Autonomous Pentest AI
Red Teaming Supercharged.
XBOW Bench (XBEN)
93.27%
Overall Pass Rate
HackTheBox CTF
#1
Ranked among all SEA Teams
As an end-to-end AI red teaming solution, PAIStrike automates offensive security workflows with AI agents that map attack surface area, test exploit paths, and produce evidence-backed results.
Summary
RUNNING
Start time
2026-03-31 08:42
Duration
5h 14m
Project
Acme Banking Surfaces
Asset
Public API Gateway
Asset type
api
Target
api.acme-bank.io
Critical
2
High
5
Medium
11
Low
6
ATTACK SURFACE
GET /mvno-gateway/mock/enterprise/sendEmailCode?email={enc_test_mail}&operType={enc_signup}&basicOrgId={enc_org_1001}&language={enc_en}
GET /mvno-gateway/mock/enterprise/confirm?authCode={enc_auth_6d12}&language={enc_en}
GET /mvno-gateway/mock/enterprise/checkUserEmail?email={enc_test_mail}
GET /mvno-gateway/mock/enterprise/getEnterpriseProduct
GET /mvno-gateway/mock/cms/singpassConfig
OBJECTIVE
- Determine if `sendEmailCode` can be spammed at scale (rate-limit bypass, repeated traceCode issuance)
- Test whether `checkUserEmail` enables deterministic email existence enumeration
- Confirm whether any enterprise/cms endpoint discloses sensitive config beyond current findings
- Re-verify `confirm` endpoint stack trace leakage with a minimal PoC
$ CONSTRAINTS
Read-only, no destructive updates. Use disposable test addresses only. No real user mailbox targeting.
RSAC 2026 Perspective
“You are going to be red-teamed whether you pay for it or not, the only difference is, you know who gets the results delivered to them.”
Rob Joyce, U.S. Homeland Security Advisor and NSA Cyber leader, RSAC 2026
Proactive Offensive Security turns unknown exposure into prioritized action. Instead of waiting for a real breach to reveal weak controls, security teams can continuously validate exploit paths, measure detection readiness, and deliver remediation evidence to engineering and leadership first.
Pilot User and Evaluation Partners
One-Click, Fully Automated Red Team Workflow. From reconnaissance to reporting, with AI that plans, validates, and documents every step.
Attack Surface Discovery
PAIStrike begins by discovering assets, services, and exposed interfaces, modeling the attack surface the same way a real attacker would during reconnaissance.
Vulnerability Reasoning
Instead of blindly reporting findings, PAIStrike reasons about vulnerabilities using contextual information, attack preconditions, and research-driven heuristics.
Automated Exploitation
PAIStrike attempts real exploitation to validate whether vulnerabilities are actually exploitable, retrying and adjusting strategies when needed.
Evidence & Report
Every successful exploitation is recorded with reproducible evidence, attack steps, and structured reports that support review, auditing, and remediation.
Top-Tier Performance
From common web flaws to complex attack chains, consistently validated.
XBEN Benchmark
104 Official Scenarios
Evaluation Engine
Scenario execution and verdict pipeline
Performance by Attack Complexity
Level 1 — Common Web Vulnerabilities
95.56%
Level 2 — Multi-step Attack Chains
90.20%
Level 3 — Stateful Attacks
100%
Vulnerability Coverage
Full coverage
Tags
Pass Rate
IDOR
10
93.33%
Privilege Escalation
10
92.86%
Command Injection
10
90.91%
Blind SQLi
6
66.67%
JWT
6
66.67%
XXE
6
66.67%
Arbitrary File Upload
5
50.00%
Overall Pass Rate
Built for measurable outcomes. PAIStrike is benchmarked against official, multi-category security scenarios to validate real exploitability at scale. Strong pass rates demonstrate consistent agent reasoning, reliable execution quality, and repeatable security outcomes that teams can trust in production workflows.
Built by Scantist. Grounded in Academic Research. PAIStrike is part of Scantist’s security platform, combining product-grade engineering with years of cybersecurity research from leading Singapore university labs. This foundation enables practical, reproducible red teaming outcomes for modern organizations.
Scantist AI Security Solutions
PAIStrike / AppDenfender / AI Defender
A focused portfolio for offensive validation, application protection, and AI security hardening under one security organization.
Learn more on Scantist.comResearch Leadership
Scantist’s direction is informed by deep academic cybersecurity research in Singapore, including leadership from Professor Liu Yang.
In today's rapidly evolving digital landscape, effectively translating cutting-edge cybersecurity research into actionable, measurable enterprise security outcomes has become the critical bridge between academic innovation and industry practice.
Professor Liu Yang
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