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Introduction
The cyber threat landscape has entered a dangerous new phase where frontier artificial intelligence models are fundamentally transforming both offensive and defensive capabilities. As CyberCX Director of Cyber Intelligence Leah Pinto prepares to address the 2026 Digital Future Summit alongside Australia’s Head of National Security, the message is clear: organisations can no longer afford reactive security postures when AI-driven threats evolve faster than traditional defences can adapt. With cyber extortion now the most common incident type and financially motivated attacks taking more than twice as long to detect—from 24 days in 2024 to 68 days in 2025—the urgency for proactive resilience has never been greater.
Learning Objectives
- Understand how frontier AI models are accelerating the speed, scale, and sophistication of cyber attacks, and why this demands a fundamental shift in defensive strategy
- Master the technical implementation of phishing-resistant multi-factor authentication and zero-trust architectures to counter adversary-in-the-middle session hijacking
- Apply practical Linux and Windows commands for system hardening, threat hunting, and compliance with Australia’s enhanced Critical Infrastructure Risk Management Program (CIRMP) Rules
You Should Know
- The Frontier AI Threat Multiplier: From Vulnerability Discovery to Exploitation in Hours
Frontier AI models such as Anthropic’s Claude Mythos have demonstrated the ability to identify significant zero-day vulnerabilities in major IT software globally, forcing vendors to scramble for patches before attackers can weaponise these findings. The European Systemic Risk Board warns that these models increase the speed, scale, and sophistication of cyberattacks, fundamentally reshaping the threat landscape for financial systems and critical infrastructure alike.
What makes frontier AI particularly dangerous is its accessibility. CyberCX’s 2026 Threat Report confirms that threat actors are now using generative AI to create custom, bespoke commands and malware, reducing the time between initial access and achieving malicious objectives. However, the more immediate risk may be internal: organisations are already responding to data spill incidents caused by employees uploading sensitive material to public-facing AI tools.
Step-by-step guide: Implementing AI-aware data loss prevention
- Audit AI tool usage across your organisation: Identify all public and private AI platforms employees are accessing. Use network monitoring to detect unusual API calls to AI services.
Linux command to detect outbound AI service connections:
sudo tcpdump -i any -1 'dst port 443' | grep -E '(openai|anthropic|claude|chatgpt|gemini)'
Windows PowerShell equivalent:
Get-1etTCPConnection | Where-Object {$_.RemotePort -eq 443} | Select-Object RemoteAddress, LocalAddress, State
- Deploy content inspection policies: Configure data loss prevention (DLP) tools to scan outgoing traffic for patterns matching sensitive data (e.g., credit card numbers, passport details, source code). Block uploads to unauthorised AI platforms.
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Establish an approved AI usage policy: Create a whitelist of vetted AI tools with contractual assurances about data handling. Require all employee AI interactions to go through a secure, monitored gateway.
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Implement real-time alerting: Set up SIEM rules to trigger alerts when sensitive data patterns are detected in outbound HTTP POST requests to AI API endpoints.
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Conduct regular employee training: Simulate phishing campaigns that mimic AI tool login pages to test awareness. Educate staff on the risks of pasting proprietary code or customer data into public AI chatbots.
2. Beyond MFA: Defeating Adversary-in-the-Middle Session Hijacking
One of the most alarming findings in the CyberCX Threat Report is that attackers are now routinely bypassing most multi-factor authentication solutions through adversary-in-the-middle (AITM) session hijacking. This technique steals the user’s session token rather than the credentials themselves, rendering traditional MFA ineffective. With Phishing-as-a-Service kits becoming cheap and widely available, this attack vector is accelerating rapidly.
The Australian government’s enhanced CIRMP Rules now explicitly require phishing-resistant multi-factor authentication for critical systems. This means moving beyond SMS-based or push-1otification MFA to FIDO2/WebAuthn security keys or certificate-based authentication.
Step-by-step guide: Implementing phishing-resistant MFA
- Audit existing MFA methods: Identify all systems using SMS, voice, or push-1otification-based MFA. These are vulnerable to AITM attacks.
