crack-hashcat

A password-recovery and hash-cracking tool for authorized security work. A hash is a one-way representation of a password that can be tested against possible passwords.

In plain words
What is it for?
Use it for authorized password audits, forensic recovery, and testing password policies with different algorithms and attack methods.
Why use it?
It helps assess whether captured password hashes are weak or recover passwords during approved investigations.

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/agentsecops/secopsagentkit/crack-hashcat
Any agent
npx skills add AgentSecOps/SecOpsAgentKit --skill crack-hashcat
Clone the repo
git clone --depth 1 https://github.com/AgentSecOps/SecOpsAgentKit

Made for: Claude Code, Codex.

Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,780 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. Scan, not verified.
Origin unknown 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 $0.00090 $0.03780
Opus 5 $0.00045 $0.01890
Sonnet 5 $0.00018 $0.00756
Haiku 4.5 $0.00009 $0.00378

Measured 2d ago against content hash 9ff19a6c217d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

crack-hashcat scanned grade B with 2 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.

Asks for rootlowPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

sudo cat /etc/shadow | grep -v "^#" | grep -v ":\*:" | grep -v ":!:" > shadow_hashes.txt

Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.

Reaches for credential filesmediumPrivilege escalation

SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.

# From /etc/shadow (Linux)

Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.

skills/offsec/crack-hashcat/SKILL.md · 510 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

5 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 · 510 lines · 90 tokens per session scan B 9ff19a6c217d

Subscribe to this mod's changes

crack-hashcat is a skill published in the GitHub repository AgentSecOps/SecOpsAgentKit (202 stars, last pushed 4mo ago), with no licence file. It adds 90 tokens to every session and 3,780 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it B with 2 findings (asks for root, reaches for credential files). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

agent-security

Reviews AI agent architectures for security risks including permission model design, least-privilege enforcement, human-in-the-loop gate placement, blast radius containment, audit trail completeness, rollback capability, and multi-agent trust boundaries. Auto-invoked when reviewing agentic AI systems where LLMs invoke…

UnitOneAI/SecuritySkills · 99 tokens

agentic-top-10

Reviews agentic AI systems against the OWASP Top 10 security risks for autonomous AI agents. Auto-invoked when reviewing multi-agent architectures, AI agent deployments, or systems where LLMs have tool access and act autonomously. Covers permission models, tool security, memory integrity, trust boundaries, and human…

UnitOneAI/SecuritySkills · 82 tokens

forensics-checklist

Guides digital forensic evidence collection following NIST SP 800-86 and RFC 3227 order of volatility. Auto-invoked when the user needs to collect forensic evidence, preserve chain of custody, capture volatile data, create disk images, or handle cloud forensics. Produces an evidence collection plan with…

UnitOneAI/SecuritySkills · 85 tokens

analyzing-prefetch-files-for-execution-history

Parse Windows Prefetch files to determine program execution history including run counts, timestamps, and referenced files for forensic investigation.

Mikaru0Mystic/sectinel · 34 tokens

acquiring-disk-image-with-dd-and-dcfldd

Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.

pinkpixel-dev/skills-collection-1 · 38 tokens

analyzing-email-headers-for-phishing-investigation

Parse and analyze email headers to trace the origin of phishing emails, verify sender authenticity, and identify spoofing through SPF, DKIM, and DMARC validation.

Mikaru0Mystic/sectinel · 44 tokens