Not just detection — judge and fix the moment AI writes each line of code
The AI engine understands business logic, data flows, and permission boundaries — moving code security from after-the-fact scanning to real time, and replacing legacy SAST.
The legacy paradigm of static analysis was built on rule matching; in an age when AI produces code 10× faster, it is bound to fail
An AI-native engine that re-architects code security, collapsing detection, judgment, and repair into one developer turn.
Deep data-flow and control-flow analysis tracks sensitive data, permission boundaries, and auth bypass to pinpoint truly exploitable vulnerabilities.
Beyond pattern matching — contextual understanding of business semantics cuts noise so engineers focus on real risk, not alert triage.
One-click jump from web into the IDE; an AI agent proposes a fix, a human confirms, and a rescan closes the loop — no more 'found it, now what?'.
Purpose-built rules for the high-frequency flaws of AI-generated code: insecure defaults, missing validation, hardcoded credentials.
Extends coverage into Agent scenarios, detecting new supply-chain and prompt-injection risks in MCP tool integrations and AI Skills.
PR/MR-level incremental scans finish in seconds without blocking; configurable gates block high-risk merges, compatible with mainstream quality-gate systems.
Deep data-flow and control-flow analysis traces sensitive data, permission boundaries, and authentication bypasses to pinpoint vulnerabilities that are actually exploitable.
Tracks untrusted input from source to a dangerous sink along the data flow.
Uses branch conditions and auth boundaries to drop unreachable / sanitized paths.
Reports only triggerable vulns — fewer false positives, fix high-risk first.
No deferring to review: detection, repair, and regression verification all happen within the same turn the developer writes code — a continuous closed loop.
Risks surfaced as you type, not at pipeline time.
Delivers applicable patches, not just alerts.
Re-scans after the fix to confirm nothing new broke.
Security judgment and repair happen in lockstep with AI coding.
Human- or AI-written code; scanning triggers on write and on commit.
The AI engine understands business logic and data flow, locating real exploitable risk and explaining the cause.
In-IDE AI proposes a patch; the developer confirms; fixes land now, not in backlog.
A rescan verifies the fix, visualized, ensuring the issue is truly closed.
Book a demo and see how CleanCode Security Agent protects code in real time inside your pipeline.
