Skip to content

CavenderProjects/Multi-Modal-Scanner

Repository files navigation

Multi-Modal Vulnerability Scanner

A regulated-environment security assessment platform built and maintained by a senior information security professional with 20 years of GRC and security management experience across financial services, healthcare, and real estate.


Two Versions

Version Repo What It Is
Claude Code Skill Multi-Modal-Scanner AI-augmented assessment workflows inside Claude Code — install once, runs wherever Claude Code runs
Standalone App Multi-Modal-Scanner_Standalone Full PyQt6 desktop application — runs independently, no Claude Code required, persistent scan history, offline capable

Both versions share the core controls libraries (website/agent, API, code review, interconnected), compliance framework mappings, and report format. The standalone app is the production-ready version of the scanner with a full GUI, database-backed scan history, and an interactive report review interface.


What This Does

Across both versions the platform provides seven assessment workflows:

  • Website Vulnerability Assessment — Evaluates web applications against 67 controls across 13 families
  • AI Agent Assessment — Evaluates Claude skills, OpenAI GPTs, MCP servers, LangChain/LangGraph apps, Bedrock agents, and other AI agents against the same controls library, identifying risks specific to AI-augmented workflows (both versions)
  • API Vulnerability Assessment — Tests APIs against OWASP API Security Top 10 and 53 controls across 17 families, covering authentication, authorization, rate limiting, data exposure, and SSRF
  • Source Code Review — Static analysis of codebases against 51 controls across 12 families covering security flaws, complexity risks, and development practice gaps
  • STIG Compliance Assessment — Imports DISA STIG XCCDF files, parses rules into a structured controls library, and produces a compliance checklist report (both versions)
  • OS & Software Assessment — Scans Windows/Linux hosts for patch compliance, EOL software, insecure services, and CVE exposure (Standalone only)
  • Connected Systems Assessment — Correlates findings from two or more completed assessments to detect multi-step attack chains spanning connected systems, with CVSS re-scoring and reachability promotion analysis

Vulnerability assessment workflows (Website, AI Agent, API, Source Code, Connected Systems) produce interactive HTML reports with:

  • CVSS v3.1 scoring and vector strings
  • Severity pill filters (multi-select: Critical / High / Medium / Low)
  • Status filters (Compliant / Needs Review / Suppressed)
  • Expandable finding cards with evidence, remediation, and review procedures
  • Per-control triage actions: Confirm / Mark Compliant / Suppress as False Positive
  • Expandable Review Procedure for every Needs Review finding — specific numbered steps tailored to the control
  • Report save with original filename + timestamp preserved

The STIG Compliance Assessment produces a separate checklist report in CAT I/II/III severity format. The Standalone App supports prior report import to carry forward false positive decisions and notes across reassessments.


Compliance Framework Coverage

Every finding is cross-referenced against 12+ compliance and regulatory frameworks:

Framework Coverage
OWASP Top 10 (2025) All workflows
NIST SP 800-53 Rev 5 All workflows
ISO/IEC 27001:2022 All workflows
PCI-DSS v4.0.1 All workflows
SOC 2 Type II All workflows
HIPAA Security Rule All workflows
CMMC v2.0 Level 2 All workflows
DoD Cloud SRG All workflows
FedRAMP Moderate All workflows
SEC/FINRA All workflows
EU DORA All workflows
EU AI Act All workflows

Why It Exists

Security assessments generate noise. Regulated environments generate liability. After 11 years managing GRC programs across financial services, healthcare, and real estate, I built this to structure what I was doing manually: running findings against compliance frameworks, flagging ambiguous results for explicit review, and producing reports that hold up when they surface in an audit or board-level discussion.


Regulated Environment Considerations

1. False-Positive Risk

In regulated environments, a false positive isn't just wasted time — it can trigger unnecessary remediation spend, create misleading audit artifacts, or generate erroneous risk exceptions that become permanent record. Every finding with ambiguous scanner output is flagged for explicit manual review before being documented as confirmed.

