch or draft pull request
Keep agent changes reviewable and easy to discard. A draft pull request prevents an agent from silently merging its own work and gives reviewers a single place to inspect source changes, workflow edits, dependency updates, and generated artifacts.
Threat model: what can go wrong
| Threat | Why it matters | Practical control |
|---|---|---|
| Prompt injection in an issue, pull request, or repository file | Attacker-controlled text can be interpreted as instructions to invoke tools, alter code, or disclose data. | Mark external content as untrusted, limit tools and egress, and require review of every proposed write. |
| Shell injection through workflow expressions | Workflow expressions are expanded before the shell runs; an issue title, branch name, or comment can alter the generated command. | Pass event values through environment variables and quote shell expansions. Never splice uncontrolled values directly into shell source. |
| Secret or token exposure | Agent code, a malicious dependency, or a process with host access can read credentials. | Keep secrets out of the agent job, scope tokens narrowly, and use short-lived credentials in a separate privileged stage. |
| Unsafe patch or dependency | Generated code can introduce vulnerabilities, licensing problems, data loss, or an unexpected network dependency. | Run deterministic tests and security checks independently; inspect dependency and configuration changes manually. |
| Compromised or shared runner | Persistent state can expose tokens, caches, files, or other repositories to later jobs. | Use disposable isolated runners and segment self-hosted runner groups by repository and trust level. |
| Changed agent configuration | Edits to workflow files, agent rules, tool definitions, or MCP configuration can silently expand authority. | Treat those files as security-sensitive code, protect them with review and integrity checks, and apply stricter branch rules. |
Build the first isolated job
Use read-only permissions by default
For a review or investigation job, grant only the repository and metadata reads it needs. On GitHub Actions, a typical starting profile is contents: read, with read access to pull requests or issues only when the task requires it. Do not grant write permissions merely because the agent might eventually need them. Add one narrowly scoped write permission only for a defined operation such as creating a branch or draft pull request.
Keep credentials out of the agent process
Do not expose production, deployment, signing, package-publishing, or broad cloud credentials to the agent. If the provider API requires a key, make the key available only to the smallest action or wrapper process that needs it, and prevent agent-generated commands from inheriting that environment. A process that can inspect the runner, parent environment, command line, temporary files, or logs may be able to recover a key.
When a later step genuinely needs a credential, make it a separate job with a separate permission boundary. Pass only a validated artifact or commit identifier from the agent job. Prefer short-lived, task-scoped credentials where the platform supports them.
Disable credential persistence after checkout
When using a checkout action for an agent job, configure it so the repository token is not persisted in the local Git configuration. The Codex Action README uses persist-credentials: false together with a read-only contents permission as an example of this workflow shape. Those settings reduce exposure but do not secure every deployment by themselves.
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Example read-only review workflow
name: Agent review
on:
pull_request:
permissions:
contents: read
pull-requests: read
issues: read
jobs:
review:
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Check out source without persisted credentials
uses: actions/checkout@v4
with:
persist-credentials: false
fetch-depth: 1
- name: Save untrusted event data as files
env:
PR_TITLE: ${{ github.event.pull_request.title }}
PR_BODY: ${{ github.event.pull_request.body }}
PR_NUMBER: ${{ github.event.pull_request.number }}
run: |
set -euo pipefail
printf '%s' "$PR_TITLE" > /tmp/pr-title
printf '%s' "$PR_BODY" > /tmp/pr-body
printf '%s' "$PR_NUMBER" > /tmp/pr-number
- name: Run the agent in review-only mode
run: |
set -euo pipefail
agent-cli review
--repo "$GITHUB_WORKSPACE"
--title-file /tmp/pr-title
--body-file /tmp/pr-body
--output /tmp/review.json
- name: Publish review artifact
uses: actions/upload-artifact@v4
with:
name: agent-review
path: /tmp/review.jsonThis is a shape to adapt, not a universal security guarantee. Pin actions to trusted references according to your organization’s supply-chain policy, set a timeout, and configure the agent CLI so it cannot write or invoke tools beyond the review contract. The event values are placed in environment variables and quoted in the shell instead of being inserted directly into command source.
Handle untrusted input explicitly
Prompt injection can arrive indirectly. Issue descriptions, pull-request bodies, comments, branch names, source files, test fixtures, generated documentation, and repository-local instruction files may all influence an agent. A file named AGENTS.md, AGENTS.override.md, or a configured fallback project document is still untrusted when it comes from pull-request-controlled content. The fact that a file looks like project policy does not make it authoritative.
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Separate data from instructions
- Tell the agent which text is data to analyze and which rules are system-level policy.
- Load external text through files or structured fields rather than concatenating it into a high-privilege instruction string.
