Individual skill

pre-bounty

Map a bug-bounty scope and rank targets by payout, crowding, and freshness. Use to size up a program or decide where to hunt before committing time.

skills/hunter-utils/pre-bounty/SKILL.md

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Last checked: Nov 5, 2026

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Repository stars (not skill ratings): 153
Repository last updated: Nov 7, 2026
License: MIT

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ai-security Repository topic
ai-skills Repository topic
security-skills Repository topic
dynamic-workflow Repository topic
engineering Derived category

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SKILL.mdcore · 8,471 bytes
SKILL.mdcore · 8,471 bytes
references/sankey.mddoc · 9,174 bytes
references/scoring.mddoc · 4,014 bytes
references/sourcing.mddoc · 3,632 bytes

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# Pre-bounty: scope recon & target prioritization

## The core thesis

Most hunters converge on whatever is cheapest to start testing. That means the
crowd is an artifact of the **setup barrier**, not of where the bugs are. So the
edge is systematic: rank the scope by

> **opportunity ≈ (payout ceiling × freshness) ÷ crowd**, with **setup difficulty
> acting as a moat** - a hard-to-reproduce environment keeps competitors out, so
> it is a *positive* when paired with a high ceiling.

The whole skill exists to compute that ranking from real program data and show it
in a way the user can act on. A high max-payout asset that is trivial to set up