2. Assessment Documentation

Any finding that may surface in an audit response, regulatory submission, or board-level risk report needs a clear record of: who assessed it, what context was applied, what compensating controls were considered, and what the final risk position is. Reports are structured for this and carry decisions forward across reassessment cycles.

3. Business-Constraint Remediation

Many findings in production regulated environments cannot be remediated in isolation. A vulnerability in a critical-care device, a legacy system under a multi-year vendor contract, or an integration a business unit depends on for revenue falls into this category. The tool supports suppression and false-positive documentation for findings where remediation isn't viable.


Repository Structure

Multi-Modal-Scanner/
├── README.md
├── pen-tester/
│   ├── SKILL.md                                    # Claude Code skill definition
│   ├── assets/
│   │   ├── report-template.html                    # Website & AI Agent report template
│   │   ├── api-report-template.html                # API vulnerability report template
│   │   ├── code-review-report-template.html        # Source code review report template
│   │   ├── interconnected-report-template.html     # Connected systems report template
│   │   └── stig-report-template.html               # STIG checklist report template
│   ├── references/
│   │   ├── controls-library.md                     # 67 controls, 13 families (Website/Agent)
│   │   ├── api-controls-library.md                 # 53 controls, 17 families (API)
│   │   ├── code-review-controls.md                 # 51 controls, 12 families (Code Review)
│   │   ├── interconnected-controls.md              # 27 controls, 9 families (Connected)
│   │   └── os-software-controls.md                 # OS & software security controls
│   └── test-reports/                               # Sample generated reports
└── Multi-Modal-Scanner_Standalone/                 # → See standalone repo
    # Full PyQt6 desktop app — lives at:
    # https://github.com/CavenderProjects/Multi-Modal-Scanner_Standalone

Standalone App

The standalone desktop application is maintained in a separate repository: github.com/CavenderProjects/Multi-Modal-Scanner_Standalone

It is the full, independently deployable version of this scanner — no Claude Code, no API dependency. Designed for use in air-gapped or restricted environments where a Claude API connection is not available or not permitted.

Key differences from the Claude Code skill:

Feature Claude Code Skill Standalone App
Runtime Claude Code Python + PyQt6 (desktop)
Claude API required Yes No
Scan history Per session SQLite database, persistent
Report triage In report (browser) In-app triage interface
AI Agent assessment Yes Yes
STIG import Yes (XCCDF) Yes (XCCDF)
OS & Software assessment No Yes
Prior report import No Yes (FP + notes carryover)

Limitations and Caveats

This is a workflow augmentation tool, not an autonomous security assessment engine.

  • It does not perform port scanning, network discovery, or automated exploitation. Website and API assessments make live HTTP requests to the target; OS, code review, STIG, and agent assessments do not make external network requests
  • Output requires review by a qualified security professional before use in any regulatory or audit context
  • False-positive evaluation is only as good as the context provided
  • It does not replace legal review for risk acceptance decisions with significant regulatory exposure

Part of a Broader AI Governance Practice Portfolio

Artifact Status Description
Multi-Modal Vulnerability Scanner (this repo) Live Regulated-environment security assessment platform — Claude Code skill + standalone app
AI Risk Assessment Template In progress Maps NIST AI RMF + ISO 42001 controls to GRC language enterprises already use
AI Vendor Risk Questionnaire In progress 25-question due diligence framework for evaluating third-party AI vendors

Background

Christopher Cavender, CISSP, CCSP | IAPP AIGP (in progress)

20 years in information security and GRC. Former Business Information Security Officer at Anywhere Real Estate (Fortune 500); 11 years managing security programs across financial services, healthcare, and real estate. Currently Information Systems Security Manager at Tripoint Solutions. NJ/NYC.

Connect: LinkedIn


Contributing

Contributions welcome, especially from practitioners working in regulated environments with specific HIPAA, NYDFS, PCI, EU AI Act, or other framework-specific context to add. Open an issue or submit a PR.


License

MIT License. Use freely. Attribution appreciated but not required.


Built 2026 · Part of an active AI governance practice portfolio

About

Claude Code skill for AI-augmented multi modal security scanning in regulated environments — false-positive evaluation, regulated-environment risk workflow

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors