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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsIf you are bringing coding agents into a real repository, the question that matters is not whether the agent can write working code. It is whether your team can still show that requirements, security checks, tests, human approval and release controls hold once an agent is taking multi-step actions on its own. What SDLC gates should I enforce so AI coding agents don’t silently skip security, testing, review, or release controls? Enforce the ten gates below, scaled to the risk of the code being changed.
The reason these checks need to be explicit is that an agent rarely announces that it skipped a step. A weakened test, a file read outside the task, or an edit to a CI workflow can sit inside a diff that otherwise looks finished. Each gate names a point where a person or a tool checks something the agent cannot be relied on to check for itself.
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What the sources establish, and what they do not
Two bodies of guidance anchor this list. NIST describes a notional software development lifecycle with seven phases, Plan, Develop, Build, Test, Release, Deploy and Operate, and states that secure practices should be integrated into each organization’s own SDLC. Its Secure Software Development Framework (SSDF) is a customizable, risk-based framework rather than a fixed checklist. NIST SP 800-218A, finalized on July 26, 2024, adds an AI-specific community profile to the SSDF. That date is a publication date; the document does not measure how well any coding agent performs.
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The ten gates are an editorial synthesis of that guidance. Neither NIST nor OWASP has published or mandated this exact list, so treat it as an implementation starting point rather than a compliance checklist. No published source establishes how often coding agents skip SDLC controls, so this article makes no frequency claim. The case for each gate rests on the control logic explained below.
Why agents change the control picture
NIST’s NCCoE DevSecOps introduction, titled “Introduction — Secure Software Development, Security, and Operations (DevSecOps) Practices,” describes agentic AI as capable of executing multi-step development and DevSecOps tasks. It states:
“While these capabilities have the potential to accelerate the software delivery, organizations should ensure that appropriate governance, authorization controls, auditability, and human oversight are maintained for agent actions and outputs.”
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Once an agent can act across the repository, the terminal and the pipeline, authorization, audit trails and human oversight stop being optional hygiene. They become the controls that let you verify everything else.
The ten gates
Each gate below states the control, why it matters for agents, and how to check it. Gates 1 to 4 apply before and while the agent is set up. Gates 5 to 8 apply to the proposed change. Gates 9 and 10 apply at merge and after release.
Gate 1: Scope and requirements
Before the agent starts, write down the task, the expected behavior, the security requirements and the work it must not perform. NIST places requirements and secure design in the Plan phase, ahead of development. An agent given a vague goal will fill the gaps with its own assumptions, so the brief has to close them.
A usable task brief includes:
- the goal and acceptance criteria, stated in testable terms
- the security requirements that apply to the change, such as input validation or authentication behavior
- an explicit out-of-scope list, for example “no changes to authentication code, CI workflows or dependency manifests”
- the files or directories the agent may modify
Gate 2: Tool qualification and threat model
Before adoption, evaluate the coding tool, the agent and every connected service for the risks OWASP highlights: untrusted input, insecure output handling, excessive agency (an agent holding more capability than its task requires) and supply-chain dependencies. The threat model should answer these questions:
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- Which inputs can reach the agent? This includes issue text, pasted logs, fetched web pages and README files inside third-party packages.
- What happens if the agent’s output is executed, merged or rendered without a check?
- Which plugins, extensions or connected services does the agent load, and who maintains them?
- Can the agent take an action the task did not require?
Gate 3: Permission and environment
Grant only the repository access, tools, credentials and actions the assigned task needs. NIST calls for governance and authorization controls over agent actions and identifies excessive privileges as a risk. Higher-impact actions, such as merging, deploying, changing secrets or altering permissions, should stay behind human approval.
Verify that:
- the agent works on a feature branch, never a protected branch
- its credentials are scoped to that repository and are not a maintainer’s personal token
- production credentials and cloud administrator access are absent from the agent’s environment
- the agent cannot push to protected branches or trigger deployments on its own
Gate 4: Context and data exposure
A coding tool may transmit more than the file you have open. OWASP cautions that assistants may send broad project context, and that .gitignore does not stop an AI tool from reading files. Excluding a path from version control does not exclude it from the tool.
Before enabling an agent on a repository:
- Read the tool’s documentation on what it sends, including repository files and terminal context, and record the answer.
- Configure the tool’s own exclusion settings for secrets, private keys, customer data and environment files. Confirm the exclusion works by testing it with a dummy file.
- Keep credentials out of the working tree altogether, injecting them at runtime from a secrets manager.
