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Agentic AI platform

Platform

A mission-grade agentic AI surface for bug bounty hunters. Scope-locked. Validation-first. Submission-ready output.

Agentic hunt flow

01Import scopePaste HackerOne / Bugcrowd scope URL
02ReconAgent maps endpoints within locked boundaries
03ExploitTests IDOR, auth bypass, prompt injection…
04ValidateDeterministic curl replay — CONFIRMED only
05PoC reportSubmission-ready output for your platform
$81M+HackerOne payouts per year, growing 13% YoY (HackerOne 2025)
2M+Registered researchers on HackerOne alone
+116%IDOR report growth over 5 years on HackerOne (2025)
70-82%Bug bounty hunters already using AI tools (HackerOne/Bugcrowd 2025-26)

Not a scanner. Not a chat wrapper.

Generic vulnerability scanners fire hundreds of alerts without ranking, reproducing, or formatting them for submission. Chat wrappers wrap an LLM around your manual workflow without changing the underlying quality. Neither is built for a bug bounty hunter who needs confirmed, submission-ready findings.

RaSEC Hunt is an agentic AI system that reasons about your target like a senior hunter would: it understands scope boundaries, prioritizes high-signal bug classes (IDOR, auth bypass, access control), validates each finding deterministically, and assembles the evidence into a report you can actually submit.

The "agentic" part means the AI takes autonomous multi-step actions — not just answering prompts. It decides which endpoints to test, what vectors to try, how to reproduce a finding, and when to stop. You give it the scope. It does the work. You steer when needed.

Every agent action is logged, streamed, and reversible. You always know what it did, why, and what it found. There is no black box. There is no hidden "AI magic" behind a spinner. Full operator transparency is a core design constraint, not a dashboard feature.

Platform pillars

Every pillar is a runtime guarantee. Not a marketing claim.

01

Scope control

Boundaries enforced at the execution layer, not the UI layer

Every agent action is gated against an immutable scope policy before any network call. You define the in-scope hostnames and URL patterns once. The system enforces them throughout the entire hunt session with no operator-side override required. If the agent discovers a redirect that leaves scope, it stops, flags, and waits. There is no "oops" mode.

  • Wildcard and regex scope patterns supported
  • Scope violations flagged as first-class events in the activity log
  • Scope policy is version-locked per session — cannot be mutated mid-run
  • Out-of-scope targets are never contacted, logged, or counted as coverage
02

Mission execution

Live agentic hunting with full operator visibility

The agent streams its reasoning, tool calls, and intermediate findings in real time. Every step is surfaced in the Mission Control dashboard: what the agent is testing, which endpoints it is touching, and what lifecycle state each finding is in. You can pause, resume, or inject instructions mid-hunt without stopping the session. The glass-box model means you always know exactly what the AI did.

  • SSE-backed live activity stream with full event replay
  • Pause / resume / steer controls always accessible
  • Agent thinking exposed in real time (not hidden behind a spinner)
  • Multi-session support: run parallel hunts on separate targets
03

Validation lifecycle

Three-stage gate before a finding is called confirmed

Every potential finding goes through a mandatory validation pipeline: initial detection, deterministic reproduction attempt (up to 3 passes), and evidence assembly. Only findings that pass all three stages are promoted to "CONFIRMED" status. High-severity findings require a working curl command and a clean HTTP response diff. Nothing is hidden behind an "AI-confirmed" label without evidence.

  • Pending → Reproducing → Confirmed → Rejected states clearly tracked
  • Failed reproductions archived with explanation, not silently dropped
  • CVSS-level tags assigned only after confirmation
  • Evidence chain (request, response, diff) bundled with every finding
04

Submission output

Reports built for real disclosure programs, not demos

The final output is not a JSON blob or a raw log. It is a structured PoC report formatted for the platform you are submitting to: HackerOne, Bugcrowd, Intigriti, or custom templates. The report includes the vulnerability summary, CVSS score, step-by-step reproduction, a curl command, and the evidence diff. Copy. Paste. Submit. No cleanup needed.

  • Platform-native templates: HackerOne, Bugcrowd, custom markdown
  • Reproduction steps generated automatically from live agent trace
  • Curl command included and verified against the confirmed response
  • Reports exportable as markdown, PDF, or direct API push (Elite)

Agentic capabilities

A full agentic toolchain purpose-built for bug bounty hunting.

Recon engine

Crawls auth flows, API surfaces, and object references using scope-aware path expansion.

IDOR detection

Tests horizontal and vertical access control boundaries with ID substitution across user contexts.

Auth bypass testing

Tries token manipulation, session state confusion, and header injection patterns systematically.

Race condition probes

Available on Elite tier — detects time-of-check-time-of-use windows with parallel request bursts.

Prompt injection (AI apps)

Tests AI-powered endpoints for prompt injection, context leakage, and unsafe tool delegation.

Evidence baseline

Takes full HTTP baseline snapshots before and after each test to produce clean reproducible diffs.

From scope to submission in five steps

Paste scope

Enter your program's in-scope URLs or wildcard patterns. The agent will never leave these boundaries.

Select tier

Free for surface coverage. Pro for IDOR and auth bypass with PoC reports. Elite for overnight sessions and advanced capabilities.

Start the hunt

The agentic AI begins recon immediately. You watch the live activity stream as it works through your surface.

Review findings

Findings appear in the findings board by severity. You promote, reject, or request re-validation from the same surface.

Export and submit

Download your submission-ready PoC report formatted for your bounty platform. Copy. Paste. Submit.

What we commit to. What we do not.

We guarantee:

  • Scope is enforced before every network action
  • No finding is promoted without deterministic reproduction
  • Your hunt data is not used to train models
  • The agent activity log is complete and not filtered
  • Report output matches what the agent actually did

We do not guarantee:

  • 100% vulnerability coverage on any target surface
  • Acceptance by any specific bug bounty program
  • Results on targets behind strong anti-bot controls
  • Equivalent output on every network topology
Platform capabilities ship incrementally per milestone. Join the early access cohort to see the current production state and roadmap.
RaSEC Platform

Ready to run your first agentic hunt?

Scope-safe from the first run
Deterministic validation
PoC-ready output
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