- Reject instructions in repository content that request secrets, permission changes, disabling checks, or contacting an external service.
- Log the exact task configuration and input identifiers so a reviewer can reconstruct what the agent saw.
Avoid shell interpolation vulnerabilities
GitHub expands expressions such as event fields before the shell script starts. Writing an expression directly inside a run: block can therefore turn attacker-controlled text into shell source. Put the value in env:, then use a quoted shell variable such as "$PR_BODY". Do the same for branch names, labels, usernames, and comment text. Validate expected formats before using a value in a path, argument, or command.
Do not use a privileged event as a shortcut
Workflows that run with write tokens or secrets for pull-request events require special care, especially when the request can originate from a fork. Checking out untrusted code in a privileged context can let that code read credentials or attack the runner. If a privileged event is unavoidable, check out only trusted base-branch content, keep untrusted data as inert input, and place the privileged operation behind an explicit approval gate.
Constrain tools, network, and egress
List the tools the task needs and deny the rest. A review agent may need file reads, a compiler, and test commands; it usually does not need cloud CLIs, package publishing, SSH, browser automation, or arbitrary code execution outside the repository.
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Network policy
- Disable network access for tasks that can run entirely on checked-out source and preinstalled dependencies.
- If downloads are required, allow only the package registries or services needed for that job.
- Review MCP servers, plugins, webhooks, and telemetry endpoints as additional trust boundaries.
- Prevent the agent from sending source code, prompts, logs, or secrets to unapproved destinations.
A sandbox or firewall reduces reachable resources; it does not prove that an agent’s output is correct or safe. Verify the actual boundary in your runner configuration rather than assuming a product’s default applies to your workflow.
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Mount only the repository and temporary working directories. Avoid sharing host sockets, cloud credential files, Docker sockets, package-manager caches, or directories from other repositories. Run as a non-root user when possible, apply CPU and memory limits, and destroy the environment after the job.
Keep verification independent of the agent
An agent can claim that tests passed or can modify the test command itself. Run verification in a separate job or at least in a separately configured step whose commands are not selected by the agent.
- Build and unit-test the exact commit or patch that will be reviewed.
- Run static analysis, dependency vulnerability checks, secret scanning, license policy checks, and infrastructure-as-code validation.
- Compare dependency manifests and lockfiles explicitly; require review for new packages, registry changes, install scripts, and post-install hooks.
- Use branch protection so required checks cannot be skipped by changing workflow definitions in the same pull request.
- Require a qualified human to approve workflow files, deployment scripts, dependency manifests, agent instructions, and security configuration.
Do not allow an unattended agent recommendation to install dependencies, publish an artifact, merge code, or release to production. A downstream job should consume a validated commit or artifact, not arbitrary commands generated by the agent.
Separate privileged operations
Use a downstream promotion job
Keep signing, deployment, release, and production credentials in a job that the agent cannot invoke directly. The job should accept a specific commit SHA or immutable artifact, re-run policy checks, and require an approval environment or equivalent human gate.
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Prefer short-lived credentials
Use an identity with the smallest scope and shortest lifetime available. Bind it to the repository, environment, branch, and operation. Revoke or rotate it when a run is cancelled, a runner is suspected of compromise, or logs indicate unexpected access.
Validate outputs before promotion
- Confirm the artifact was built from the reviewed commit.
- Verify checksums or signatures where your supply chain supports them.
- Reject output that contains unexpected binaries, generated credentials, workflow permission changes, or new network endpoints.
- Require a human to approve any change to deployment policy or release configuration.
Protect the runner boundary
Disposable hosted runners are generally easier to reason about for untrusted pull requests than persistent self-hosted machines. A self-hosted runner may retain files, credentials, caches, network routes, and service-account access after the job ends. GitHub warns that fork-based pull requests can compromise self-hosted runners and may expose secrets or tokens depending on workflow settings.
If self-hosted runners are required
- Use separate runner groups for public contributions, internal repositories, and production operations.
- Do not share a runner between untrusted pull requests and jobs that hold sensitive state.
- Reset or reimage the machine after each untrusted job; clearing the workspace alone is insufficient.
- Block access to metadata services, internal networks, host administration sockets, and unrelated repositories.
- Monitor outbound connections and retain host-level audit records.
An environment approval gate does not make a non-isolated runner safe if untrusted code can execute before the gate or inspect persistent host state.
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Retain workflow logs, agent session records, input identifiers, tool calls, produced patches, test results, and approval events for a period that matches your incident-response requirements. Record who or what initiated the task and which agent version, configuration, and tool definitions were used.
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Agent rules, MCP definitions, workflow YAML, container images, and prompt templates are security-sensitive code. Protect them with code owners, required review, change history, and integrity monitoring.