Gate 5: Change boundary
The proposed diff should be inspectable against a clear task boundary. Changes outside the expected scope deserve heightened review, especially changes to tool configuration and infrastructure. NIST calls for traceability of models, modifications and annotations, so record which agent and task produced each change.
Before review, list every changed file and compare it with the allowed paths:
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git diff --name-only origin/main...HEADAnything outside the task’s allowed list fails the gate until a human explains it. Tag the pull request or commit with the tool, model version and task identifier so provenance survives the merge.
Gate 6: Test integrity
A green test run proves less than it appears to. The agent may have edited the tests it was supposed to satisfy. OWASP’s “Secure Coding with AI” cheat sheet states the core point directly:
“A passing test suite generated by the same agent that produced the code provides no independent assurance.”
Review every test change for:
- deleted test cases or removed assertions
- assertions weakened until they only check that code runs or that a value is not null
- mocks or stubs that replace the very behavior under test
- newly added skip or expected-failure markers
Then add negative and adversarial tests, such as invalid input, unauthorized access and boundary values, written by someone other than the agent. Review the test directories as a separate diff, for example git diff origin/main -- tests/, adjusting the path to your layout.
Gate 7: Independent security validation
Run the security checks appropriate to the change, and review their results yourself rather than accepting the agent’s account that the code is secure. NIST recommends established security validation and testing. OWASP advises independent analysis and security-critical tests written by hand. Typical choices are static analysis, dependency checks and secret scanning, run in a pipeline stage the agent cannot modify.
Gate 8: Build and supply-chain changes
Agent edits to package scripts, build files, workflow definitions, container files and deployment configuration deserve their own review step. OWASP flags these files for extra scrutiny because they can run automatically, often in a trusted context with access to secrets and deployment credentials. Require explicit approval whenever an agent change can execute on its own in such a context.
- Typical paths to watch include
package.jsonscripts,Makefile,Dockerfile,.github/workflows/, and Terraform or Helm files. - Use code-owner rules so changes to these paths require approval from a designated owner. Many Git hosting platforms support this, though the mechanism differs by platform.
- Do not let an agent-authored workflow run with secrets before a human has reviewed it.
Gate 9: Human review and approval
A responsible developer must review, understand and approve the change before it merges. AI review comments can assist that reviewer, but they cannot stand in for the approval. Accountability stays with the human who accepts and commits the change.
A practical test for the approver: can they explain, in their own words, what each changed file does and why the tests would fail without it? If not, the change is not approved.
Gate 10: Release, monitoring and learning
Keep your normal release and deployment approvals in place for agent-authored changes, so the agent gains no faster route to production. NIST’s lifecycle continues through Release, Deploy and Operate, and its model calls for logged, traceable AI outputs reviewed through established control gates.
- Log agent sessions, the tasks they were given and the changes they produced, retained under your existing records policy.
- Tag agent-authored releases so that incidents, rollbacks and defects can be traced back to the agent’s work.
- Feed every escaped defect and every gate failure back into the task-brief template from Gate 1 and the permission list from Gate 3.
Evaluating an agent setup
When comparing tools or configurations, put the same questions to each one. The table lists the dimensions that matter and the evidence to request for each.
| Dimension | Question to answer | Evidence to request |
|---|---|---|
| Permission scope and approval boundaries | Which actions can the agent take without a human approving them? | A written list of default permissions and the approval points that override them |
| Context transmitted | What code and terminal context leaves the developer’s machine? | The tool’s documentation of transmitted context and its exclusion settings |
| Provenance | Can each change be traced to the model, tool and task that produced it? | Sample audit records or commit metadata from a test repository you control |
| Independent validation | Can you run security checks and tests that the agent cannot edit? | Documentation of where checks run and who can modify them |
| Build and CI/CD treatment | Are changes to build, workflow and deployment files isolated for review? | Your repository’s approval rules for those paths |
| Human review and release path | Is there any route to merge or deploy without a human? | Your repository’s branch protection and deployment approval settings |
Scaling the gates to risk
NIST says SSDF practices should be customized to business or mission needs, risk tolerance and available resources. Applied to agents, that means the gates should be strictest where a bad change would do the most damage. The following tiering is an editorial suggestion, not a published standard:
- Documentation and comment-only changes: Gates 3, 5 and 9 cover scope, boundary and approval.
- Application code and tests: all ten gates, with review depth matched to the size of the diff.
- Authentication, authorization, cryptography, payment, data handling, build and deployment changes: all ten gates, with independent security review and Gate 8 approval before anything runs.
If you can enforce only two gates this quarter, make them Gate 3 and Gate 9. Together they limit what the agent can touch and make a named person answerable for the result.
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