credential-attack

credential-attack is a skill for Claude Code from Awarexone/Agentic-Bug-Hunter. It costs 102 tokens per session (4,931 once invoked), scanned A, original, MIT.

A controlled password-spraying workflow for authorized bug-bounty testing, using company-specific terms and login methods such as web forms, OAuth, Microsoft 365, or Okta. Password spraying tests a small set of likely passwords across many accounts.

In plain words
What is it for?
It helps decide when credential testing is allowed, gather relevant words, generate candidate passwords, run a cautious spray, detect successful access, and continue with authorized security testing.
Why use it?
It helps test for weak account security while accounting for rate limits, lockouts, program rules, and the risk of disrupting users.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the agentic-bug-hunter plugin — 16 skills, 37 commands, 9 agents, 3 hooks shipped together

Good fit It helps decide when credential testing is allowed, gather relevant words, generate candidate passwords, run a cautious spray, detect successful access, and continue with authorized security testing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/awarexone/agentic-bug-hunter/credential-attack
About the project

Agentic Bug Hunter is a terminal toolkit that uses AI to investigate security targets, test for vulnerabilities, validate findings, and write bug bounty reports. It is for ethical hackers submitting findings to platforms such as HackerOne, Bugcrowd, Intigriti, or Immunefi, and can resume previous sessions. The catalogue entries package commands, skills, agents, instructions, hooks, and settings for using the toolkit.

Awarexone/Agentic-Bug-Hunter · 5,315 stars · on GitHub · awarexone.com

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 Awarexone/Agentic-Bug-Hunter --skill credential-attack
Clone the repo
git clone --depth 1 https://github.com/Awarexone/Agentic-Bug-Hunter

Made for: Claude Code.

Or install agentic-bug-hunter, the plugin that ships this one along with the rest of its 16 skills, 37 commands, 9 agents, 3 hooks.

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 credential-attack

README.md
[![agentmods](https://agentmods.dev/badge/skills/awarexone/agentic-bug-hunter/credential-attack/github.svg)](https://agentmods.dev/skills/awarexone/agentic-bug-hunter/credential-attack)
Your own site
<a href="https://agentmods.dev/skills/awarexone/agentic-bug-hunter/credential-attack"><img src="https://agentmods.dev/badge/skills/awarexone/agentic-bug-hunter/credential-attack/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 credential-attack

Your own site · 80×15
<a href="https://agentmods.dev/skills/awarexone/agentic-bug-hunter/credential-attack"><img src="https://agentmods.dev/badge/skills/awarexone/agentic-bug-hunter/credential-attack.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,931 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found 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 $0.00102 $0.04931
Opus 5.5 $0.00041 $0.01972
Sonnet 5.5 $0.00020 $0.00986
Haiku 4.5 $0.00010 $0.00493

Measured 1mo ago against content hash 86d34b508a81, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

credential-attack scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

| `http-form` | Custom login page (most BB targets) | Pure Python urllib |
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/credential-attack/SKILL.md · 388 lines

How it starts

The opening of the file, as written. The whole thing — 388 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CREDENTIAL ATTACK PIPELINE

Real-world initial-access vector. Verizon DBIR consistently ranks Stolen Credentials in the top 3 incident types. Most BB hunters skip this because they only try rockyou.txt and get rate-limited.

Core principle: humans pick lazy passwords. {CompanyName}{Year}!, {ProductName}{Season}, {City}123. Harvesting company-specific vocabulary (product names, office cities, internal project codes) before spraying is what makes the hit-rate go from 0.01% to 1%+.

This skill covers WHEN to use credential attack, HOW to chain the 4 commands, and the legal/operational guardrails.


WHEN TO RUN CREDENTIAL ATTACK

Credential attack is a parallel branch to /hunt, not a replacement. Both come after /recon:

/recon ──┬──▶ /hunt (web vuln scan)         ──┐
         │                                     ├──▶ /validate ──▶ /report
         └──▶ /wordlist-gen → ... → /spray  ──┘

Run it when:

  • Target has a discoverable login endpoint (web form / O365 / Okta / OAuth)
  • Program scope explicitly permits authentication testing or credential testing
  • You can stomach a 30-min-to-multi-hour run (with conservative defaults)

Skip it when:

  • Program policy lists "credential stuffing", "brute force", or "password attacks" as out-of-scope (this is the majority)
  • Target only has SSO via a provider you don't control (e.g., "Login with Google")
  • The login endpoint is rate-limited so aggressively that even 1 attempt/30min triggers alerts

KILL signals (don't even start):

  • No login surface in recon output
  • WAF (Cloudflare with Bot Management, Akamai) on every auth endpoint
  • Program runs an active red-team — they'll see your spray immediately
  • You don't have a clean wordlist yet (running rockyou.txt is a waste of lockouts)

THE 4-STAGE PIPELINE

/wordlist-gen     ──▶  /breach-check     ──▶  /osint-employees   ──▶  /spray
(company words)        (rank by HIBP)         (real usernames)         (live attempts)

Read the full file on GitHub · 388 lines

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 · 388 lines · 102 tokens per session scan A 86d34b508a81

Subscribe to this mod's changes

credential-attack is a skill published in the GitHub repository Awarexone/Agentic-Bug-Hunter (5,315 stars, last pushed 8d ago), licensed MIT. It adds 102 tokens to every session and 4,931 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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