Secure every app your organization is shipping.
Developers, business teams, and coding agents all create application attack surface. NightVision gives every workflow the same runtime security check.
The newest apps are the easiest to miss.
Coverage decays when new applications never enter the security program. NightVision gives human and AI builders a runtime check that shows what the application exposes and what behavior failed.
The deterministic evidence layer under AI velocity
New API routes added to the map
API eNVy emits an OpenAPI spec from supported source in under 20 seconds, deterministically: no LLM reads your code. Routes enter testing even when documentation lags behind. How API discovery works.
Tested at runtime, fully authenticated
Whole-app DAST drives a real browser with Playwright-recorded authentication, TOTP/MFA included. Request-level findings retain HTTP evidence; supported source-discovered API findings add file and line.
Agents fix and verify
The coding agent combines the evidence with repository context, proposes a change, and rescans before calling the issue fixed. Branch protections and human review still govern the merge.
Security that runs inside the agent's workflow
NightVision ships an open-source MCP server and Agent Skills, so the same agent that wrote the code can launch a scan, retrieve findings, propose a change, and rescan without leaving the workflow; the guided one-call whole-app scan is rolling out in early access. See how NightVision works with coding agents.
Dynamic testing on the finding, agents on the fix, humans on the merge. Runtime evidence gives the agent a concrete behavior to investigate; a verification scan gives reviewers proof the fix worked.
AI-generated code security questions
Why does AI-generated code need DAST?
AI tools generate endpoints and integrations faster than documentation or review keeps up. DAST tests the running application the way an attacker would: the check that does not depend on the code having been reviewed, documented, or written by a human.
Is NightVision an autonomous pentester?
No. NightVision gives coding agents structured tools to launch dynamic tests and retrieve observed evidence. The agent uses that evidence with repository context to propose a change and rescan; repository permissions and human review still govern what ships.
How do coding agents use NightVision?
Through NightVision's open-source MCP server and Agent Skills: launch a scan, monitor it, retrieve checks and runtime evidence, use file and line context on supported source-discovered API scans, propose a change, and run a verification scan. See NightVision for coding agents.
Does AI decide what counts as a vulnerability?
No. NightVision produces findings from dynamic tests against the running application. LLMs can assist with form handling, explanations, and remediation, but the agent is consuming observed runtime behavior rather than inventing a finding from a code pattern.
What happens after a finding?
The agent retrieves the finding evidence and, where supported, source location context, proposes a code or configuration change, verifies the behavior changed with another scan, and submits the change through the team's normal review process.
Put a deterministic evidence layer under your AI velocity.
Book a demo to see an agent-triggered scan end to end, or start free and scan the app your AI just built.