Windows command to list Active Directory users with MFA status (using MSOnline module):
Get-MsolUser -All | Select-Object UserPrincipalName, StrongAuthenticationMethods
Linux command to check SSH key-based authentication (a form of certificate-based auth):
sudo grep -r "PubkeyAuthentication" /etc/ssh/sshd_config
- Deploy FIDO2 security keys: Enrol employees with hardware security keys (YubiKey, Google Titan, etc.) or platform authenticators (Windows Hello, Apple FaceID/TouchID).
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Configure conditional access policies: In Azure AD/Entra ID, create policies that require FIDO2 authentication for all privileged roles and sensitive applications.
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Disable legacy authentication protocols: Block IMAP, POP3, SMTP, and other legacy protocols that don’t support modern MFA.
Azure CLI command to disable legacy authentication:
az ad conditional-access policy create --1ame "Block Legacy Auth" --conditions ... --grant-controls builtin-controls=block
- Monitor for AITM attacks: Deploy session anomaly detection. Look for impossible travel scenarios—a user authenticating from Sydney and then immediately from Eastern Europe.
Splunk query for detecting AITM indicators:
index=authentication source=azure | stats count by user, city, country | where count > 1 AND city != previous_city
- Critical Infrastructure Hardening: Meeting Australia’s Enhanced CIRMP Requirements
The Australian Government has commenced the Enhanced Critical Infrastructure Risk Management Program Rules under the Security of Critical Infrastructure Act 2018, introducing targeted uplifts for energy, water, broadcasting, freight, and domain name system assets. These rules require entities to assess risks associated with legacy systems, artificial intelligence, and the connection between critical and non-critical systems.
With an additional $89.3 million invested under Horizon 2 of the Australian Cyber Security Strategy, organisations must now demonstrate compliance with established cybersecurity frameworks, implement phishing-resistant MFA, and segregate critical systems from non-critical systems.
Step-by-step guide: Critical infrastructure system segregation and hardening
- Map your critical assets: Identify all systems that support essential services. Classify them according to the SOCI Act asset classes.
Nmap command to discover network assets:
sudo nmap -sn 192.168.0.0/24 | grep "Nmap scan" | awk '{print $5}'
- Implement network segmentation: Use VLANs and firewalls to isolate critical systems from corporate and guest networks.
Linux iptables rule to restrict access to critical system (example: block all except specific management IP):
sudo iptables -A INPUT -p tcp --dport 22 -s 10.0.0.0/24 -j ACCEPT sudo iptables -A INPUT -p tcp --dport 22 -j DROP
Windows Firewall command to restrict RDP access:
New-1etFirewallRule -DisplayName "Restrict RDP" -Direction Inbound -Protocol TCP -LocalPort 3389 -RemoteAddress 192.168.1.0/24 -Action Allow
- Conduct legacy system risk assessments: Document all end-of-life systems. Develop remediation plans that include virtual patching, air-gapping, or migration.
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Establish continuous monitoring: Deploy intrusion detection systems (IDS) on critical network segments.
Deploying Suricata on Linux:
sudo apt-get install suricata sudo suricata -c /etc/suricata/suricata.yaml -i eth0
- Prepare for compliance audits: Maintain evidence of risk assessments, patch management cycles, and incident response exercises. Document all third-party supply chain assessments.
4. Threat Hunting for Nation-State Covert Networks
Chinese and Russian nation-state actors have been identified compromising small office/home office routers and IoT devices globally to create covert infrastructure networks. Nodes have been identified in Australia and New Zealand, presenting a serious threat through DNS hijacking and adversary-in-the-middle attacks while obfuscating attribution.
Organisations should map and baseline their edge devices to identify malicious tradecraft. The Australian Cyber Security Centre, alongside 15 partner agencies, has issued guidance on defending against these covert networks.
Step-by-step guide: Router and IoT device threat hunting
- Inventory all edge devices: Document every router, switch, firewall, and IoT device on your network. Include model, firmware version, and configuration.
Linux command to discover network devices using ARP scanning:
sudo arp-scan --localnet
- Baseline normal behaviour: Capture typical DNS query patterns, outbound connection destinations, and administrative login times.
Linux command to monitor DNS queries:
sudo tcpdump -i any -1 port 53 | grep -v "response"
- Check for unauthorised DNS changes: Compare current DNS settings against known-good configurations.
