Trade vs Cybersecurity: How AI Keeps You Safer

A single nation-state campaign can now ripple across hundreds of organizations and dozens of countries—and it doesn’t need missiles or troops to do it. The Salt Typhoon telecom intrusions are a blunt reminder: when attackers sit inside carrier networks, they’re not just stealing data. They’re gaining vantage points into everything that depends on telecom infrastructure—identity flows, SMS-based MFA, remote access paths, and the “out-of-band” channels incident responders count on when things go sideways.

Now add a second reality: governments regularly treat cyber sanctions and export controls as bargaining chips in broader trade negotiations. That’s not shocking. It’s how diplomacy works. The problem is what it communicates to adversaries and what it tempts organizations to do: wait for policy to protect them.

For this AI in Defense & National Security series, I’m taking a stance: if trade policy and cybersecurity policy aren’t coordinated, enterprises and agencies must assume the gap will be filled by attackers. The practical answer isn’t more press releases—it’s deterrence by denial, backed by AI-enabled operations that reduce dwell time, expose abnormal behavior faster, and harden supply chains that sanctions can’t realistically secure.

When trade priorities reshape cyber posture

Answer first: When cyber actions (sanctions, export controls, regulatory pressure) get folded into trade talks, security becomes negotiable—while adversaries keep operating as if nothing changed.

The core tension is simple: trade negotiators optimize for economic outcomes on a deadline; cybersecurity teams optimize for risk reduction on an always-on battlefield. When the two collide, cyber policy can look inconsistent—even if the intent is to “buy” cooperation on other priorities.

From an enterprise perspective, this matters for two reasons:

1. Signals drive attacker behavior. If punitive measures appear reversible, adversaries learn that persistence pays.
2. Regulatory whiplash creates uneven defenses. If cybersecurity requirements for critical sectors (like telecom) are tightened and then relaxed, the weakest links become predictable targets.

There’s also a subtle operational cost: security leaders waste cycles trying to interpret geopolitical intent instead of instrumenting controls that make intrusion expensive and noisy.

The myth: “Sanctions will stop the next intrusion”

Sanctions can raise costs, embarrass agencies, and constrain individuals. What they don’t reliably do is prevent intrusion in the first place—especially when the mission is strategic intelligence collection.

I’ve found that many executive teams still treat geopolitical actions like a perimeter control: “Surely, that will deter them.” It won’t. Nation-state operators plan in years, not quarters. They’ll route around financial pressure and keep going.

A better mental model: sanctions are a foreign policy tool; your security program is your defense system. Confusing the two leads to underinvestment in detection, identity security, and supply chain assurance.

Salt Typhoon is a telecom story—and a national security lesson

Answer first: Telecom compromises are uniquely dangerous because they create downstream access to identity, recovery channels, and critical communications—exactly what defenders rely on during crises.

The Salt Typhoon intrusions started with telecoms and ISPs and expanded into a broad set of victims globally. That pattern should ring bells for anyone responsible for national resilience, critical infrastructure, or continuity of operations.

Here’s why telecom footholds are so valuable:

• Identity interception: If attackers can observe or manipulate traffic flows, they can target MFA mechanisms and account recovery processes.
• High-trust adjacency: Carriers connect to cloud providers, government networks, emergency services, and enterprise WAN edges.
• Operational disruption potential: Even without “blowing things up,” disrupting routing, DNS, or signaling systems creates chaos.

For defense and national security leaders, the takeaway isn’t “telecoms should do better.” It’s: critical infrastructure compromises are shared-risk events. Your organization’s security depends on vendors, carriers, and upstream providers you don’t control.

Why deterrence by denial is the only stable strategy

Deterrence by denial means making intrusion hard to achieve and harder to maintain—so the attacker’s ROI collapses. In practice, it’s built from three pillars:

1. Hardening: reduce exploitable surface area and enforce secure baselines.
2. Instrumentation: increase visibility so attackers can’t hide.
3. Governance: ensure controls are sustained, audited, and tied to business outcomes.

This is where AI can actually earn its keep—because denial at scale requires speed, correlation, and consistency that humans alone can’t maintain 24/7.

Where AI fits: bridging trade-security gaps with faster denial

Answer first: AI helps most when policy is inconsistent because it makes detection and response less dependent on perfect coordination—and more dependent on measurable signals.

When trade and cybersecurity policies drift, organizations still need a reliable operating model. AI can provide that model by continuously monitoring for the tactics nation-state groups use: lateral movement, credential abuse, covert persistence, and “living off the land” activity.

But let’s be blunt: AI isn’t a magic shield. The win comes from applying AI to specific security choke points where adversaries must reveal themselves.

1) AI for telecom-adjacent anomaly detection

Carrier and network-adjacent telemetry is noisy, high-volume, and time-sensitive—ideal territory for machine learning when it’s properly governed.

Use cases that consistently pay off:

• Behavioral baselining for service accounts and network devices (routers, firewalls, VPN concentrators)
• Sequence detection for multi-step intrusion chains (initial access → privilege escalation → new tunnels → data staging)
• Cross-domain correlation between identity logs, endpoint events, and network flows

The practical goal: reduce time-to-suspicion. If your SOC can move from “weird” to “confirmed” in minutes instead of days, you’ve raised the cost of staying inside.

2) AI for supply chain risk scoring that sanctions can’t cover

“You can’t sanction your way out of a supply chain compromise” is a line worth repeating because it’s operationally true.

AI can help by continuously scoring supplier and software risk based on:

• vulnerability exposure and patch cadence
• software composition (known risky dependencies)
• anomalous update patterns (unexpected build changes, unusual signing events)
• operational signals (suspicious outbound traffic from vendor-managed systems)

This is especially relevant for agencies and defense contractors working under frameworks like CMMC 2.0 expectations. Compliance checklists help, but continuous verification is what catches real intrusions.

3) AI copilots for analysts—when you lock them down

LLM-style copilots can speed triage and investigations:

• summarizing an incident timeline from heterogeneous logs
• translating detection logic across SIEM/query languages
• drafting containment steps tied to your playbooks

The security catch: copilots must run inside strong guardrails—access controls, data handling policies, prompt/response logging, and red-team testing against prompt injection. Otherwise, you’re adding a new attack surface.

A coordination playbook: what leaders should do in Q1 2026

Answer first: Treat geopolitics as a volatility driver, then build AI-enabled controls that keep working even when policy shifts.

December is when many teams lock budgets and reset operating rhythms. Use that timing. