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Introduction:
The landscape of financial crime compliance is undergoing a radical shift, moving away from static, rule-based systems toward dynamic, intelligence-led frameworks. As highlighted by Neotas’ recent recognition as a Market Disrupter in the Chartis FCC50 report, the integration of Artificial Intelligence (AI), Machine Learning (ML), and Generative AI (GenAI) is no longer a luxury but a necessity for managing third-party and supply chain risk. This article provides a technical deep dive into the methodologies and tools that power such next-generation compliance platforms, offering cybersecurity professionals a hands-on guide to implementing similar capabilities, from OSINT gathering to API security hardening.
Learning Objectives:
- Understand how to leverage AI and OSINT techniques for enhanced third-party risk management (TPRM).
- Learn to configure and utilize low-code/no-code environments for rapid security tool development.
- Master specific Linux and Windows commands for supply chain risk investigation and data forensics.
- Explore the implementation of GenAI for automated compliance reporting and threat analysis.
You Should Know:
1. Automated Open-Source Intelligence (OSINT) Gathering for KYTP
Modern Know Your Third Party (KYTP) processes require scraping vast amounts of data from the clear, deep, and dark web. Neotas’ platform excels by automating this data collection. To emulate this for supply chain risk assessment, security engineers can utilize a combination of command-line tools and APIs.
Step‑by‑step guide for Linux (OSINT Aggregation):
Start by aggregating data on a third-party vendor using `theHarvester` and recon-ng.
Install theHarvester on Kali Linux
sudo apt-get update && sudo apt-get install theharvester
Gather emails, hosts, and virtual hosts related to a target domain (e.g., vendor.com)
theharvester -d vendor.com -b all -f /tmp/vendor_osint.html
Use curl to check for exposed .git or .env files on the vendor's web server (common misconfigurations)
curl -s -o /dev/null -w "%{http_code}\n" https://vendor.com/.git/config
if [ $? -eq 200 ]; then echo "VULNERABILITY: .git exposed!"; fi
What this does: It automates the initial footprinting of a vendor, checking for data leaks and exposed configuration files that could indicate poor security hygiene.
- Implementing Low-Code Security Automation with Power Automate and Python
The “low/no-code user interface” mentioned in the report allows compliance teams to build workflows without heavy development. However, security professionals often need to harden these workflows.
Step‑by‑step guide (Hybrid Approach):
- Create a Flow: In Microsoft Power Automate, create a cloud flow triggered by a new vendor onboarding form.
- Inject Custom Code: Use the “Python script” action (or Azure Function) to run a custom security check that isn’t native to the low-code platform.
Python snippet to validate a vendor's SSL certificate health import ssl import socket import datetime</li> </ol> hostname = vendor_url Passed from the low-code workflow ctx = ssl.create_default_context() with ctx.wrap_socket(socket.socket(), server_hostname=hostname) as s: s.connect((hostname, 443)) cert = s.getpeercert() expiry = datetime.datetime.strptime(cert['notAfter'], '%b %d %H:%M:%S %Y %G') days_left = (expiry - datetime.datetime.now()).days if days_left < 30: print("Risk Alert: Certificate expires soon")What this does: It enhances the low-code interface by embedding a custom Python script to check SSL certificate expiry, ensuring encrypted communication channels with the third party remain secure.
- Supply Chain Risk Hardening: Windows PowerShell for Active Directory Audits
Supply chain risk isn’t just external; it involves how vendors interact with your internal directories. Using Windows PowerShell, security teams can audit vendor access.
Step‑by‑step guide (Windows Server/Desktop):
Export a list of all users with vendor accounts in Active Directory Get-ADUser -Filter "Company -eq 'VendorName'" -Properties MemberOf, LastLogonDate | Select-Object Name, SamAccountName, @{Name="Groups";Expression={$<em>.MemberOf -join ";"}}, LastLogonDate | Export-Csv -Path C:\Audits\Vendor_Access</em> Audit.csv -NoTypeInformation Check for dormant accounts (older than 90 days) $CutoffDate = (Get-Date).AddDays(-90) Get-ADUser -Filter "LastLogonDate -lt '$CutoffDate' -and Company -eq 'VendorName'" | Disable-ADAccount -WhatIfWhat this does: It identifies and disables dormant vendor accounts, mitigating the risk of compromised credentials being used by former or inactive third-party partners.
4. Deploying GenAI for Compliance Summarization
Generative AI, as used by Neotas, can summarize complex financial crime reports. Security teams can deploy local Large Language Models (LLMs) to avoid sending sensitive data to public clouds.
Step‑by‑step guide (Linux with Ollama):
Install Ollama (Local GenAI runner) curl -fsSL https://ollama.com/install.sh | sh Pull a model (e.g., Llama 3 or Mistral) ollama pull mistral Create a prompt to summarize a compliance PDF (after converting to text) cat compliance_report.txt | ollama run mistral "Summarize this due diligence report and list all red flags regarding PEP status or sanctions:"
What this does: It allows an analyst to run an AI model locally to digest lengthy compliance documents, extracting key risk indicators without exposing proprietary data to third-party AI services.
5. API Security and Configuration Review
To ensure the integrity of the data feeding into platforms like Neotas, APIs must be secured against injection and data exfiltration.
Step‑by‑step guide (cURL for API Hardening):
Test your financial crime API endpoints for common vulnerabilities.
Test for SQL Injection in a third-party data query API curl -X GET "https://api.vendor-risk.com/lookup?company=ACME%20Corp'%20OR%20'1'%3D'1" Test for excessive data exposure (IDOR) Attempt to access a report belonging to a different company by changing the ID curl -H "Authorization: Bearer VALID_TOKEN" "https://api.vendor-risk.com/reports/12345" curl -H "Authorization: Bearer VALID_TOKEN" "https://api.vendor-risk.com/reports/12346"
What this does: It validates that the APIs feeding your compliance platform enforce proper authorization and are resilient to injection attacks, preventing data breaches.
What Undercode Say:
The recognition of Neotas underscores a critical pivot in cybersecurity: compliance is becoming synonymous with continuous, automated threat intelligence.
– Key Takeaway 1: The fusion of AI and OSINT allows organizations to shift from periodic, reactive vendor checks to real-time, proactive supply chain monitoring.
– Key Takeaway 2: Low-code platforms are democratizing security automation, but they require rigorous hardening through embedded scripts and strict API governance to prevent them from becoming a weak link.By adopting these hybrid approaches—combining low-code agility with command-line precision and local GenAI—security teams can build resilient frameworks capable of navigating the complex financial crime landscape of 2026.
Prediction:
By 2027, regulatory bodies will begin mandating “AI-Driven Continuous Monitoring” for critical infrastructure vendors, rendering annual compliance questionnaires obsolete. Platforms like Neotas will evolve from disruptors to standard-bearers, forcing traditional audit firms to acquire or develop similar real-time intelligence capabilities to remain relevant.
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Reported By: Neotas Thirdpartyriskmanagement – Hackers Feeds
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- Supply Chain Risk Hardening: Windows PowerShell for Active Directory Audits
