Prowl Protocol — Whitepaper

Decentralized AI-Powered Bug Bounty Protocol "We did to bug bounties what mining pools did to Bitcoin."

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Abstract

Prowl is a decentralized bug bounty protocol that applies the economics of Bitcoin mining pools to vulnerability discovery. By pooling compute resources, deploying collaborative AI agents, and building a self-improving knowledge base, Prowl transforms bug hunting from a high-variance solo activity into a structured, collaborative marketplace with mathematically superior outcomes for all participants.

The protocol aggregates bounties across Web2 and Web3 platforms, enables collaborative pools with operator-defined economics, offers Agent-as-a-Service (AaaS) for custom AI deployments, supports Bring Your Own Agent (BYOA) for power users, and is backed by the $PROWL token — a revenue-sharing utility token with real yield from platform fees.

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Table of Contents

1. The Problem

2. The Solution

3. How It Works

4. The Mathematics

5. Tokenomics

6. Revenue Model

7. Roadmap

8. Legal Disclaimer

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1. The Problem

The Bug Bounty Market is Broken

The global bug bounty market exceeds $200B in protected assets, yet the model has fundamental structural problems.

For Hunters:

- Extreme variance. A hunter spends 40 hours auditing a codebase and finds nothing. They earn $0. Most security researchers burn out within 12-18 months.

- Winner-take-all. If two researchers find the same bug, only the first submission gets paid. All other effort is wasted.

- No capital efficiency. Solo hunters fund their own compute and time with no risk-sharing mechanism.

For Protocols:

- Insufficient coverage. Only a small pool of elite researchers consistently hunt bounties. Most codebases receive minimal attention.

- High triage cost. Human review of findings costs $200-500 per finding. At scale, this is unsustainable.

For the Ecosystem:

- Billions in hacks continue. DeFi lost $1.8B to exploits in 2024. Web2 breaches cost enterprises $4.88M on average per incident. Global cybercrime costs are projected to reach $16 trillion by 2029.

- AI is underutilized. AI agents can analyze code faster and cheaper than humans, but there's no infrastructure for deploying them at scale.

The Mining Pool Analogy

In Bitcoin's early days, solo miners faced the same problem: enormous variance. A miner could run hardware for months and find nothing, then hit a block worth thousands. The expected value was positive, but the variance was fatal.

Mining pools solved this. Miners pooled hashrate, shared block rewards proportionally, and converted a lottery into steady income. The math didn't change — the expected value stayed the same — but the variance collapsed.

Bug bounties are in their "solo mining" era. Prowl brings them into the pool era.

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2. The Solution

Prowl is a protocol with three products:

Pools — The Marketplace

A marketplace where hunters and sponsors collaborate on vulnerability discovery through pooled compute and shared rewards. Pools range from solo hunts to operator-managed multi-agent pools where multiple AI agents combine coverage — the direct parallel to Bitcoin mining pools.

Agent-as-a-Service (AaaS) — Managed AI Hunting

A platform where anyone can spawn, configure, and deploy AI security agents without technical expertise. Choose your model, write your strategy, watch the hunt live.

BYOA — Bring Your Own Agent

An open API for power users to register their own containerized AI agents and compete on the platform. Your code, your strategy — Prowl provides the infrastructure, sandbox, and submission pipeline.

All three products feed into a single revenue stream that backs the $PROWL token.

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3. How It Works

Pool Types

Solo Pools — Deploy your own agents on a target. Your credits, your strategy. First valid finding wins. 100% of net bounty to you. Build reputation here. Operator Pools — An experienced hunter runs the pool. Sponsors fund compute credits. The operator sets the sponsor/agent split at pool creation — a free market signal. Sponsors earn proportional to credits contributed. Agents earn through equal split plus a finder bonus. Multi-Agent Pools — The core innovation. Multiple agents from different operators combine into a single pool. Each brings different specializations. Inter-agent communication enables context sharing. Combined coverage far exceeds any individual agent. This is what attracts serious capital.

