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Do not change code because an AI-generated report sounds convincing. Treat it as an unverified security report: preserve it privately, confirm that the affected version and configuration apply, trace attacker-controlled input through the real code path, reproduce the behavior in an isolated environment, and document the security impact. Only then should you accept it for remediation, request missing evidence, or close it with a reason.
GitHub’s guidance describes a strong AI-assisted submission as one that has been verified, reproduced, and submitted with a working proof of concept. Keycloak’s security policy puts the obligation plainly: “Validate before submitting. You are responsible for verifying that the vulnerability is real and reproducible.”
Why an AI-generated finding is only a lead
AI systems can identify suspicious patterns, connect code fragments, and produce a plausible exploit narrative. They can also misunderstand a framework, overlook a permission check, assume a feature is enabled, or confuse unreachable code with an exposed path. Confidence, technical vocabulary, and a proof-of-concept script do not establish that a vulnerability exists.
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- Does the reported component, version, feature, and configuration actually exist in the deployment being assessed?
- Can an attacker control the alleged input and reach the claimed code path or endpoint?
- Does the observed behavior cross a security boundary rather than merely produce an error or an expected result?
- Can another maintainer reproduce the behavior and inspect the evidence independently?
A report can be useful even when it is ultimately a false positive. The report, reproduction attempts, and disposition should leave a durable record of the repository context that future triage can use.
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1. Preserve the report and define its scope
Capture the facts before investigating
Save the original report without editing away details. Record the reported product and component, affected version or commit, operating environment, configuration, feature flags, prerequisites, claimed attacker, entry point, and alleged security boundary. Also record when and where the report was received and who has access to it.
Separate the reporter’s assertions from facts you have confirmed. A short statement such as “remote code execution” is a claim, not an established impact. Preserve the prompt or model output only when your project’s policy permits it and when it helps explain how the finding was generated.
Keep unverified exploit details private
Handle the issue as a security report while it is being assessed. Do not paste exploit commands, sensitive logs, credentials, personal data, or a potentially working payload into a public issue tracker. Use the project’s private security contact, confidential intake form, or equivalent access-controlled channel. If no private path is published, restrict the investigation to the smallest trusted group and ask the project’s maintainers how they want the report transferred.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsNIST Special Publication 800-216, published May 24, 2023, recommends a defined process for receiving, assessing, managing, and communicating vulnerability reports. A defined process prevents an AI-generated claim from being treated as an ordinary bug ticket before its risk is understood.
Set an explicit investigation boundary
Write down what you will and will not test. For example, specify the product version, deployment mode, authentication state, feature flags, test data, and network isolation. This prevents an accidental change in environment from being mistaken for evidence that the report is valid.
2. Check whether the report applies
Confirm the affected version and feature
Check the exact release, commit, build options, and optional modules named in the report. Read the relevant configuration rather than assuming a default. A flaw in an old release may already be fixed; a flaw in an optional feature may not matter when that feature is disabled; and a code path present in source may be removed or replaced by a backport.
Record the version and configuration used for every test. If the report gives no version, ask for one before drawing a conclusion, then test the nearest supported versions only if that helps narrow the question.
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Trace the alleged input
Start at the claimed attacker-controlled input: an HTTP parameter, uploaded file, message, job definition, repository change, command-line argument, or other external value. Follow it through parsing, normalization, validation, authorization, sanitization, storage, and the final operation. Mark each transformation and note where control is lost or constrained.
Do not infer reachability from a matching variable name. An input may be hard-coded in the relevant deployment, replaced by a trusted service, constrained by a schema, or discarded before the sensitive operation.
Check triggers, permissions, and trust assumptions
Ask what must happen for the path to execute:
- Does a workflow, webhook, scheduled job, plugin, or feature flag have to be enabled?
- Can an unauthenticated user reach it, or is an account, role, approval, or prior action required?
- Are pull requests, forks, repositories, tenants, or projects treated as trusted or untrusted?
- Do permission scopes, sandboxing, network policy, or service identities limit the alleged action?
