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Introduction:
As digital transformation accelerates and attack surfaces expand at an unprecedented rate, organisations face a fundamental challenge: how to maintain continuous visibility over their entire digital footprint while effectively prioritising and remediating vulnerabilities before attackers exploit them. YesWeHack, a leading offensive security and exposure management platform founded by ethical hackers in 2015, is addressing this challenge through a unified approach that combines crowdsourced bug bounty programs, autonomous penetration testing, and continuous attack surface mapping. At GITEX AI Europe 2026 in Berlin, YesWeHack is showcasing how organisations can move beyond fragmented, point-in-time security assessments to embrace a proactive, continuous, and measurable security posture.
Learning Objectives:
- Understand the core components of a modern offensive security and exposure management strategy, including attack surface mapping, continuous testing, and risk-based prioritisation.
- Learn how to implement continuous security testing using both crowdsourced human intelligence (bug bounty) and automated validation checkpoints.
- Gain practical knowledge of tools and commands for attack surface discovery, vulnerability assessment, and remediation validation across Linux and Windows environments.
- Explore how AI-powered systems introduce new attack vectors and how to test them effectively using hybrid human-AI approaches.
- Develop a framework for moving from reactive vulnerability management to proactive Continuous Threat Exposure Management (CTEM).
You Should Know:
- Mapping Your Attack Surface: The Foundation of Proactive Security
Before you can defend your organisation, you must know what you are defending. Attack Surface Management (ASM) is the process of continuously discovering, inventorying, and monitoring all internet-facing assets—including web applications, APIs, cloud infrastructure, subdomains, and exposed services. YesWeHack’s platform automates this discovery, enumerating subdomains, identifying related domains, and detecting open ports, protocols, and technology versions in real-time.
For security teams looking to implement ASM independently, a combination of open-source and commercial tools can provide comprehensive coverage. Below is a practical workflow for mapping your external attack surface using industry-standard tools.
Step-by-Step Guide: External Attack Surface Mapping
Step 1: Subdomain Enumeration
Subdomain discovery is critical because attackers often target forgotten or poorly secured subdomains. Use tools like subfinder, amass, or `assetfinder` to enumerate subdomains associated with your primary domain.
Linux - Subdomain enumeration with subfinder subfinder -d example.com -o subdomains.txt Linux - Passive subdomain enumeration with amass amass enum -passive -d example.com -o amass_subdomains.txt Combine and sort unique subdomains cat subdomains.txt amass_subdomains.txt | sort -u > all_subdomains.txt
Step 2: Live Host Validation
Not all discovered subdomains resolve to live hosts. Use `httpx` or `massdns` to filter for responsive assets.
Linux - Validate live hosts with httpx cat all_subdomains.txt | httpx -silent -o live_hosts.txt Linux - MassDNS for high-speed DNS resolution massdns -r resolvers.txt -t A all_subdomains.txt -o S -w resolved.txt
Step 3: Port and Service Discovery
Once live hosts are identified, perform port scanning to discover open services. `masscan` is optimised for high-speed scanning across large IP ranges, while `nmap` provides detailed service and version information.
Linux - Masscan for rapid port discovery (scanning all ports) masscan -iL live_hosts.txt -p1-65535 --rate=10000 -oJ masscan_results.json Linux - Nmap for detailed service enumeration on discovered ports nmap -sV -sC -p 80,443,8080,8443 -iL live_hosts.txt -oA nmap_scan
Step 4: Technology Fingerprinting
Identify web technologies, frameworks, and versions using tools like whatweb, wappalyzer, or retire.js.
Linux - Technology fingerprinting with whatweb whatweb -i live_hosts.txt --log-json=whatweb_results.json
Windows Alternative: PowerShell for Port Scanning
Windows - Basic port scan using Test-1etConnection
$ports = @(80,443,8080,8443,22,21,25,53)
$hosts = Get-Content .\live_hosts.txt
foreach ($host in $hosts) {
foreach ($port in $ports) {
$result = Test-1etConnection -ComputerName $host -Port $port -WarningAction SilentlyContinue
if ($result.TcpTestSucceeded) {
Write-Host "$host : $port open"
}
}
}
2. Continuous Security Testing: Moving Beyond Point-in-Time Assessments
Traditional penetration tests provide a snapshot of security at a single point in time, but attack surfaces evolve continuously—new assets are deployed, configurations change, and new vulnerabilities emerge daily. YesWeHack addresses this through Continuous Pentesting, which combines attack surface discovery, targeted security checkpoints, and expert human validation to uncover exploitable vulnerabilities with a 0% noise rate.
