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.
npx agentmods add skills/awarexone/agentic-bug-hunter/credential-attacknpx skills add Awarexone/Agentic-Bug-Hunter --skill credential-attackgit clone --depth 1 https://github.com/Awarexone/Agentic-Bug-HunterWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00102 | $0.04931 |
| Opus 5 | $0.00051 | $0.02465 |
| Sonnet 5 | $0.00020 | $0.00986 |
| Haiku 4.5 | $0.00010 | $0.00493 |
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 3d 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 | 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)
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.
- 3d ago First seen · 388 lines · 102 tokens per session scan A 86d34b508a81
credential-attack is a skill published in the GitHub repository Awarexone/Agentic-Bug-Hunter (4,651 stars, last pushed yesterday), licensed MIT. It adds 102 tokens to every session and 4,931 once invoked, about $0.0005 per session on Opus 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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