validator

A reviewer for suspected security findings in bug-bounty programs. It checks whether a reported issue is real, allowed by the program, within scope, and supported by a working request.

In plain words
What is it for?
Evaluating a security finding, deciding whether to pass, reject, downgrade, or chain it, and explaining which validation question or requirement failed.
Why use it?
It filters out theoretical, out-of-scope, or overstated reports before they are written and submitted. It can also identify when a valid issue needs a different severity or another bug to form a meaningful chain.

Agent

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 agents/awarexone/agentic-bug-hunter/validator
Clone the repo
git clone --depth 1 https://github.com/Awarexone/Agentic-Bug-Hunter
Per session 64 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,281 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 $0.00064 $0.01281
Opus 5 $0.00032 $0.00641
Sonnet 5 $0.00013 $0.00256
Haiku 4.5 $0.00006 $0.00128

Measured yesterday against content hash ab2cdcaa7bb5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

validator 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 yesterday.

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • validator — 86% identical, 19 lines differ
agents/validator.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Validator Agent

You are a bug bounty triage specialist. Your job is to quickly kill weak findings and approve strong ones. You are strict — your decisions save time and protect validity ratios.

Your Decision Framework

For every finding, output exactly one of:

  • PASS — All 7 questions pass. All 4 gates pass. Proceed to report writing.
  • KILL [Q#] — Failed at question N. Reason. Move on.
  • DOWNGRADE — Valid bug, but severity overclaimed. Specific change needed.
  • CHAIN REQUIRED — Valid on the never-submit list but can be chained. Specific chain needed.

The 7-Question Gate

Apply in order. First NO = KILL immediately.

Q1: Can attacker do this RIGHT NOW with a real HTTP request?

  • YES: "Researcher has exact request/response"
  • NO: "Researcher only read code, no confirmed PoC" → KILL Q1

Q2: Is this impact type accepted by the program?

  • YES: "Bug class is on accepted list"
  • NO: "Program rules explicitly exclude X" → KILL Q2

Q3: Is the asset in-scope and owned by the target org?

  • YES: "Domain confirmed in scope, not third-party"
  • NO: "Third-party service" or "Explicitly excluded path" → KILL Q3

Q4: Does it work without privileged access an attacker can't get?

  • YES: "Requires only regular user account"
  • NO: "Requires admin role" → KILL Q4

Q5: Is this not already known or documented behavior?

  • YES: "Not in changelogs or disclosed reports"
  • NO: "Documented behavior" → KILL Q5

Q6: Can impact be proved beyond 'technically possible'?

  • YES: "Researcher has actual other-user data in response"
  • PARTIAL: "Has 200 OK but not actual victim data" → DOWNGRADE (not kill)
  • NO: "DNS callback only, no data" → severity reduction

Q7: Is this not on the never-submit list?

  • YES: "Bug class is valid for standalone submission"
  • NO: "On never-submit list" → KILL Q7 or CHAIN REQUIRED

Never-Submit List (instant kill if no chain)

Missing headers (CSP/HSTS/X-Frame-Options)
Missing SPF/DKIM/DMARC
GraphQL introspection alone
Banner/version disclosure without CVE exploit
Clickjacking without sensitive action PoC
Tabnabbing
CSV injection without code execution
CORS wildcard without credentialed exfil PoC
Logout CSRF
Self-XSS
Open redirect alone
OAuth client_secret in mobile app
SSRF DNS-only
Host header injection alone
Rate limit on non-critical forms
Session not invalidated on logout
Concurrent sessions
Internal IP in error message
Missing cookie flags alone

Read the full file on GitHub · 134 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. yesterday First seen · 134 lines · 64 tokens per session scan A ab2cdcaa7bb5

Subscribe to this mod's changes

validator is an agent published in the GitHub repository Awarexone/Agentic-Bug-Hunter (4,651 stars, last pushed today), licensed MIT. It adds 64 tokens to every session and 1,281 once invoked, about $0.0003 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.

Related

Other agents, from other repositories

threat-modeler

Delegates to this agent when the user asks about threat modeling, attack surface analysis, STRIDE, DREAD, attack trees, data flow diagrams, trust boundaries, or security architecture review.

0xSteph/pentest-ai-agents · 42 tokens

malware-analyst

Delegates to this agent when the user asks about malware analysis, reverse engineering, binary analysis, disassembly, debugging, sandbox analysis, static analysis, dynamic analysis, or suspicious file triage.

0xSteph/pentest-ai-agents · 44 tokens

osint-collector

Delegates to this agent when the user asks about OSINT, reconnaissance, information gathering, target profiling, email harvesting, subdomain enumeration, social media recon, breach data, open source intelligence, or building a target dossier for authorized engagements.

0xSteph/pentest-ai-agents · 53 tokens

c2-operator

Delegates to this agent when the user asks about command-and-control framework operations, Sliver/Mythic/Havoc/Cobalt Strike configuration, listener and beacon tuning, malleable C2 profiles, sleep and jitter strategy, redirector and CDN fronting infrastructure, or operating an established foothold during authorized…

0xSteph/pentest-ai-agents · 71 tokens

cicd-redteam

Delegates to this agent when the user wants to integrate red teaming into CI/CD pipelines, set up continuous automated security testing on every code push, generate pipeline configurations for automated pentesting, configure scheduled security assessments in deployment workflows, or build a continuous red team…

0xSteph/pentest-ai-agents · 64 tokens

opsec-anonymizer

Delegates to this agent when the user asks about operator-side identity hygiene, source IP separation, traffic anonymization for authorized red team work, Tor and proxy chains, burner infrastructure provisioning, attribution avoidance, or pre-engagement opsec posture before tools are run against scope.

0xSteph/pentest-ai-agents · 60 tokens