hackerone

hackerone is a skill for Claude Code, Codex from Unclecheng-li/DeepSec. It costs 43 tokens per session (1,624 once invoked), scanned A, a copy of hackerone, MIT.

A HackerOne bug-bounty safety procedure that reads a program's scope and rules before testing any target. HackerOne is a platform where companies invite security researchers to report vulnerabilities for possible rewards.

In plain words
What is it for?
Use it when starting a HackerOne security test to identify in-scope and out-of-scope assets and pass only permitted targets to the testing workflow.
Why use it?
It prevents testing assets that the program excludes, which could violate its rules or create legal and eligibility problems. If the scope page cannot be read automatically, it asks for the scope to be provided.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when starting a HackerOne security test to identify in-scope and out-of-scope assets and pass only permitted targets to the testing workflow.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/unclecheng-li/deepsec/hackerone
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Unclecheng-li/DeepSec --skill hackerone
Clone the repo
git clone --depth 1 https://github.com/Unclecheng-li/DeepSec

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for hackerone

README.md
[![agentmods](https://agentmods.dev/badge/skills/unclecheng-li/deepsec/hackerone/github.svg)](https://agentmods.dev/skills/unclecheng-li/deepsec/hackerone)
Your own site
<a href="https://agentmods.dev/skills/unclecheng-li/deepsec/hackerone"><img src="https://agentmods.dev/badge/skills/unclecheng-li/deepsec/hackerone/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for hackerone

Your own site · 80×15
<a href="https://agentmods.dev/skills/unclecheng-li/deepsec/hackerone"><img src="https://agentmods.dev/badge/skills/unclecheng-li/deepsec/hackerone.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,624 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00043 $0.01624
Opus 5.5 $0.00017 $0.00650
Sonnet 5.5 $0.00009 $0.00325
Haiku 4.5 $0.00004 $0.00162

Measured 1mo ago against content hash 6d89f7bb4313, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

hackerone scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to hackerone — 191 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

deepsec/spear/skills/specialized/hackerone/SKILL.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

HackerOne 赏金 scope-guard Skill

你当前正在执行 HackerOne bug bounty 流程。本 Skill 是一层 scope-guard wrapper: 先解析并强制 program scope 与 program rules,再把每个 in-scope asset 交给 pentest-flow Skill 执行真正的渗透。严禁在任何阶段触碰 out-of-scope asset。

启动参数是一个 HackerOne program 链接(<SCOPE LINK>),例如 hackerone.com/<handle> 或 .../policy_scopes。本 Skill 无预设 target (frontmatter requires_target: false)——target 从 scope 中发现。

阶段一:读取 scope(Read scope)

  1. 优先 fetch 链接

    • 用 fetch 工具访问传入的 <SCOPE LINK>。
    • HackerOne 是 JavaScript SPA:hackerone.com/* 的 fetch 通常只返回 空 app shell,没有渲染出的 scope 行(scope 数据来自 hackerone.com/graphql 或 authenticated api.hackerone.com,naive fetch 拿不到)。
    • 检测空壳:若响应中没有可识别的 scope 表格 / asset 列表(只有 <div id="app"> 之类的骨架),判定为 fetch 失败。
  2. fallback:请用户粘贴 scope

    • fetch 为空 / 被 login-wall / 仅 JS 渲染时,这是常态而非例外。

    • 请用户从 program 页面的 Scope 标签把 in-scope 与 out-of-scope 两张表 直接粘贴过来。给出一个可参照的粘贴格式示例:

      In scope:
      https://api.example.com        | URL       | Eligible for bounty
      *.example.com                  | WILDCARD  | Eligible for bounty
      app.example.com                | URL       | In scope, NOT bounty-eligible
      com.example.android            | GOOGLE_PLAY_APP_ID | Eligible for bounty
      
      Out of scope:
      blog.example.com               | URL
      *.corp.example.com             | WILDCARD
      
  3. 宽松解析(lenient parse)

    • 从粘贴或 fetch 结果中提取两个列表:in-scope 与 out-of-scope。
    • 识别 asset type(human label 或 API enum 均可): URL、WILDCARD(*.x.com)、CIDR/IP、SOURCE_CODE、 GOOGLE_PLAY_APP_ID/APPLE_STORE_APP_ID/TESTFLIGHT/OTHER_APK/OTHER_IPA、 HARDWARE、AI_MODEL、SMART_CONTRACT、OTHER 等。
    • 识别 eligibility 三态(submission 与 bounty 是两个独立布尔):
      • submission=true, bounty=true → in scope,可测,有赏金。
      • submission=true, bounty=false → in scope,可测,无赏金(勿与 out-of-scope 混淆)。
      • submission=false → out of scope,绝不测试。
    • 解析不确定时,向用户确认,绝不把 asset 默认当作 in-scope。

Read the full file on GitHub · 113 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 113 lines · 43 tokens per session scan A 6d89f7bb4313

Subscribe to this mod's changes

hackerone is a skill published in the GitHub repository Unclecheng-li/DeepSec (493 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 1,624 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to hackerone, differing in 191 lines, and is treated as a copy.

Related

Other skills, from other repositories

exploit-reporting

Exploitation finding documentation — initial access reports, exploit chain documentation, CVSS v4.0 scoring, shell/credential inventory, detection gap analysis.

PurpleAILAB/Decepticon · 35 tokens

ti-ioc-extraction

Automated IOC extraction from threat reports, logs, and unstructured text — parse hashes, IPs, domains, URLs, email addresses, and CVEs. Covers regex-based extraction, defanging/refanging, bulk hash lookup, IOC deduplication, YARA rule generation from IOCs, and STIX/TAXII formatting for sharing.

PurpleAILAB/Decepticon · 75 tokens

ti-yara-hunting

YARA rule writing from behavioral observations and TI report analysis — sample-to-rule conversion, condition optimization, performance tuning, and retrohunting on VirusTotal and ANY.RUN. Covers YARA/YARA-X syntax, yarGen automated generation, and production rule deployment.

PurpleAILAB/Decepticon · 58 tokens

m365-mailbox-compromise

Microsoft 365 mailbox compromise chain — OAuth consent phishing, delegate access abuse, mail rule persistence, and token theft via device code phishing. Full kill chain from initial access to persistent email collection.

PurpleAILAB/Decepticon · 45 tokens

web

Web application exploitation — the primary category skill for all web-based attacks. This is a routing skill: read this first to identify the attack type, then load the appropriate specialized sub-skill for detailed procedures. Covers 11 technique areas across injection, file access, authentication, and API…

PurpleAILAB/Decepticon · 60 tokens

opsec

Operational security management — traffic shaping, scan rate limiting, source IP management, tool signature avoidance, evidence handling, anti-detection patterns.

PurpleAILAB/Decepticon · 30 tokens