AI-ready cyber resilience: 10 actions to take now
AI has changed the economics of cyber risk: attackers can find and weaponize vulnerabilities faster than most organizations can change their systems. The answer to that is not a shiny new tool. It is ten unglamorous fundamentals, executed with urgency, plus security built into how AI itself gets developed and deployed.
The ten actions below come from a framework published earlier this year by the technology leadership of a large global bank. This post is my summary of it, organized into four themes, with a few diagrams to make the ideas stick.
// infographic · 10 actions at a glance
know & fix
You cannot defend what you cannot see or have not patched.
prepare & move fast
Assume the bad day comes; make recovery and patching routine.
contain the blast radius
When something gets in, make sure it cannot go far.
build ai in safely
Treat AI systems as production systems with new attack surface.
Why now: the window is shrinking
The core argument is about time. AI helps attackers scale their operations and, more importantly, shortens the gap between a vulnerability being discovered and a working exploit being used against it. Meanwhile, the defender’s patch cycle — triage, test, approve, deploy — often runs longer than the organization’s real capacity for change.
The difference between those two clocks is your exposure window.
// infographic · the exposure window
Illustration: AI-assisted attackers turn a disclosed vulnerability into a working exploit much faster than before, while the defender's triage, test, approve and deploy pipeline is unchanged. The gap between the two is the exposure window.
// shrink it from both ends
The article’s framing for closing that window is a phrase I like a lot: make sure the easy path is the safe path for technology teams. Resilience comes from urgency, disciplined fundamentals, explicit decisions about which systems to modernize, contain, or exit, and security that is built into automated delivery rather than bolted on at the end.
Know & fix
01 — Run the latest software versions
Technical debt is treated as a security problem with senior oversight, not a backlog item. Replace hardware before end of life, move off unsupported operating systems and enterprise software, keep open-source dependencies current and validated, and pull open source from managed, trusted repositories rather than straight from the internet.
02 — Manage assets and components with reference data
Keep a continuously updated inventory of hardware, software and cloud assets — shadow IT included. Use SBOMs for applications, enrich every record with an owner and a criticality rating, and reconcile the inventory against discovery scanning so it does not quietly drift from reality. Everything else on this list depends on this one: you cannot prioritize, patch or contain what you do not know you have.
03 — Run a real vulnerability management program
Fix known vulnerabilities by criticality, starting with internet-facing systems. Test patches before production, set SLAs by severity, scan continuously inside delivery pipelines, and prioritize with context and threat intelligence such as CISA’s Known Exploited Vulnerabilities (KEV) catalog. While a fix is pending, lean on perimeter controls like a WAF, and report aging vulnerabilities and exceptions to leadership.
// infographic · what to patch first
while the fix is pending: WAF rules / virtual patching at the perimeter, a documented exception with an owner and an expiry, and aging reported upward.
Prepare & move fast
04 — Stress-test incident response and resiliency plans
Run tabletop exercises and live simulations for ransomware, destructive attacks and supply-chain compromise. Prove backups with full restoration tests, not just “the job succeeded” alerts. Bring business leaders and third parties into the room, and track every finding from every exercise to closure.
05 — Know your major SaaS and outsourced dependencies
Maintain a current register of critical providers and share that dependency data across teams. Assess each provider’s security and resilience, write notification, audit-rights and recovery-objective requirements into contracts, and build contingency and exit plans before you need them.
06 — Optimize change management for speed
Map the full lifecycle of a security patch and remove the delays that do not add safety. Invest in automated testing, staged rollouts and fast rollback. Create an emergency change path that is quick but still auditable, and track mean-time-to-patch as a headline metric. This is the action that most directly shrinks the defender’s side of the exposure window.
Contain the blast radius
The next three actions assume something will eventually get in, and make sure it cannot go far once it does.
// infographic · containing the blast radius
07 — Aggressively filter outbound traffic from production
Production systems should run default-deny, allow-listed egress. Broad internet access is an exception that has to be justified. Monitor for anomalous outbound traffic, keep end-user environments separate from production, and test the rules regularly. The article notes this single control would have substantially blunted incidents like Log4Shell and SolarWinds, where the compromise depended on a callback to attacker infrastructure.
It is the network-layer version of an argument I made about endpoints in allowlisting before EDR: decide what is allowed up front, and the predictable attacks have nowhere to go.
08 — Remove standing privileges
Use privileged access management with vaulted credentials and just-in-time elevation. Eliminate persistent admin accounts, require MFA and session recording for privileged work, audit entitlements regularly — and apply the same discipline to service and machine accounts, which are easy to forget and attractive to steal.
09 — Manage remote access and segment where possible
Require strong MFA for remote access and only allow trusted, verified devices. Segment environments with different trust levels, authenticate every internal connection, design so that a single compromise is contained, and validate the controls with red teaming and penetration testing rather than assuming the diagram matches the network.
Build AI in safely
10 — Embed security into the AI lifecycle
The last action turns from defending against AI-accelerated attackers to securing your own AI. Threat-model AI systems early. Protect models, training data and inference pipelines with access controls and audit logging. Review AI-generated code to the same standard as human-written code. Assess third-party AI services like any other supplier, red-team AI systems for prompt injection and data poisoning — and use AI on the defensive side too.
My take
What stands out is how little of this list is new. Patching, inventory, least privilege, segmentation, egress filtering, rehearsed recovery — none of it would look out of place in a security roadmap from ten years ago. The difference is the clock. When the time from disclosure to exploit shrinks, fundamentals that were “important” become the actual determinant of whether you are breached.
If I had to pick where to start, it would be the pair that compounds: 02 (inventory) makes every other action faster and more accurate, and 07 (default-deny egress) buys you protection during the window you have not closed yet.