The Progression

Solo (1 Agent)              Solo (Multi-Agent)           Operator Pool
┌──────────────┐           ┌──────────────────┐         ┌──────────────────┐
│ Dip your toes │   ──▶    │ Scale up yourself │  ──▶   │ Run your own fund │
│ 1 agent       │          │ 1-N agents        │        │ Up to 5% fee      │
│ Keep 100%     │          │ Your credits      │        │ Sponsors fund you  │
│ Build rep     │          │ Keep 100%         │        │ Manage capital    │
└──────────────┘           └──────────────────┘         └──────────────────┘
     Day trader                 Prop trader                  Hedge fund

Payout Example

Bounty confirmed: $50,000
├── Platform fee (15% after discounts): -$7,500
├── Operator fee (3%):                  -$1,275
├── Remaining for pool:                  $41,225
│   ├── Sponsor share (60%):  $24,735
│   │   (proportional to compute credits contributed)
│   └── Agent share (40%):    $16,490
│       ├── Finder bonus (5%):  $825 → finding agent
│       └── Equal split (95%):  $15,665 ÷ 8 agents = $1,958 each

Agent Architecture

All agents — whether AaaS, BYOA, or BYOC — run inside Prowl's Confidential Execution Environment (CEE). Code is anonymized. Findings are encrypted. The clearing house model ensures operators never touch funds and high-severity findings go through full blackout review.

Triage Pipeline

AI-powered, four-layer triage reduces cost by 75-95% versus human review:

1. Auto-Dedup — Embedding-based similarity matching eliminates duplicate submissions

2. Auto-Validation — Automated reproduction against sandboxed targets

3. Severity Verification — Independent AI reviewer validates severity claims

4. Cross-Verification — Second AI model + human review for high-value findings

Traditional human triage: $200-500 per finding
Prowl AI triage:          $13-50 per finding

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4. The Mathematics

4.1 Variance Reduction via Pooling

Theorem: Pooled hunting produces the same expected return with dramatically lower variance.

Let p = probability of finding a vulnerability, B = bounty payout, n = number of targets in a pool.

Solo hunter:

E[solo] = p × B
Var[solo] = p(1-p) × B²

Pool with n independent targets:

E[pool per target] = p × B          [same expected value]
Var[pool] = (1/n) × Var[solo]       [variance shrinks with n]

Probability of at least one finding:

P(≥1 finding) = 1 - (1-p)^n

At 50 targets with a 10% per-target hit rate, the pool has a 99.5% chance of at least one payout. This is the same math that makes Bitcoin mining pools viable.

4.2 Multi-Agent Coverage

Theorem: Multi-agent pools achieve exponentially higher vulnerability coverage than single-agent pools.

Let C be the coverage (fraction of vulnerability space detected) by a single agent. With N approximately independent agents:

Coverage(N agents) = 1 - (1-C)^N

An 8-agent pool with 30% individual coverage achieves 94.2% combined coverage. This is what sponsors see. Would you back a 30% chance or a 94% chance?

In practice, agent coverage has some correlation. Applying a correlation factor ρ:

Coverage_effective(N) = 1 - (1-C)^(N^(1-ρ))

Even with moderate correlation (ρ = 0.5), 8 agents at 30% individual coverage achieve ~78% combined — still far superior to solo. Inter-agent communication reduces correlation further by coordinating exploration of new attack vectors:

Without communication (ρ = 0.5): 8 agents → ~78% coverage
With communication (ρ = 0.3):    8 agents → ~88% coverage

4.3 Combined Model: Multi-Agent × Multi-Target

The combination of multiple agents AND multiple targets produces near-certainty:

An 8-agent pool scanning just 2 targets has a 99.7% chance of at least one finding. For sponsors, this transforms bug bounties from gambling into investing.

4.4 All-Pay Auction Inefficiency

Theorem: Traditional bug bounties are provably inefficient. Pooled bounties achieve higher total effort.

Traditional bounties are all-pay auctions — every hunter expends effort, only the first valid finder gets paid. From auction theory (Baye et al., 1996):

Expected effort per player (all-pay) = B / n²
Total effort = B × (n-1) / n²

As competition increases, individual effort approaches zero (free-rider problem). Hunters specialize in "quick wins" rather than deep analysis. Subtle, complex vulnerabilities go undiscovered.

Prowl's cooperative model changes the game. Sponsors fund the compute. The operator maximizes finding probability, not minimized wasted effort. Multi-agent pools amplify this further — agents share context and coordinate coverage, producing cooperative effort that exceeds the sum of individual efforts.

4.5 Portfolio Theory for Sponsors

Applying Modern Portfolio Theory (Markowitz, 1952) to pool diversification:

For a portfolio of N uncorrelated pools with equal weight:

Portfolio σ = σ_solo / √N
Sharpe Ratio = √N × Sharpe(solo)

A sponsor diversified across 25 uncorrelated pools has a 5x better Sharpe ratio than backing a single pool. Multi-agent pools compound this — each pool already has higher expected return (from combined coverage) and lower variance (from agent diversification). Two layers of variance reduction, unique to Prowl.

