Elite AI hackers aren’t born. They’re trained.
Elite AI hackers aren’t born. They’re trained.
Hadrian is an attack-surface platform with an on-demand pentest bolted on, run by a single AI Orchestrator with no independent validation, and limited to external web. Novee goes inside your applications, verifies what’s exploitable, and keeps testing as your code changes.
External attack-surface visibility tells you what’s exposed, but it stops well short of proving what an attacker could do with it.
EASM first, application testing bolted on.
On-demand, one test at a time.
A single orchestrator, lightly validated.
Priced per test.
Attack-surface visibility is a starting point. What security teams need next is proof of what’s exploitable inside the application, confirmed continuously as the code keeps changing.
Goes inside the application.
Coverage across web, API, mobile, and AI.
Proves what's exploitable.
A proprietary offensive AI stack.
Continuous and change-triggered.
A closed loop to a verified fix.
| Capability | Novee AI Pentesting | Hadrian |
|---|---|---|
| Coverage | Web apps, APIs, mobile apps, and AI agents/LLMs across your footprint, tested black box from a domain name. |
External web assets and EASM. No internal apps, mobile, or AI applications. |
| Application context and depth | Builds an Asset Intelligence Model before testing, mapping roles, workflows, APIs, and business logic, so it finds the IDOR, auth bypass, and chained exploits inside the app. Context compounds every cycle. |
EASM-first attack-surface mapping. No business logic testing, and no compounding application context. |
| Continuous, change-triggered testing | Runs on demand or automatically when code ships via CI/CD, with no scheduling or human intervention. Coverage deepens each cycle. |
On-demand, per-test only. No continuous or change-triggered workflow. |
| Offensive model and harness | Proprietary harness and proprietary offensive reasoning model, post-trained on real attacker tradecraft and orchestrated with leading frontier models selected per task (multi-model). |
No proprietary model described; capability likely relies on third-party models. |
| Validation architecture | Three independent agents (a finder, a validator, and a blind re-validator with no context from the first two) plus deterministic checks where possible. Every finding ships with a working exploit, replication steps, and a PoC script. |
A single AI Orchestrator with human review. No independent second agent, and findings without confirmed exploit proof. |
| Closed-loop remediation & retesting | Remediation tailored to your WAF, backend, and codebase, with automatic retesting to confirm the fix held and flag new risk the change introduced. |
No confirmed stack-specific remediation or automatic retesting. |
| Pricing | Predictable per-asset pricing. Depth and frequency don’t increase cost. |
Per-test pricing, starting at €3,000 per test. |
| Workflow & integrations | Native CI/CD plus GitHub and Jira. Connected to CI/CD, fixes drop to the code level, aligned to your codebase. |
Connects to tools like Jira, Slack, ServiceNow, and Microsoft Teams, but no CI/CD integration for change-triggered testing. |