- Does a sanitizer, encoder, allowlist, parser, or type check alter the value before use?
- Are repository-specific checks or deployment rules missing from the report?
GitHub Security Lab’s analyses emphasize workflow triggers, permissions, sanitization, attacker control, and project-specific checks because those details often determine whether a theoretical path is exploitable.
3. Reproduce the behavior safely and independently
Build an isolated test environment
Use a disposable environment that matches the stated version and configuration. Remove production credentials, real customer data, and unnecessary network access. If the test involves a worker, workflow runner, plugin, or external service, isolate that component as well. Snapshot or reset the environment between attempts so a previous run cannot create the result.
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Follow the report’s steps exactly first
- Record the tested version, operating system or runtime, configuration, enabled features, and authentication state.
- Apply the report’s setup without making unrelated code or configuration changes.
- Execute each command, request, input, or workflow trigger in the stated order.
- Capture timestamps, requests, responses, exit status, logs, stack traces, and observable side effects.
- Compare the expected result in the report with the actual result.
- Repeat from a clean state and, where practical, have a second maintainer follow the steps independently.
Do not “repair” the path while trying to reproduce it. If the supplied proof of concept fails, identify the first divergence: a missing prerequisite, a different version, a blocked permission, a sanitized value, or an incorrect expected result.
Use a minimal reproduction
Reduce the case to the smallest input and configuration that still demonstrates the behavior. Remove unrelated services, data, and automation. A minimal reproducible example makes it easier to distinguish the alleged flaw from an environmental failure and lets another maintainer inspect the exact security boundary involved.
Keycloak’s policy asks reporters to provide a minimal reproducible example and clear evidence of exploitation. The same standard is useful for maintainers assessing an AI-generated claim: a small, repeatable case is stronger than a long transcript or an opaque generated script.
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State what the reproduction proves—and what it does not
A successful run may prove that a value reaches a function, that an exception occurs, or that a test account can perform an action. It does not automatically prove remote exploitation, cross-tenant access, privilege escalation, data disclosure, or code execution. Record the exact observation and its limits.
4. Establish the actual security impact
Identify the attacker and required capability
Describe the least-privileged actor who can perform the action: an unauthenticated visitor, ordinary user, project contributor, repository participant, tenant administrator, or another service. Include prerequisites such as knowing an identifier, submitting content for review, or waiting for a workflow to run.
Identify the affected asset and boundary
State what the actor can read, change, execute, or disrupt, and whose boundary is crossed. Examples of boundaries include one user’s data versus another user’s data, one tenant versus another, an untrusted workflow versus a runner host, or an application process versus the operating system. If the behavior stays within the actor’s existing authority, describe it as such instead of assigning a stronger impact.
Separate evidence from severity labels
Do not infer severity from the model’s wording, a CVSS-like number, or the presence of a proof-of-concept file. Base the assessment on demonstrated reachability, required privileges, affected assets, and repeatable impact. If evidence supports only a lower-confidence possibility, say that plainly and request the missing demonstration.
5. Choose a disposition and record the reason
Use the evidence—not the source of the report—to select the next step. GitHub’s private-report workflow documents three practical maintainer paths.
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| Accept for private remediation | The affected version and configuration apply, the attacker-controlled path is reachable, and a security impact is reproduced or otherwise independently demonstrated. | Test environment, reproduction steps, evidence, affected versions, impact, temporary mitigations, owners, and disclosure coordination. |
| Request information | The claim may be relevant, but a version, prerequisite, input, permission detail, reproduction step, or impact demonstration is missing. | The exact unanswered question, the evidence already checked, and a deadline or next review point. |
| Reject or close with reason | The path is unreachable, the feature is not enabled, a control blocks the action, the behavior is expected, the issue is already fixed, or no security boundary is crossed. | The tested context, decisive check, evidence, and a clear explanation of why it is not considered a security risk. |
Preserve the original report, artifacts, and rationale for every disposition. Repository-specific false-positive knowledge—such as a required permission, sanitizer, or deployment rule—can prevent repeated investigations of the same pattern.
