Autonomous security research.
Point Lunadra AI at an authorized target. It hunts for real, exploitable vulnerabilities, validates every finding, and returns a submission-ready evidence package.
Most security testing buries the signal.
Automated scanners produce noise. Manual hunting does not scale. The result is a pile of low-confidence findings, weeks of triage, and real vulnerabilities that slip through.
- 01
Scanners produce noise
Generic tools flag hundreds of potential issues. Most are low-severity or false positives that drain triage time and erode confidence in the output.
- 02
Manual hunting does not scale
Skilled researchers are scarce and expensive. Continuous coverage across a large attack surface is not realistic with human-only capacity.
- 03
Unverified findings cost trust
Submitting findings nobody confirmed to a bug bounty program or a client damages credibility. Teams need high-confidence output, not a list to sort through.
Hunt. Validate. Report.
Autonomous hunting
Lunadra AI maps the attack surface and hunts for vulnerabilities continuously, without manual direction for each test case.
High-confidence findings
Every finding is validated before it surfaces. Each reported vulnerability is real and reproducible.
Submission-ready evidence
Output is a complete package: PoC, reproduction steps, CVSS score, impact analysis, remediation guidance, and a PDF report.
What you get with every finding.
Lunadra AI does not hand you a raw flag. Each confirmed finding ships as a complete package, ready for immediate action.
- 01
Executable Python PoC
A self-contained proof-of-concept script you can run immediately to reproduce the vulnerability in scope.
- 02
Step-by-step reproduction
Numbered steps a developer or security reviewer can follow to confirm the issue without guesswork.
- 03
CVSS score
A scored severity rating calculated against the Common Vulnerability Scoring System, ready for any report.
- 04
Impact analysis
Plain-English business risk: what an attacker gains, which assets are affected, and how far they could reach.
- 05
Remediation guidance
Concrete, developer-facing fix recommendations that address the root cause, not just the symptom.
- 06
Exportable PDF report
A print-ready report covering all findings, suitable for internal review, client delivery, or disclosure submission.
How Lunadra AI works.
Recon
Lunadra AI ingests your authorized target scope and maps the attack surface: endpoints, services, authentication surfaces, and application logic boundaries.
Deep hunt
It probes for real vulnerabilities across authentication, access control, business logic, injection, and more. Findings are validated before they are surfaced.
Evidence pack
Confirmed findings are packaged into a complete bundle: PoC, reproduction steps, CVSS score, impact analysis, remediation guidance, and a PDF report.
Confirmation before alert.
Every finding is confirmed before it reaches you. The result is a concise, high-confidence report you can act on, not a backlog to sort through.
- 01
Cross-service business logic
Lunadra AI follows how your application flows across services, not just individual endpoints. It finds logic-layer vulnerabilities that surface-level scanners routinely miss.
- 02
Adapts to defensive controls
When Lunadra AI meets a WAF or other defense, it pursues findings through alternative paths rather than stopping at the first obstacle.
- 03
Deduplicated and chained findings
Related issues are grouped and chained. You see the full impact of a vulnerability chain, not a fragmented list of individual observations.
Monitor findings in real time.
Start a scan, track progress, and review validated findings from a single web dashboard.
Authentication bypass via JWT none algorithm
IDOR on order ownership: cross-account data access
Reflected XSS in search parameter
Common questions.
Ready to find what really matters?
Join the Lunadra AI design-partner program. We work with a small number of engineering-first security teams to validate findings and shape the product.