Platform-specific behavior and limits
Codex Action-style workflows
The Codex Action README demonstrates a pull-request review workflow using a read-only contents permission and checkout with persisted credentials disabled. It also describes supplying a provider API key as a GitHub Actions secret. Treat that as an implementation example, not proof that those two settings secure every use case. Keep the key out of agent-generated subprocesses and remember that a process able to inspect runner state may expose it.
GitHub Copilot cloud agent
GitHub’s documentation says agent-created pull requests are drafts requiring human review and merge, and that workflow runs are held for approval by default. It also describes branch restrictions, prompt-injection mitigations, session logs, and audit records. These are documented product behaviors that can change with settings; verify the controls enabled in your organization.
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The Agentic Workflows documentation describes read-only repository permissions by default, validated safe outputs for writes, downstream isolation for secrets, threat detection, firewalled execution, and role-based access. Those features belong to that framework. An arbitrary workflow that invokes an agent CLI does not acquire them automatically. Budget for both GitHub Actions minutes and model-inference costs when estimating operation.
Gemini CLI issue-specific remediation
A Cloud Security Alliance note describes a specific Gemini CLI vulnerability with a source-reported CVSS score of 10.0. Its remediation guidance names Gemini CLI 0.39.1 or later and google-github-actions/run-gemini-cli 0.1.22 or later. Because these versions are issue-specific and can become outdated, verify the current advisory and releases before rollout. Audit older workflows that processed uncontrolled content, rotate credentials if exposure is suspected, and review logs and artifacts.
Choose an integration approach by control, not branding
| Approach | Execution and isolation | Permissions and secrets | Write and approval controls | What to verify |
|---|---|---|---|---|
| Native agent platform | Often provides documented runner and service boundaries, but settings may vary. | Check whether secrets are outside the agent runtime and how tokens are scoped. | Confirm draft-only behavior, workflow approval, and branch restrictions. | Session logs, audit events, tool policy, network controls, and current defaults. |
| Agentic workflow framework | May include firewalls, role-based access, and validated outputs. | Confirm downstream secret isolation and the exact permission defaults. | Inspect how proposed writes are validated and who can approve them. | Framework version, Actions-minute usage, inference cost, and override paths. |
| Custom CLI action | Your runner, container, shell, and network rules define the boundary. | You must design token scope, secret handling, and environment cleanup. | You must implement patch validation, review gates, and promotion separation. | Every command, inherited environment variable, mounted path, plugin, and egress route. |
For any option, answer seven questions before enabling it: where does code execute; can the agent read or write repository content; can its process read secrets; which tools, network routes, and MCP integrations are allowed; are writes validated; are workflow, merge, and deployment actions human-approved; and which session and audit records are retained?
Quick Recap
Roll out in controlled stages
- Inventory: list repositories, runner types, secrets, workflow permissions, agent tools, external services, and protected environments.
- Prototype: run a read-only review or CI-investigation task on a disposable runner with synthetic or non-sensitive data.
- Measure: inspect logs, network connections, file access, token use, false positives, and output quality.
- Expand cautiously: permit branch or draft-pull-request writes only after the read-only behavior is understood.
- Add human gates: require approval for merges, workflow changes, dependency updates, releases, signing, and deployment.
- Reassess: review agent, action, runner-image, and dependency updates; repeat threat modeling when tools or permissions change.
Incident response when an agent may be compromised
- Stop the workflow and disable the affected automation or runner.
- Revoke and rotate any token, API key, signing credential, or cloud identity that the process could read.
- Preserve workflow logs, agent sessions, artifacts, runner telemetry, and the exact commit or pull request.
- Review file access, command history, outbound connections, repository changes, and downstream jobs.
- Quarantine suspicious branches, artifacts, dependencies, and releases.
- Rebuild the runner from a known-good image, patch the vulnerable component, and narrow permissions before re-enabling automation.
Production-readiness checklist
- The agent job has a single documented purpose and a timeout.
- Repository, issue, and pull-request content are explicitly treated as untrusted.
- Workflow event values are passed through environment variables and quoted, not interpolated into shell source.
- Default permissions are read-only and writes are limited to a defined branch or draft pull request.
- Production, deployment, signing, and broad cloud secrets are unavailable to the agent process.
- Tools, filesystem mounts, network routes, plugins, and MCP servers are allow-listed.
- The runner is disposable or isolated from sensitive state, especially for fork-based contributions.
- Tests, static analysis, dependency checks, secret scanning, and policy checks run independently.
- Workflow, dependency, deployment, and agent-configuration changes receive stricter human review.
- Merge and deployment require human approval and consume an immutable, validated output.
- Logs, session records, audit events, artifacts, and initiating identities are retained.
- There is a tested stop, revoke, rotate, and rebuild procedure.
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