6. Coordinate remediation and disclosure
Keep communication private while facts are unsettled
Use the project’s published security contact or private reporting mechanism. Limit circulation to people who need the information to reproduce, fix, or coordinate the issue. Do not publish a working exploit, affected endpoint, or sensitive evidence merely to show that triage is underway.
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Agree on timing and responsibilities
Once the issue is accepted, agree who owns the fix, what temporary mitigation is available, who validates the correction, and how the reporter and affected users will be informed. Coordinate the advisory and fix through the project’s established process. The timing should account for remediation readiness, downstream releases, and the sensitivity of the exploit details.
Re-test the fix
Run the minimal reproduction against the fixed build and verify that the relevant security boundary is restored. Also test nearby variants that exercise the same input and permission checks. Record the fixed version or commit and retain the evidence used to close the report.
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What a trustworthy report contains
Before changing code, check that the report supplies—or that your follow-up investigation establishes—each item below:
- One finding per report. Keycloak’s policy requires this separation, which keeps scope and remediation decisions clear.
- Product, component, affected version, configuration, feature flags, and prerequisites.
- The attacker-controlled input and the code path, workflow, or endpoint it reaches.
- Exact reproduction steps, expected behavior, observed behavior, and supporting commands, requests, logs, or screenshots.
- The attacker’s required permissions and a concrete description of the affected asset and crossed boundary.
- Permission checks, sanitizers, mitigations, trust assumptions, and repository-specific controls that were considered.
- Private contact and disclosure details, with no premature public exploit material.
- Disclosure of AI assistance when the project’s policy asks for it.
A concise report is easier to verify than a long model transcript. Keep only the generated material that helps an independent maintainer reproduce the claim; remove irrelevant speculation and duplicate output.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Common triage mistakes and their corrections
Changing code before proving reachability
Mistake: An AI identifies a dangerous-looking call, and a maintainer immediately adds a filter or rewrites the function.
Correction: Trace a real attacker-controlled value from entry point to operation first. If the value cannot reach the operation under the affected configuration, document that result instead of introducing an unneeded change.
Treating a failed proof of concept as a definitive rejection
Mistake: The script fails once, so the report is closed.
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Correction: Compare versions, feature flags, credentials, workflow triggers, and setup instructions. Ask for the missing prerequisite or a minimal example when the claim remains plausible.
Equating an exception with a vulnerability
Mistake: A stack trace or error message is labeled as data exposure or denial of service without showing who can trigger it and what is affected.
Correction: Demonstrate the attacker’s capability, repeatability, and effect on a protected asset. Record the boundary that is—or is not—crossed.
Publishing details while assessment is incomplete
Mistake: A public issue or chat message includes a payload before the project has a mitigation.
Correction: Move the discussion to the private security channel and coordinate disclosure timing with the maintainers.
Discarding false positives without a record
Mistake: The report is deleted after a quick dismissal.
Correction: Preserve the evidence and the precise reason. Future AI output or human reports may raise the same pattern, and repository-specific context can make the next decision faster and more accurate.
A compact triage record
Use a structured record so another maintainer can repeat the decision without relying on memory:
Report identifier and received date
Product, component, version, and commit
Environment and configuration
Claimed attacker and prerequisites
Entry point and attacker-controlled input
Code path, endpoint, workflow, or trigger
Permissions, sanitizers, feature flags, and mitigations
Reproduction commands or requests
Expected result
Observed result and captured evidence
Affected asset and crossed security boundary
Disposition and rationale
Owner, private contact, and disclosure plan
Fixed version or follow-up dateKeep the record access-controlled and retain only the sensitive material your policy requires. If the project requires AI-use disclosure, note which part of the finding was AI-assisted and which evidence a human independently verified.
How to make the final decision
Change code only after the report is applicable to a real supported context and the security impact is supported by repeatable evidence. If applicability is clear but evidence is incomplete, request the missing information while keeping the matter private. If a project-specific control prevents the alleged action or no protected boundary is crossed, close the report with the tested context and reason. In every case, preserve the evidence and disposition so the decision is auditable and useful for future triage.
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