AI Pentesting & Autonomous Exploit Platform
Next-generation AI pentesting platform exploring Web, APIs, and business logic with zero downtime.
State-of-the-art AI pentesting that autonomously maps attack surfaces, reasons through multi-step logic flaws, and provides verified proof-of-concepts.
Traditional vulnerability scanners rely on brute-force signature matching, missing complex authentication bypasses, business logic abuse, and multi-step lateral attack chains. Modern application architectures require an intelligent AI pentesting system that understands context and reasons like an elite human red-teamer.
Supradim AI Pentesting combines autonomous reasoning agents with a specialized exploit synthesis engine. It actively crawls modern single-page apps and microservice APIs, formulates adversarial hypotheses, executes non-destructive zero-payload validation, and delivers evidence-backed reproduction proofs with virtually zero false positives.
| Target Asset | Status | Findings |
|---|---|---|
| api.example.com | Verified | 3 7 |
| staging.example.com | Verifying | 1 3 |
| auth-service | Verified | 2 5 |
| payments-api | Verified | 0 2 |
Core CLI Engine Open-Sourcing Soon · Register for Cloud SaaS Beta
We are preparing to open-source our core autonomous pentesting CLI engine. Meanwhile, our zero-ops hosted Cloud Multi-Agent SaaS platform is opening for early registration. Enter your work email below to secure priority access.
Key Capabilities & Deep Dive
Autonomous Multi-Hop Attack Path Reasoning
Our AI pentesting engine dynamically maps session hierarchies and microservice dependencies to reconstruct viable attack graphs.
- Deep business logic flaw exploration (BOLA, IDOR, privilege escalation, payment flow tampering)
- Context-aware multi-step session replay and autonomous parameter mutation
- Evidence-based verification ensuring zero false-positive alert fatigue
Full-Scope Web & API Pentesting Coverage
Seamlessly runs AI pentesting across modern SPAs, GraphQL APIs, RESTful microservices, and gRPC endpoints.
- Autonomous API schema inference from live traffic or OpenAPI/Swagger definitions
- Complex token manipulation: OAuth 2.0, JWT signature stripping, and mTLS handshake testing
- Non-destructive fuzzing customized for 100% production-grade uptime
Developer-Ready Proofs & Remediation
Transforms raw security scanner noise into clear, replayable developer patches and executive reports.
- Actionable curl reproduction commands and step-by-step HTTP proof-of-concepts
- Tailored framework-specific patch snippets (Node.js, Go, Java Spring, Python FastAPI)
- CVSS v4 risk scoring with direct mapping to OWASP Top 10 and compliance frameworks
How the System Works
Continuous Surface Discovery
The AI pentesting agent crawls subdomains, API gateways, and client bundles to map active assets and trust boundaries.
Dynamic Exploit Hypothesis Engine
The pentest AI constructs test hypotheses based on anomalous responses, session tokens, and business flow semantics.
Safe Proof-of-Concept Execution
Executes strictly bounded sandbox validations that prove vulnerability impact without risking data loss or system interruption.
Automated CI/CD Fix Verification
Integrates into engineering workflows to automatically re-test vulnerabilities after developers commit fixes.
Technical Specifications
AI Pentesting Protocol & Stack Coverage
Safety Governance & Compliance
Frequently Asked Questions
Q: What is AI pentesting and how does it work?
AI pentesting (artificial intelligence penetration testing) uses autonomous agents and LLMs to simulate the reasoning, creativity, and multi-step tactics of human white-hat hackers. Unlike legacy DAST scanners that blindly spray static payloads, AI pentesting understands business logic, adapts to application responses, and chains multiple mild flaws into verified critical findings.
Q: Will AI pentesting replace human penetration testers?
AI pentesting augments and empowers security teams by taking over repetitive, continuous assessments and baseline logic verification across thousands of APIs 24/7. It allows human security researchers to focus on bespoke architecture reviews while ensuring no basic or regression flaw goes unnoticed in production.
Q: Can AI pentesting run safely against live production environments?
Yes. Supradim AI Pentesting operates with strict safety bounds and non-destructive heuristics. It avoids database-destructive operations (such as drops or mass updates) and rate-limits requests to ensure zero disruption to live customer traffic.
AI Honeypot & Agent Deception System
An intelligent AI honeypot deploying high-fidelity synthetic decoys to intercept automated bots, reverse attack TTPs, and drain LLM tokens with 0% false positives.
003Security for AI & Agents
Secures LLM applications against prompt injections, tool privilege escalation, and sensitive data leakage.
002Intelligent Code Security Review
Tracks true data flows and cross-file call hierarchies to deliver validated fixes directly into Pull Requests.