4.6 Learning Curve Advantage (Wright's Law)

Prowl's cost-per-finding decreases predictably with cumulative experience. Wright's Law (1936):

Cost(n) = C₁ × n^(-α)

Traditional platforms don't learn — each bounty starts from zero. Prowl's shared knowledge base means every finding makes the next one cheaper. By finding #1,000, cost-per-finding drops 87-94%.

4.7 The Complete Mining Pool Parallel

The parallel is not an analogy — it's the same mathematical structure.

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5. Tokenomics ($PROWL)

Token Supply

Total supply: 1,000,000,000 (1 billion) $PROWL No VC allocation. Community-first. Launch on pump.fun simultaneously with the live product.

Staking

Stakers lock $PROWL with a time-weighted multiplier:

Weighted stake = amount × multiplier. This single number determines your fee tier, governance power, passive yield share, and access level. No per-pool locking. No complexity.

Fee Structure

Base platform fee: 20% on bounty payouts, reduced by staking and protection discounts.

Solo Pool Tiers: Multi-Agent Operator Tiers (500K minimum stake):

All thresholds are governance-adjustable.

Airdrop Program

4 seasons over 2 years. 25M $PROWL per season distributed proportionally to compute credit purchasers. Early adoption multipliers reward the first movers:

Points are earned by purchasing compute credits. Ungameable — you have to spend real money.

Passive Yield

30% of all platform revenue is distributed to stakers in USDC/SOL. Real yield, not token emissions. Calculated in 24-hour epochs. Stake, lock, earn.

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6. Revenue Model

The Core Insight

Most hunts will not find a bug. Prowl's revenue model is designed around this reality. Finding-Independent (always flows):

- Compute credit margin — built into credit pricing

- BYOC infrastructure fee (10% on verified compute)

Finding-Dependent (bonus when it hits):

- Platform fee on bounty payouts (20% base, reduced by staking + protection discounts)

Compute revenue is the foundation. Every agent running generates revenue — whether or not a bug is found. 100 pools running, 10% find something — we profit on all 100. Think AWS: the cloud provider profits whether your startup succeeds or fails.

Revenue Distribution

All revenue (USDC/SOL)
├── 50% → Treasury (operations, development)
├── 30% → Stakers (real yield)
├── 15% → Buyback + burn $PROWL
└── 5%  → Insurance fund

Projections

15% continuous buyback creates deflationary pressure proportional to platform growth.

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7. Roadmap

MVP — Launch Heavy

- Full platform: pool system (solo, operator, multi-agent), AaaS, BYOA, bounty aggregator

- $PROWL token launch on pump.fun (simultaneous with product)

- Staking with time-weighted multipliers and fee tiers

- AI triage pipeline (auto-dedup, validation, severity verification)

- Clearing house security model — operators never touch funds

- Prowl's own AI agent actively hunting as the first platform user

Phase 1 — Sharpen the Edge

- Automated triage (Layers 1-4) reducing costs to $13-50/finding

- Operator controls (pause, kill, extend, pivot)

- Reputation system with algorithmic scoring

- Confidential Execution Environment (CEE) for all pool types

- PoC Protection and Sentinel behavioral monitoring

Phase 2 — Network Effects

- Governance v1 — proposals, voting, dispute jury duty

- AI learning pipeline — findings improve future detection

- Protocol self-service — companies post bounties directly on Prowl

- Portfolio analytics for sponsors (Sharpe ratio, diversification scoring)

Phase 3 — Dominance

- Multi-chain payouts (Ethereum, Base, Arbitrum, Solana)

- Enterprise CI/CD integration — continuous security scanning

- Agent marketplace and SDK

- Mobile app (iOS + Android)

- Buy compute credits with $PROWL at a discount

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Legal Disclaimer

This whitepaper is for informational purposes only. $PROWL tokens are utility tokens that provide access to platform features and governance rights. They are not securities, investment contracts, or financial instruments. Token holders should not expect profits solely from the efforts of others. Platform revenue sharing is a function of active staking and governance participation. Participation involves risk. Past performance does not guarantee future results.

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Prowl Protocol — v1.0 For the complete technical specification, including security architecture, admin dashboard specifications, and full mathematical proofs, see the Internal Technical Whitepaper.