The Continuous Pentesting workflow follows five key steps:
- Asset Specification: Define domains, IP addresses, and ranges that constitute your external footprint, assigning business criticality to each asset.
- Automated Mapping: The platform continuously enumerates subdomains, related domains, open services, and technology components in real-time.
- Security Checkpoints: A proprietary library of autonomous tests runs continuously against your attack surface, targeting actively exploited vulnerabilities—emerging CVEs, misconfigurations, and subdomain takeovers.
- Expert Validation: Each finding is validated by experienced security professionals to eliminate false positives and confirm exploitability within your specific environment.
- Risk-Based Prioritisation: Vulnerabilities are prioritised based on asset value, severity, and exploitability, enabling teams to focus on the most critical risks first.
For organisations building their own continuous testing pipelines, integrating automated vulnerability scanners with human validation is essential. Below is a workflow using open-source tools.
Step-by-Step Guide: Automated Vulnerability Scanning with Validation
Step 1: Vulnerability Scanning with Nuclei
Nuclei is a fast, customisable vulnerability scanner powered by a extensive template library.
Linux - Nuclei scan against live hosts nuclei -l live_hosts.txt -t cves/ -t misconfiguration/ -t exposures/ -severity critical,high -o nuclei_critical_high.txt Linux - Nuclei scan with custom template directory nuclei -l live_hosts.txt -t ~/nuclei-templates/ -tags cve,2024 -o nuclei_cve_2024.txt
Step 2: Web Application Scanning with OWASP ZAP
For deeper web application testing, OWASP ZAP provides both automated and manual testing capabilities.
Linux - OWASP ZAP headless scan (Docker) docker run -v $(pwd):/zap/wrk/:rw -t zaproxy/zap-stable zap-baseline.py -t https://example.com -r /zap/wrk/zap_report.html
Step 3: API Security Testing
APIs are increasingly targeted by attackers. Tools like `Postman` (for manual testing) and `Burp Suite` (for intercepting and modifying traffic) are essential.
Linux - Using ffuf for API endpoint fuzzing ffuf -u https://api.example.com/FUZZ -w /usr/share/wordlists/api_endpoints.txt -mc 200,401,403,404 -o api_fuzz_results.json
Step 4: Validation and Prioritisation
Automated scanners generate many findings, many of which are false positives or low-priority issues. Validation requires manual verification or correlation with asset criticality.
Python script to correlate findings with asset criticality
import json
Load asset criticality data
with open('asset_criticality.json', 'r') as f:
assets = json.load(f)
Load vulnerability scan results
with open('nuclei_results.json', 'r') as f:
findings = json.load(f)
Prioritise findings based on asset value
prioritised = []
for finding in findings:
asset = finding.get('host')
if asset in assets:
finding['priority_score'] = assets[bash]['criticality'] finding['severity_score']
prioritised.append(finding)
prioritised.sort(key=lambda x: x['priority_score'], reverse=True)
3. Leveraging Crowdsourced Intelligence: Bug Bounty Programs
Bug bounty programs provide access to a diverse, global community of skilled ethical hackers who conduct continuous, ad-hoc security testing across your entire attack surface. YesWeHack’s community exceeds 150,000 ethical hackers, delivering continuous audit coverage that uncovers high-impact vulnerabilities—even on heavily-penetrated scopes. Bug bounty programs are particularly effective at identifying complex, logic-based vulnerabilities that automated scanners miss, such as business logic flaws, privilege escalation issues, and intricate injection attacks.
The key success factors for a bug bounty program include:
- Clear Scope Definition: Precisely define which assets, applications, and APIs are in scope, along with any exclusions.
- Transparent Reward Structure: Establish competitive bounty amounts based on vulnerability severity, with clear payout criteria.
- Efficient Triage: Rapidly validate and respond to submissions to maintain researcher engagement.
