Elite AI hackers aren’t born. They’re trained.
Elite AI hackers aren’t born. They’re trained.
Bright Security embeds DAST in the developer workflow, built for developers configuring tests, not security teams running offensive programs. Novee starts from a domain and tests autonomously, the way an attacker would.
Scanning in the developer workflow is useful, but developer-configured testing optimizes for convenience, not the coverage attackers exploit.
Developer-first is the ceiling.
Automated, but developer-configured.
No compounding context between scans.
No proprietary offensive model.
No mobile coverage.
Real coverage isn’t what a developer thinks to configure, it’s what an attacker would actually reach, proven, chained, and tied to a verified fix.
Autonomous from a domain name.
Tests what attackers target, not what devs configure.
Depth through chained attack paths.
A living model of your app.
Predictable per-asset pricing.
A proprietary offensive model.
| Capability | Novee AI Pentesting | Bright Security |
|---|---|---|
| Autonomous execution | Fully autonomous from a domain name, reasoning and chaining exploits on its own, with no developer setup or maintenance. |
Automated but developer-configured. Developers set up and maintain test suites, so testing runs only where they point it. |
| Testing depth | Tests the full attack surface an attacker would target, not what’s configured. |
Developers configure the scan, so coverage reflects what they thought to test, not attacker behavior. |
| Validation architecture | Three independent agents, including a blind re-validator, prove each finding, then chain vulnerabilities across your business logic into real attack paths, with deterministic checks where execution can confirm exploitability. |
Validates exploitability one finding at a time, but with no independent blind re-validation and no chaining across business logic. |
| Compounding application context | Builds an Asset Intelligence Model of roles, workflows, APIs, and business logic that deepens every cycle, so coverage compounds and testing gets more targeted instead of resetting each scan. |
Each scan runs independently, starts fresh, so context never compounds across runs. |
| Offensive AI stack | Proprietary offensive reasoning model post-trained on real attacker tradecraft and orchestrated with best-in-class frontier models selected per task, getting sharper with every recurring cycle. |
Runs on third-party AI; no proprietary model. |
| Coverage | Web apps, APIs, mobile apps, and AI agents/LLMs, the full application-layer surface, with mobile always included. |
Web, API, and AI apps, but no mobile coverage at all. |
| Continuous, change-triggered testing | Runs on demand or automatically when code ships via CI/CD, continuous coverage with no human intervention. |
Embedded directly in CI/CD, running continuously within the pipeline. |
| Workflow and CI/CD Integration | Native CI/CD and change-triggered workflows, plus Jira and GitHub, with fixes that drop straight down to the code level. |
Strong CI/CD and developer-workflow integration, its core design and a genuine strength. |