bynn-document-fraud

bynn-document-fraud is a skill for Claude Code from Bynn-Intelligence/skills. It costs 102 tokens per session (1,486 once invoked), scanned A, original, MIT.

A document-forensics API for examining PDFs and images such as IDs, passports, invoices, bank statements, and contracts. You submit a document first, then retrieve its later risk and authenticity findings.

In plain words
What is it for?
Use it to screen documents for manipulation, forgery, deepfakes, or AI generation. It also returns parsed information and an overall risk score.
Why use it?
It removes the need to implement separate checks for editing, fake templates, inconsistent fonts or layouts, signatures, AI-generated content, metadata, and document codes. The result is asynchronous, so submission returns a receipt rather than an immediate verdict.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the bynn plugin — 10 skills shipped together

Good fit Use it to screen documents for manipulation, forgery, deepfakes, or AI generation. It also returns parsed information and an overall risk score.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/bynn-intelligence/skills/bynn-document-fraud
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.

Any agent
npx skills add Bynn-Intelligence/skills --skill bynn-document-fraud
Clone the repo
git clone --depth 1 https://github.com/Bynn-Intelligence/skills

Made for: Claude Code.

Or install bynn, the plugin that ships this one along with the rest of its 10 skills.

Wrote 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.

agentmods badge for bynn-document-fraud

README.md
[![agentmods](https://agentmods.dev/badge/skills/bynn-intelligence/skills/bynn-document-fraud/github.svg)](https://agentmods.dev/skills/bynn-intelligence/skills/bynn-document-fraud)
Your own site
<a href="https://agentmods.dev/skills/bynn-intelligence/skills/bynn-document-fraud"><img src="https://agentmods.dev/badge/skills/bynn-intelligence/skills/bynn-document-fraud/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.

agentmods 80×15 button for bynn-document-fraud

Your own site · 80×15
<a href="https://agentmods.dev/skills/bynn-intelligence/skills/bynn-document-fraud"><img src="https://agentmods.dev/badge/skills/bynn-intelligence/skills/bynn-document-fraud.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,486 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00102 $0.01486
Opus 5 $0.00051 $0.00743
Sonnet 5 $0.00020 $0.00297
Haiku 4.5 $0.00010 $0.00149

Measured 9d ago against content hash 90fd1df5b989, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

bynn-document-fraud 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 9d 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.

curl -X POST https://api.bynn.com/v1/documents \
plugins/bynn/skills/bynn-document-fraud/SKILL.md · 161 lines

How it starts

The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Document fraud detection

One submission runs the full forensic pipeline: forgery template matching, tampering and manipulation detection, font and layout consistency, signature validation, deepfake and AI-generation scoring, MRZ and barcode parsing, EXIF analysis, classification, and an overall risk score.

This is asynchronous. Submitting returns a receipt, not a verdict.

Base: https://api.bynn.com/v1. Private key on both calls.

1. Submit

Multipart, which is what you want for anything of real size:

curl -X POST https://api.bynn.com/v1/documents \
  -H "Authorization: Bearer <YOUR_PRIVATE_KEY>" \
  -F "file=@/path/to/document.pdf" \
  -F "reference_id=order-8123"

Or JSON with strict base64, no line breaks and no data: prefix:

curl -X POST https://api.bynn.com/v1/documents \
  -H "Authorization: Bearer <YOUR_PRIVATE_KEY>" \
  -H "Content-Type: application/json" \
  -d '{ "document_base64_strict": "<...>", "reference_id": "order-8123" }'

Send file or document_base64_strict, not both.

Response:

{ "submission_id": "document_...", "document_id": "...", "status": "received" }

submission_id is what you poll. Store it.

Submit the original file, never a derivative

Do not resize, crop, re-encode, re-compress, or otherwise process the document before submitting it. Send the bytes exactly as you received them.

Tampering detection, AI-generation scoring, and deepfake analysis all work on traces the manipulation left in the file: compression and quantization artifacts, resampling patterns, sensor noise, font and edge inconsistencies, and EXIF. Those traces live in the exact bytes. Resizing resamples them away, re-encoding overwrites them with your own encoder's artifacts, and stripping metadata removes evidence outright.

The failure mode is quiet and dangerous: a processed forgery comes back looking clean.

  • Store the original upload and submit that, not a thumbnail or a normalized copy.
  • Do not flatten a PDF to an image, and do not re-render it. Send the PDF.
  • Do not run the file through an image optimizer, a screenshot, or a messaging app.
  • If a file exceeds the size limit, reject or escalate it. Do not shrink it and submit anyway. A downscaled submission can return a false clean verdict.

Read the full file on GitHub · 161 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. 9d ago First seen · 161 lines · 102 tokens per session scan A 90fd1df5b989

Subscribe to this mod's changes

bynn-document-fraud is a skill published in the GitHub repository Bynn-Intelligence/skills (0 stars, last pushed 16d ago), licensed MIT. It adds 102 tokens to every session and 1,486 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 2026-08-31.

Related

Other skills, from other repositories

compliance-documentation-requirements

Use when setting up or auditing how compliance documentation is structured, collected, and preserved for regulatory audit in Salesforce FSC — covering KYC data collection workflows, AML screening integration setup, audit trail configuration, and regulatory reporting readiness. Triggers: KYC form setup, AML integration…

PranavNagrecha/AwesomeSalesforceSkills · 148 tokens

compliance-documentation-requirements

Use when setting up or auditing how compliance documentation is structured, collected, and preserved for regulatory audit in Salesforce FSC — covering KYC data collection workflows, AML screening integration setup, audit trail configuration, and regulatory reporting readiness. Triggers: KYC form setup, AML integration…

BanibrataChatterjee/AwesomeSalesforceSkills · 148 tokens

specification-writing

A workflow for writing complete patent specifications from patent claims and an invention disclosure. It adapts the document to a chosen jurisdiction, such as the US, Europe, or China.

wanshuiyin/Auto-claude-code-research-in-sleep · 49 tokens

x-scorecard

OpenSSF Scorecard for assessing open source project security. Check security best practices and compliance. Dependency: This is an x-cmd module. Install x-cmd first (see x-cmd skill for installation options). see x-cmd skill for installation.

x-cmd/x-cmd · 57 tokens

gesellschaftsrechtliche-satzungen-agb

Für Gesellschaftsrechtliche Satzungen AGB Abgrenzung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: gesellschaftsrechtliche-satzungen-agb.

Klotzkette/claude-fuer-deutsches-recht · 69 tokens

nda-review

Use when the user uploads or pastes a non-disclosure agreement and asks for review, redline, risk assessment, or a recommendation on whether to sign. Identifies missing standard protections, one-sided or unusual provisions, and operational issues; produces a structured report with severity ratings and citations to…

LegalQuants/lq-ai · 79 tokens