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Agent skill

Detecting Qr Code Phishing With Email Security

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Detect and prevent QR code phishing (quishing) attacks that embed malicious URLs inside QR code images to bypass link-based email security, using image-based threat detection, OCR/QR decoding, and…

Apache-2.0Auto-check passedSecurity

Install Detecting Qr Code Phishing With Email Security

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-qr-code-phishing-with-email-security -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-qr-code-phishing-with-email-security --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/detecting-qr-code-phishing-with-email-security .claude/skills/detecting-qr-code-phishing-with-email-security && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
detecting-qr-code-phishing-with-email-security
GitHub stars
34k
Token cost
~1.7k tokens
SKILL.md length
729 words
Files
8 (incl. scripts, references, assets)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Detect and prevent QR code phishing (quishing) attacks that embed malicious URLs inside QR code images to bypass link-based email security, using image-based threat detection, OCR/QR decoding, and…

  • Works in 5 steps: Enable Image-Based Threat Detection → Configure QR Code URL Analysis → Deploy Mobile-Side Protection → …
  • Configuring gateway rules against QR phishing
  • SKILL.md covers Overview, When to Use, Prerequisites and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder

What it does

Detecting Qr Code Phishing With Email Security is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Detect and prevent QR code phishing (quishing) attacks that embed malicious URLs inside QR code images to bypass link-based email security, using image-based threat detection, OCR/QR decoding, and mobile-side scanning (Microsoft Defender for O365, Proofpoint TAP, Barracuda Multimodal AI). Use when configuring gateway rules against QR phishing or investigating suspicious emails containing QR codes.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/api-reference.md` and `references/standards.md`).

It sits in Security. It works with Microsoft Defender. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Configuring gateway rules against QR phishing
  • Investigating suspicious emails containing QR codes

Example prompts

  • “/detecting-qr-code-phishing-with-email-security”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Enable Image-Based Threat Detection
  2. Configure QR Code URL Analysis
  3. Deploy Mobile-Side Protection
  4. Build Detection Rules
  5. Train Users on Quishing Recognition

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Detecting Qr Code Phishing With Email Security loads about 1.7k tokens when it runs, and up to ~3.4k if it reads all its reference files. Until then it costs about 112 tokens; SKILL.md has 729 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~112
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 729 words, ~1,697 tokens.

Download SKILL.mdSave it as .claude/skills/detecting-qr-code-phishing-with-email-security/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
detecting-qr-code-phishing-with-email-security
description
Detect and prevent QR code phishing (quishing) attacks that embed malicious URLs inside QR code images to bypass link-based email security, using image-based threat detection, OCR/QR decoding, and mobile-side scanning (Microsoft Defender for O365, Proofpoint TAP, Barracuda Multimodal AI). Use when configuring gateway rules against QR phishing or investigating suspicious emails containing QR codes.
domain
cybersecurity
subdomain
phishing-defense
tags
quishing, qr-code, phishing, email-security, image-analysis, ocr, mobile-security
version
1.0
author
mahipal
license
Apache-2.0
atlas_techniques
AML.T0052, AML.T0024, AML.T0035
nist_ai_rmf
MEASURE-2.8, MAP-5.1
nist_csf
PR.AT-01, DE.CM-09, RS.CO-02, DE.AE-02
mitre_attack
T1566, T1598, T1534, T1036, T1027

Detecting QR Code Phishing with Email Security

Overview

QR code phishing (quishing) is a rapidly growing attack vector where malicious URLs are embedded in QR code images within phishing emails. Quishing incidents grew fivefold from 46,000 to 250,000 between August and November 2025, with credential phishing comprising 89.3% of detected incidents. Traditional email security filters struggle because QR codes cannot be read by humans or standard URL scanners, and when scanned, users typically use personal mobile devices that lack corporate security controls. Attackers have evolved to use split QR codes (two separate images), nested QR codes, and ASCII text-based QR codes to evade detection.

