password-attacks

A guide to testing password and credential attacks, including guessing passwords online, cracking stolen password hashes offline, password spraying, and Kerberos ticket attacks. A hash is a one-way representation of a password that can sometimes be tested against guesses.

In plain words
What is it for?
Authorized security assessments involving hash cracking, online login testing, password spraying, credential stuffing, Kerberos attacks, and custom wordlist creation.
Why use it?
Different credential situations require different tests, tools, and precautions. The guide helps classify whether the tester has password hashes, live services, domain accounts, or leaked credentials before choosing an approach.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/ogrodev/fsociety/password-attacks
Any agent
npx skills add ogrodev/fsociety --skill password-attacks
Clone the repo
git clone --depth 1 https://github.com/ogrodev/fsociety

Made for: Claude Code, Codex.

Per session 412 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,684 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00412 $0.03684
Opus 5 $0.00206 $0.01842
Sonnet 5 $0.00082 $0.00737
Haiku 4.5 $0.00041 $0.00368

Measured 2d ago against content hash f6026ad3751c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

password-attacks 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 2d 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.

elliot/skills/password-attacks/SKILL.md · 311 lines

How it starts

The opening of the file, as written. The whole thing — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Password Attacks

Full-spectrum credential attack skill covering offline hash cracking, online service brute forcing, domain password spraying, targeted wordlist generation, Kerberos ticket attacks, and credential stuffing with breach data. Choose the right attack class, tool, and OPSEC posture based on the scenario.

Why This Matters

Weak, reused, and default credentials remain the most common initial access vector across every engagement type. A single cracked hash can escalate from low-privilege foothold to domain admin. Password spraying bypasses per-account lockout policies. Breach credential reuse turns old leaks into fresh access. This skill covers every angle.

Decision Tree — Choosing Your Attack

Before touching a tool, classify the scenario:

Do you have hashes/credentials offline?
├── YES → OFFLINE ATTACKS
│   ├── Know the hash type? → hashcat/john with correct mode
│   ├── Unknown hash type? → hashid/hash-identifier first
│   ├── Windows hashes (NTLM)? → hashcat -m 1000, pass-the-hash
│   ├── Kerberos tickets? → references/kerberos-attacks.md
│   └── Need custom wordlist? → references/wordlist-generation.md
│
└── NO → ONLINE ATTACKS
    ├── Single target, known creds format? → Hydra/Medusa
    ├── Domain/AD environment? → Password spraying (crackmapexec/kerbrute)
    ├── Have breach data for target users? → Credential stuffing
    ├── Web login form? → Hydra http-post-form / Patator
    └── Need to avoid lockout? → Spray with lockout-aware timing

Methodology — Execution Order

Phase 1 — Intelligence Gathering

Before attacking, gather intelligence that shapes your approach:

  1. Password policy: Minimum length, complexity, lockout threshold, lockout duration, password history
  2. Target users: Enumerate valid usernames (LDAP, Kerberos, web user enumeration, OSINT)
  3. Hash types: Identify exact hash algorithm if you have offline hashes
  4. Service versions: Protocol-specific quirks affect tool selection
  5. Prior findings: Check if credentials were already found in other phases

Read the full file on GitHub · 311 lines

Files

What ships with it

6 files 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. 2d ago First seen · 311 lines · 412 tokens per session scan A f6026ad3751c

Subscribe to this mod's changes

password-attacks is a skill published in the GitHub repository ogrodev/fsociety (20 stars, last pushed 5mo ago), licensed MIT. It adds 412 tokens to every session and 3,684 once invoked, about $0.0021 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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