Proof, notdetection.
An autonomous AI agent validates findings with safe exploit proof-of-concepts, chains vulnerabilities into real attack paths, and eliminates false positives — before they reach your report.
Scanner-Level Validation
AI-Assisted Validation Tool Selection
Intelligent decision engine selects the optimal validation approach per finding type — SQL injection, XSS, SSTI, CORS, CRLF, subdomain takeover, command injection, JWT weaknesses, HTTP smuggling, and exposed services.
Exploitation Engine — 7 Vulnerability Classes
Safe exploitation of SQL injection, remote code execution, local file inclusion, authentication bypass, Redis exposure, XXE, and SSRF — producing structured exploit evidence with impact documentation.
Proven Exploit Marking
Successfully exploited findings are promoted to critical severity with full evidence chain: payload used, response received, data accessed, and remediation steps.
Deep SQL Injection Testing
Beyond scanner flags — dedicated deep testing on high-risk URLs with parameters to confirm SQL injection with controlled data extraction proof.
Deep XSS Validation
Dedicated cross-site scripting testing on high-risk URLs, confirming exploitability beyond scanner confidence levels.
Autonomous Agent Validation
Independent Reconnaissance
Autonomous AI agent performs its own port scanning, service fingerprinting, subdomain enumeration, HTTP probing, technology detection, and TLS assessment — not trusting scanner data.
Scanner Finding Reproduction
Agent independently attempts to reproduce every scanner finding. Cannot reproduce? Marked as false positive with detailed reasoning. Can reproduce? Confirmed with richer evidence.
Beyond-Scanner Discovery
Agent discovers what scanners missed: admin panels, exposed APIs, configuration files, database exposure, authentication mechanisms, authorization gaps, injection points, and file upload vulnerabilities.
Mandatory Self-Verification Checklist
Agent must validate completion of every phase: port scan, service fingerprinting, directory enumeration, scanner finding verification, new vulnerability discovery, auth testing, attack chaining, and evidence collection.
Watchdog & Session Recovery
Stalled agent sessions are detected and nudged with continuation prompts. Late collection mechanisms gather results even when agents exceed backend timeouts.
Safe Proof-of-Concept Exploits
SQL Injection PoC
Tests OR-based, UNION-based, and error-based injection across common parameters. Confirms via database response markers.
Local File Inclusion PoC
Tests path traversal, encoding bypass, and /proc/self/environ across file-accepting parameters. Confirms via system file markers.
Remote Code Execution PoC
Tests command injection payloads — semicolon, pipe, subshell — across command-accepting parameters. Confirms via OS response markers.
XXE Injection PoC
Tests XML External Entity payloads targeting file access and internal services on XML-accepting endpoints.
SSRF PoC
Tests cloud metadata endpoints (169.254.169.254) and internal addresses across URL-accepting parameters. Confirms via cloud instance markers.
Authentication Bypass PoC
Tests default credential sets and SQL injection-based auth bypass on login endpoints. Confirms via dashboard and session markers.
Attack Chain Exploitation
LFI-to-RCE Chain
Chains confirmed local file inclusion to remote code execution via log file poisoning — Apache, Nginx, and HTTPD access logs, /proc/self/environ.
SQLi-to-Auth-Bypass Chain
Chains confirmed SQL injection to authentication bypass on admin paths with injection-based credential payloads.
SQLi-to-Data-Extraction Chain
Chains confirmed SQL injection to database content extraction — table names, usernames, password hashes, and file reads.
SSRF-to-Internal-Services Chain
Chains confirmed SSRF to access internal services — Redis, Elasticsearch, application servers, monitoring dashboards, and object storage.
Redis-to-RCE Chain
Chains exposed Redis service to remote code execution via protocol injection.
Intelligent Verification & Normalization
Confidence-Threshold Verification
Three-tier verification: high confidence → confirmed. Medium → needs retest. Low → false positive. Findings promoted or demoted based on verification results.
AI Attack Plan Generation
Creates prioritized attack plans: proven findings get verified, chainable findings get chain-exploited, candidates get attempted, low-confidence findings get tested.
False Positive Pre-Filtering
Detects tech-stack mismatches — WordPress paths on non-WordPress targets, PHP paths on non-PHP targets, common fuzzing artifacts — before findings reach your report.
Severity Downgrade for Unvalidated
Unvalidated findings get severity downgraded — critical to high, high to medium, medium to low. Only confirmed findings keep original severity.
Severity Normalization
Maps 30+ severity variants to canonical levels — handles numeric scores, CVSS ranges, mixed-case labels, and vendor-specific naming conventions.
Secret Scanning & Redaction
Reports scanned for accidentally exposed API keys, tokens, passwords, JWTs, private keys, and database connection strings — automatically redacted before delivery.
Report Quality Assurance
Schema Validation
Every canonical report validated against strict schema: required keys, valid severity levels, CVSS score ranges, proper finding structure, and complete metadata.
Consistency Validation
Cross-references checked: no duplicate IDs, attack paths reference real findings, remediation matrix references real findings, confirmed findings have evidence, critical findings have remediation.
Multi-Path Report Generation with Fallback
Three generation paths: agent canonical report (preferred), LLM-generated report (fallback), deterministic minimal report (guaranteed). A report is always produced.
Type Coercion & Recovery
Malformed reports are automatically repaired: type mismatches coerced, missing fields filled, LLM output errors recovered — ensuring output integrity.
LLM Report Agent with Validation Loop
LLM-generated reports validated against schema and consistency validators. Invalid output triggers repair prompts and re-generation — up to 3 retries.
Deduplication by Root Cause
Groups findings by extracted root cause — CVE, CWE, vulnerability type. Merges duplicates keeping strongest evidence and highest severity.