Linux command to check DNS resolver settings:
cat /etc/resolv.conf nmcli dev show | grep DNS
- Review administrative access logs: Look for logins from unusual IP addresses or at odd hours.
Linux command to check recent SSH logins:
sudo last | head -20 sudo grep "sshd" /var/log/auth.log | tail -50
Windows PowerShell to check RDP logins:
Get-WinEvent -LogName Security | Where-Object {$<em>.ID -eq 4624 -and $</em>.Message -match "Network"} | Select-Object TimeCreated, Message
- Apply vendor security patches: Update all router and IoT firmware to latest versions. Disable remote management interfaces where not required.
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Implement DNS monitoring: Use tools like SecurityTrails or OpenDNS to detect DNS hijacking attempts. Configure alerts for DNS query anomalies.
5. Open-Source Software Supply Chain Security
Financially motivated and nation-state threat actors are increasingly compromising open-source software supply chains to introduce information stealers and remote access trojans. JavaScript libraries and npm packages are particularly targeted. Organisations must scrutinise their own critical infrastructure and defence pipelines while gaining visibility into upstream dependencies used by third parties.
Step-by-step guide: Securing your software supply chain
- Inventory all open-source dependencies: Use software composition analysis (SCA) tools.
Node.js command to list npm dependencies:
npm list --depth=5
Python command to list pip dependencies:
pip freeze
- Scan for known vulnerabilities: Use tools like OWASP Dependency-Check, Snyk, or Trivy.
Running OWASP Dependency-Check:
dependency-check --project "MyApp" --scan ./src --format HTML
- Implement dependency pinning: Lock dependency versions to prevent automatic updates to compromised packages.
For npm:
npm shrinkwrap
For Python:
pip freeze > requirements.txt
- Monitor for malicious package updates: Use tools like Socket or npm audit to detect suspicious package behaviour.
npm audit command:
npm audit --audit-level=high
- Establish a software bill of materials (SBOM): Generate and maintain an SBOM for all applications. This is becoming a regulatory requirement globally.
Using Syft to generate SBOM:
syft dir:. -o spdx-json > sbom.json
- Vet third-party vendors: Require all suppliers to provide SBOMs and evidence of their own supply chain security practices.
What Undercode Say:
- AI is both sword and shield: While frontier AI models supercharge offensive capabilities—automating vulnerability discovery and malware generation—they also enable defensive innovations like autonomous threat detection and predictive analytics. The organisations that thrive will be those that deploy AI defensively before attackers weaponise it against them.
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Compliance is the floor, not the ceiling: Australia’s enhanced CIRMP Rules and Horizon 2 strategy establish a baseline, but true resilience demands going beyond regulatory checkboxes. Proactive threat hunting, continuous monitoring, and a culture of security awareness are non-1egotiable in an era where detection times are stretching to 68 days.
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The human firewall remains critical: Despite all technological advances, the most common initial access technique remains valid accounts and compromised credentials sourced from information stealers and social engineering. Investing in employee education, phishing-resistant MFA, and privileged access management yields the highest return on security investment.
Prediction:
-P The gap between AI-powered offensive and defensive capabilities will narrow by 2027, as defensive AI tools become more sophisticated and widely adopted. Organisations that invest early in AI-driven security operations centres (SOCs) will gain a significant competitive advantage.
-1 The proliferation of Phishing-as-a-Service kits and AI-generated social engineering will drive a wave of credential theft and session hijacking attacks in the second half of 2026, particularly targeting financial services and critical infrastructure sectors.
-P Australia’s investment of $89.3 million in Horizon 2 initiatives, combined with enhanced CIRMP enforcement, will create a more resilient critical infrastructure ecosystem by 2028, potentially making Australia a global benchmark for cybersecurity regulation.
-1 The increasing use of public AI tools by employees will continue to cause data spill incidents, with regulatory penalties and reputational damage becoming significant business risks through 2027.
-P The shift from reactive cybersecurity to proactive resilience, as forecasted by industry analysts, will accelerate as organisations recognise that traditional perimeter-based defences are obsolete against AI-driven threats.
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