- Continuous Communication: Provide timely updates on remediation status and acknowledge researcher contributions.
YesWeHack’s platform streamlines this process with in-house triage, personalised support, and results-based pricing. Clients include Tencent, Swiss Post, Orange France, the French Ministry of Armed Forces, Louis Vuitton, Ferrero, and the European Commission.
4. Testing AI-Powered Systems: The Hybrid Challenge
As organisations rapidly deploy AI-powered systems—including LLMs, autonomous agents, and MCP servers—the attack surface expands into new and complex dimensions. AI components increasingly handle sensitive data, make autonomous decisions, and interact with backend infrastructure, introducing risks that traditional security testing alone cannot address.
YesWeHack has developed a three-pillar framework for testing AI-powered systems:
- Testing the Foundation: Securing the traditional stack around AI—web applications, APIs, cloud infrastructure, authentication layers, and data pipelines. AI integrations introduce new API endpoints, data flows, storage mechanisms, and third-party dependencies, each expanding the attack surface in familiar ways.
- Testing the Integration Layer: AI-specific vulnerabilities such as prompt injection, training data poisoning, model denial of service, and insecure output handling.
- Testing the Guardrails: Model behaviour and misuse resistance, including testing for bias, hallucinations, and adversarial inputs.
YesWeHack has launched and optimised dozens of bug bounty programs with AI-related scopes, from simple chatbot interfaces to complex multi-agent architectures with tool-calling capabilities. The company’s “experts in the loop” approach combines AI-assisted researchers with experienced triage teams, ensuring that AI-specific vulnerabilities are validated for exploitability within context—an area where automated AI security tools typically fall short.
Step-by-Step Guide: Testing AI System Foundations
Step 1: API Endpoint Discovery
AI systems expose numerous API endpoints for model interaction, configuration, and administration.
Linux - Discovering API endpoints using gospider gospider -s https://ai.example.com -o api_discovery -c 10 -d 3 Linux - Extracting endpoints from JavaScript files cat api_discovery/.txt | grep -E '/(api|v1|v2|graphql|rest)/' | sort -u > api_endpoints.txt
Step 2: Testing for Insecure Direct Object References (IDOR)
AI chatbots often expose conversation histories via API endpoints. Test for IDOR by manipulating object identifiers in API requests.
Using curl to test for IDOR on conversation history
for id in {1..100}; do
curl -s -o /dev/null -w "%{http_code}\n" -H "Authorization: Bearer $TOKEN" "https://ai.example.com/api/conversations/$id"
done
Step 3: Testing for Server-Side Request Forgery (SSRF)
AI features that process URLs (e.g., “summarise this page”) are prime targets for SSRF attacks.
Testing SSRF with internal IP addresses
curl -X POST -H "Content-Type: application/json" -d '{"url":"http://169.254.169.254/latest/meta-data/"}' https://ai.example.com/api/summarize
Step 4: API Key and Secret Exposure
Scan for exposed API keys, tokens, and credentials in code repositories, configuration files, and error messages.
Linux - Using truffleHog for secret scanning trufflehog filesystem --directory /path/to/repo --json | jq '.' Linux - Using git-secrets to prevent secret commits git secrets --scan
- Moving from Fragmented Testing to Continuous Threat Exposure Management (CTEM)
Gartner’s Continuous Threat Exposure Management (CTEM) framework provides a structured approach to ongoing security testing and risk reduction. The framework operates through five integrated phases:
- Scoping: Define your attack surface and key assets—what needs to be protected and what is the business impact of each asset.
- Discovery: Identify vulnerabilities, misconfigurations, and exposures across all assets.
- Prioritisation: Rank threats by business impact, not just CVSS score, considering asset criticality and exploitability.
- Validation: Confirm exploitability through targeted testing, eliminating false positives and theoretical vulnerabilities.
- Mobilisation: Coordinate remediation efforts across security, development, and operations teams.
YesWeHack’s unified platform operationalises all five phases, providing consolidated vulnerability management, streamlined collaboration workflows, and risk-based prioritisation dashboards. The platform aggregates findings from any source—bug bounty reports, autonomous pentests, continuous pentesting, and third-party scanners—into a single, standardised interface. Executive dashboards provide unified visibility and actionable insight across all assets, while one-click audit proofs and executive summaries support continuous compliance with evolving regulations including SOC2, ISO 27001, DORA, and NIS2.
