AI VAPT
AI VAPT that proves what's exploitable — then ships the fix.
PandaONE combines vulnerability assessment with AI-driven penetration testing. Agents map your attack surface, validate findings with safe exploits, and open remediation pull requests — so you get VAPT depth without scanner noise.
Hours
Avg. time to first findings
Exploit-validated
False positive approach
Web · API · Repo
Surfaces covered
Auto-fix PRs
Remediation
• Definition
What makes it AI VAPT?
Traditional VAPT runs a point-in-time scan and hands you a PDF. AI VAPT uses machine intelligence to continuously assess your apps, simulate attacker behavior, and explain why each exposure matters in your environment. PandaONE's AI VAPT layer reads evidence, chains attack steps, and only reports findings it can reproduce — turning hundreds of theoretical alerts into a short, ranked list of real risk.
Exploit-validated findings
Every critical and high finding is confirmed with a safe, non-destructive proof-of-concept. No alert dumps — only reproducible risk.
Attack-path prioritization
AI agents chain authentication bypasses, IDOR, injection, and SSRF into realistic attack paths — ranked by business impact.
Continuous, not annual
Run AI VAPT on every release via GitHub Actions or the dashboard. Catch regressions before production, not at the next audit.
Fixes in your workflow
PandaONE generates stack-specific remediation and opens a pull request — the path from VAPT finding to merged fix is one review.
Traditional VAPT vs AI VAPT
Same compliance intent. Faster cycles. Proof-backed results.
| Capability | Traditional VAPT | PandaONE AI VAPT |
|---|---|---|
| Time to report | 4–8 weeks | Hours |
| Finding validation | Manual spot-check | Automated exploit PoC |
| Retest after fixes | Extra engagement fee | Included in Business VAPT |
| Continuous monitoring | ||
| Remediation guidance | Generic templates | Stack-specific fix PRs |
| False positive rate | 30–60% unvalidated | Exploit-gated reporting |
How PandaONE AI VAPT works
Connect your target
Point at a URL, API, or GitHub repo. Scope is defined before any testing begins.
Agents assess & attack
Specialized AI agents enumerate surfaces, run OWASP-aligned test cases, and chain steps like a real attacker.
Validate & prioritize
Each finding is re-tested. Unsupported claims are dropped. Results are scored by exploitability and reachability.
Report & remediate
Technical findings, executive summary, and fix PRs land in your dashboard and repo — ready for audit or merge.
• FAQ
Frequently asked questions
See PandaONE on your own app.
First findings in hours. No setup required.