When to Use

  • When investigating security incidents that require detecting qr code phishing with email security
  • When building detection rules or threat hunting queries for this domain
  • When SOC analysts need structured procedures for this analysis type
  • When validating security monitoring coverage for related attack techniques

Prerequisites

  • Email security gateway with image analysis capabilities
  • Understanding of QR code structure and encoding
  • Mobile device management (MDM) or mobile threat defense solution
  • Security awareness training program
  • SIEM platform for correlation and alerting

Key Concepts

Why Quishing Works
  1. Bypasses URL Scanners: Traditional gateways scan text-based URLs but cannot decode image-embedded URLs
  2. Shifts to Unprotected Devices: Corporate email arrives on secured systems but QR scan occurs on personal mobile devices
  3. User Trust: QR codes are normalized in daily life (payments, menus, parking)
  4. Low Detection Rate: Only 36% of quishing incidents are accurately identified by recipients
Evasion Techniques (2025)
  • Split QR Codes: QR code divided into two separate images that look benign individually (Gabagool PhaaS kit)
  • Nested QR Codes: QR code within a QR code, with first scan leading to intermediate page
  • ASCII QR Codes: QR rendered as text characters instead of images, bypassing image analysis (12% of attacks in Jan 2026)
  • Styled/Artistic QR Codes: Custom-designed QR codes with logos that evade pattern matching
  • PDF Attachment QR: QR code embedded in PDF attachment rather than email body
Detection Challenges
  • Pattern-based detection faces trade-off: aggressive tuning causes false positives, cautious tuning causes misses
  • Average similarity score of 0.209 between quishing and legitimate QR emails
  • QR codes in image attachments require OCR and deep image processing

Workflow

Step 1: Enable Image-Based Threat Detection
  • Configure email gateway to scan embedded images for QR codes
  • Enable OCR processing on image attachments (PNG, JPG, GIF, BMP)
  • Deploy multimodal AI that combines image processing, OCR, and NLP analysis
  • Configure PDF scanning to detect QR codes within attachments
  • Set up detection for ASCII/text-based QR code rendering
Show full SKILL.md (307 more words)Show less
Step 2: Configure QR Code URL Analysis
  • Extract URLs from detected QR codes and submit to URL reputation services
  • Apply same URL scanning policies to QR-extracted URLs as text-based URLs
  • Enable real-time sandbox analysis for QR-decoded destination pages
  • Configure time-of-click protection for QR-extracted URLs where possible
  • Block known phishing domains extracted from QR codes
Step 3: Deploy Mobile-Side Protection
  • Implement mobile threat defense (MTD) with QR code scanning capability
  • Deploy Palo Alto ALFA or equivalent safe-by-design QR scanning
  • Configure MDM policies to warn users before opening scanned URLs
  • Enable corporate VPN/secure browser for QR-scanned destinations
  • Block known credential harvesting domains at the mobile proxy level
Step 4: Build Detection Rules
  • Alert on emails containing only an image and minimal text (common quishing pattern)
  • Flag emails with QR code images from external first-time senders
  • Detect urgency language combined with QR code presence
  • Alert on emails impersonating IT/security team requesting QR scan for MFA setup
  • Monitor for common quishing themes: MFA reset, document signing, voicemail notification
Step 5: Train Users on Quishing Recognition
  • Update security awareness program to include QR code phishing scenarios
  • Conduct quishing simulation campaigns using controlled QR codes
  • Teach users to verify QR destination URLs before entering credentials
  • Establish reporting process for suspicious QR code emails
  • Distribute guidance on safe QR scanning practices

Tools & Resources

  • Barracuda Multimodal AI: OCR + deep image processing for QR detection
  • Palo Alto ALFA: Safe-by-design QR code scanning assessment
  • Microsoft Defender for O365: QR code detection in email images
  • Proofpoint TAP: Image-based threat analysis with QR decoding
  • Lookout/Zimperium: Mobile threat defense with QR scanning

Validation

  • QR code phishing emails detected in controlled testing
  • Split QR code and ASCII QR code evasion techniques caught
  • QR-extracted URLs submitted to sandbox analysis
  • Mobile devices alert on malicious QR destinations
  • User reporting rate for quishing simulations exceeds 50%
  • False positive rate for QR detection below 1%