Step-by-Step Guide: Implementing CTEM with Open-Source Tools
Step 1: Asset Inventory and Scoping
Maintain a comprehensive asset inventory using tools like `OpenVAS` or `Nessus` for network discovery.
Linux - OpenVAS network discovery gvm-cli --gmp-username admin --gmp-password password socket --socketpath /var/run/gvmd.sock --xml "<get_tasks/>"
Step 2: Continuous Vulnerability Discovery
Schedule regular scans using automated tools and integrate results into a central repository.
Linux - Automating weekly vulnerability scans with cron 0 2 0 nuclei -l live_hosts.txt -severity critical,high -o /reports/nuclei_$(date +\%Y\%m\%d).txt
Step 3: Risk-Based Prioritisation
Develop a prioritisation matrix that considers asset criticality, vulnerability severity, and exploitability.
Python - Risk scoring function def calculate_risk_score(asset_criticality, cvss_score, exploit_available): base_score = asset_criticality (cvss_score / 10) if exploit_available: base_score = 1.5 return min(base_score, 10) Cap at 10
Step 4: Validation and Remediation Tracking
Use ticketing systems (Jira, ServiceNow) to track remediation progress and validate fixes.
Linux - Using Jira CLI to create remediation tickets jira issue create --project SEC --type Task --summary "Remediate CVE-2024-XXXX on asset X" --description "Vulnerability details..."
Step 5: Compliance Reporting
Generate audit-ready reports demonstrating continuous security testing and remediation.
Linux - Generating PDF reports from scan results nuclei -l live_hosts.txt -severity critical,high -report-json /reports/compliance_report.json Convert JSON to PDF using a reporting tool
What Undercode Say:
- Key Takeaway 1: The shift from periodic, point-in-time security assessments to continuous, integrated exposure management is not just a technological evolution—it is a strategic necessity. Organisations that fail to adopt continuous monitoring and testing will remain perpetually behind attackers who leverage automation and AI to discover vulnerabilities at scale. YesWeHack’s unified platform, combining crowdsourced intelligence with automated validation, represents a blueprint for how security teams can achieve proactive defence without overwhelming their resources.
-
Key Takeaway 2: AI is both a threat multiplier and a defensive enabler. While AI-powered tools accelerate vulnerability discovery and attack automation, they also introduce new and complex attack vectors that traditional testing methodologies cannot address. The most effective approach combines AI-assisted automation with human expertise—leveraging AI for scale and speed while relying on experienced security professionals for contextual validation and complex vulnerability discovery. YesWeHack’s “humans in the loop” model, with over 150,000 ethical hackers augmented by AI tools, demonstrates how organisations can achieve comprehensive security coverage across both traditional and AI-specific attack surfaces.
Prediction:
-
+1 The democratisation of offensive security through platforms like YesWeHack will accelerate over the next 3–5 years, with bug bounty and continuous pentesting becoming standard components of enterprise security programmes. As regulatory frameworks (DORA, NIS2, GDPR) increasingly mandate continuous security testing and compliance demonstration, organisations that have already adopted CTEM frameworks will gain significant competitive advantage.
-
+1 AI-powered autonomous pentesting will mature rapidly, enabling organisations to scale security testing across vast attack surfaces without proportional increases in headcount. However, the most effective programmes will maintain a hybrid model—automated scanners for broad coverage and human experts for deep, contextual vulnerability discovery and validation.
-
-1 The proliferation of AI-powered systems will create a “security debt” crisis similar to the technical debt accumulated during the early cloud migration era. Organisations that rush to deploy AI capabilities without corresponding security investment will face increasingly frequent and severe breaches, particularly through novel attack vectors like prompt injection, training data poisoning, and AI model manipulation.
-
-1 The cybersecurity skills gap will continue to widen, with demand for experienced security professionals far outstripping supply. This shortage will drive further automation and crowdsourcing adoption, but organisations that fail to invest in both technology and talent development will struggle to maintain effective security postures. Platforms that combine automated testing with access to global ethical hacker communities, such as YesWeHack’s ecosystem of 150,000+ researchers, will become essential for organisations of all sizes.
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