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.
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.
git clone --depth 1 https://github.com/Awarexone/Agentic-Bug-HunterWrote 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.
[](https://agentmods.dev/commands/awarexone/agentic-bug-hunter/remember)<a href="https://agentmods.dev/commands/awarexone/agentic-bug-hunter/remember"><img src="https://agentmods.dev/badge/commands/awarexone/agentic-bug-hunter/remember/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.
<a href="https://agentmods.dev/commands/awarexone/agentic-bug-hunter/remember"><img src="https://agentmods.dev/badge/commands/awarexone/agentic-bug-hunter/remember.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00436 |
| Opus 5.5 | $0.00000 | $0.00174 |
| Sonnet 5.5 | $0.00000 | $0.00087 |
| Haiku 4.5 | $0.00000 | $0.00044 |
Grade A, and why
remember 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- remember — 100% identical, 0 lines differ
What it actually says
/remember
Save a finding or successful pattern to persistent hunt memory.
What This Does
- Auto-populates fields from session context (target, endpoint, vuln_class, technique)
- If
/validatewas run in this session, pre-fills from validation output - Prompts you to confirm or edit before saving
- Writes to
journal.jsonl(always) +patterns.jsonl(if confirmed + payout > 0) - Updates the target profile's
tested_endpointsandfindings
Usage
/remember # after finding something
/remember --from-validate # explicitly pull from last /validate
Interactive Flow
REMEMBER — Log finding to hunt memory
Target: target.com (auto-detected)
Endpoint: /api/v2/users/{id}/orders (from session)
Vuln Class: idor (from session)
Technique: numeric_id_swap_with_put_method
Result: [confirmed / rejected / partial / informational]?
Severity: [critical / high / medium / low]?
Payout: $___?
Notes: ___?
Tags: [comma-separated]?
Save to hunt memory? [y/n]
Minimum Required Fields
- target
- vuln_class
- endpoint
- result
What Gets Written
| Field | journal.jsonl | patterns.jsonl | target profile |
|---|---|---|---|
| Finding details | Always | If confirmed + payout > 0 | findings[] updated |
| Tested endpoint | — | — | tested_endpoints[] updated |
| Tech stack | — | From target profile | — |
Why This Matters
- Next time you hunt a target with similar tech stack, your successful patterns are suggested first
/pickup target.comshows which endpoints you've tested and which remain- Cross-target learning: patterns from target A inform hunting on target B
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.
- 1mo ago First seen · 63 lines · 0 tokens per session scan A c7de20c0cd8a
remember is a command published in the GitHub repository Awarexone/Agentic-Bug-Hunter (5,315 stars, last pushed 8d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 436 tokens. 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.
Other commands, from other repositories
memory-gc
Inspect or rotate the autopilot ledger JSONL files (findings.jsonl, negatives.jsonl). Caps file size and keeps N rotated backups so memory does not grow unbounded.
recon
Run full recon pipeline on a target — subdomain enum (Chaos API + subfinder), live host discovery (dnsx + httpx), URL crawl (katana + waybackurls + gau), gf pattern classification, nuclei scan. Outputs to recon/ / directory. Usage: /recon target.com.
hunt
Active vulnerability hunting. Two-track dispatcher — asks Red Team vs WAPT, hands off to hunt-dispatch skill and sibling commands. Usage: /hunt target.com | /hunt .target.com | /hunt targets.txt [--vuln-class X] [--source-code P] [--chrome].
token-scan
Meme coin and token security scan — checks for rug pull vectors (hidden mint, honeypot, fee manipulation, LP lock bypass, authority retention, bonding curve exploits, fake renounce, sandwich amplification). Manual 8-class grep audit (with an optional automated scanner if present). Usage: /token-scan [--chain solana].
autopilot
Run autonomous hunt loop on a target — scope check → recon → rank surface → hunt → validate → report with configurable checkpoints. Usage: /autopilot target.com [--paranoid|--normal|--yolo].
validate
Validate a finding — runs 7-Question Gate + 4-gate checklist. Kills weak findings before report writing. Prevents N/A submissions that hurt validity ratio. Usage: /validate.