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references, assets) in skills/detecting-qr-code-phishing-with-email-security of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • assets/template.md
  • references/api-reference.md
  • references/standards.md
  • references/workflows.md
  • scripts/agent.py
  • scripts/process.py

Open the folder on GitHubat commit 54a7988

Compare with similar skills

Detecting Qr Code Phishing With Email Security next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Detecting Qr Code Phishing With Email Security compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Detecting Qr Code Phishing With Email Security this skillmukul975/Anthropic-Cybersecurity-Skills34k—~1.7kAutomated safety check: PassApache-2.0
Azure Network Security Designvinayaklatthe/microsoft-security-skills175—~1.8kAutomated safety check: PassMIT
Cloud App Security Posturevinayaklatthe/microsoft-security-skills175—~2.1kAutomated safety check: PassMIT
Defender Easmvinayaklatthe/microsoft-security-skills175—~1.9kAutomated safety check: PassMIT
Sentinelvinayaklatthe/microsoft-security-skills175—~2.2kAutomated safety check: PassMIT
Threat Modellingvinayaklatthe/microsoft-security-skills175—~1.8kAutomated safety check: PassMIT

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Works with

Categories

Questions about Detecting Qr Code Phishing With Email Security

What does Detecting Qr Code Phishing With Email Security do?

Detect and prevent QR code phishing (quishing) attacks that embed malicious URLs inside QR code images to bypass link-based email security, using image-based threat detection, OCR/QR decoding, and…. Detecting Qr Code Phishing With Email Security is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Detect and prevent QR code phishing (quishing) attacks that embed malicious URLs inside QR code images to bypass link-based email security, using image-based threat detection, OCR/QR decoding, and mobile-side scanning (Microsoft Defender for O365, Proofpoint TAP, Barracuda Multimodal AI).

When should I use Detecting Qr Code Phishing With Email Security?

Detecting Qr Code Phishing With Email Security fits situations like: configuring gateway rules against QR phishing; investigating suspicious emails containing QR codes.

How do I install Detecting Qr Code Phishing With Email Security in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-qr-code-phishing-with-email-security -a claude-code`. Or copy the skill folder (skills/detecting-qr-code-phishing-with-email-security in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/detecting-qr-code-phishing-with-email-security in your project. Claude Code loads it when a task matches its description.

How do I install Detecting Qr Code Phishing With Email Security in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-qr-code-phishing-with-email-security -a codex`. Or copy the skill folder (skills/detecting-qr-code-phishing-with-email-security in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/detecting-qr-code-phishing-with-email-security in your project. Codex loads it when a task matches its description.

Can I use Detecting Qr Code Phishing With Email Security in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-qr-code-phishing-with-email-security -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/detecting-qr-code-phishing-with-email-security, .gemini/skills/detecting-qr-code-phishing-with-email-security, .github/skills/detecting-qr-code-phishing-with-email-security and .opencode/skills/detecting-qr-code-phishing-with-email-security in your project.

What does Detecting Qr Code Phishing With Email Security need to run?

Going by SKILL.md and its folder, Detecting Qr Code Phishing With Email Security needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Detecting Qr Code Phishing With Email Security access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Detecting Qr Code Phishing With Email Security safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Detecting Qr Code Phishing With Email Security use?

Detecting Qr Code Phishing With Email Security is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Detecting Qr Code Phishing With Email Security use?

About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.7k tokens, read only when the agent opens those files.

What are the alternatives to Detecting Qr Code Phishing With Email Security?

Skills that share tags, products or a category with Detecting Qr Code Phishing With Email Security: Azure Network Security Design (vinayaklatthe/microsoft-security-skills, 175 stars), Cloud App Security Posture (vinayaklatthe/microsoft-security-skills, 175 stars), Defender Easm (vinayaklatthe/microsoft-security-skills, 175 stars) and Sentinel (vinayaklatthe/microsoft-security-skills, 175 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Detecting Qr Code Phishing With Email Security?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.