Find-to-Fix

AI-assisted vulnerability remediation. From runtime evidence to verified fix.

Anyone's agent can fix a finding; the scanner underneath is what matters. NightVision feeds the fix loop runtime evidence, and your team reviews every merge.

A NightVision finding presented as a work order with runtime evidence and a source line, connected to an agent-opened fix PR with a passing rescan, awaiting human review
The Evidence Chain

Findings arrive as work orders, not alerts

1

Dynamic finding, runtime evidence

The running application is tested; the request, response, payload, and observed behavior are captured for reproduction.

2

Code Traceback to file and line

On supported API scans backed by source discovery, findings can include the file and line that defined the endpoint, not only a URL.

3

SARIF into GitHub Security Alerts

Findings land in the repository and pull request workflow developers already live in. Jira, Slack, and Teams routing included.

4

Explain and reproduce

Explain with AI adds plain-language context; Validate with Curl replays the relevant request.

Agents on the Fix

The scan, fix, and rescan loop for coding agents

The open-source NightVision MCP server and Agent Skills put testing inside the coding session: the agent starts a scan, inspects the evidence, locates the responsible code, proposes a change, and runs NightVision again to verify the finding is gone.

Agent on the Fix

Evidence becomes a code change

Request-level findings lead the agent from the endpoint and vulnerable parameter to the actual sink; response and configuration findings point to the relevant security configuration.

Rescan Before Review

Verify the behavior changed

The agent reruns the same DAST workflow and confirms the finding no longer appears; the change and scan evidence then enter your normal pull request and review process.

A coding agent session with NightVision MCP tools: scan launched, evidence inspected, fix proposed, rescan verified
Determinism on the finding, agents on the fix, humans on the merge.
Why the Human Gate

The review gate is the feature, not the limitation

Agents get a controlled security workflow, not authority over production. Your repository controls decide what is committed or merged, and accountability stays with the team that owns the application.

FAQ

Remediation questions, answered.

Can coding agents remediate NightVision findings?

Yes. Through the NightVision MCP server and Agent Skills, a coding agent can launch a scan, inspect the evidence, follow source context where available, propose a code change, and rescan to verify the behavior changed. Your repository's normal review and merge controls still apply.

Does every finding include a source file and line?

No. Code Traceback is available for API findings when the scan uses a source-discovered OpenAPI specification. Other web, response, and configuration findings still include runtime evidence and remediation context, but the fix may live in framework or security configuration rather than the reported endpoint.

How does NightVision know the exact file and line?

Code Traceback works on API scans backed by source discovery: NightVision reads your source to map endpoints before it scans, so when the running application returns a vulnerable response on one of those endpoints, the finding resolves to a precise file and line rather than just a URL.

How do findings reach developers?

NightVision exports findings as SARIF into GitHub Security Alerts, so they appear in the repository where the code lives, alongside the pull request workflow developers already use. Findings can also flow to Jira, Slack, and Microsoft Teams.

Does NightVision bypass repository review controls?

No. The MCP server supplies scan tools and evidence to the coding agent. Repository permissions, branch protections, and review policy control what the agent may change or merge. NightVision's recommended workflow keeps a human on the merge.

Turn runtime evidence into a verified fix.

See the full loop on your own application: scan the running app, follow the evidence into the code, propose a change, and rescan before review.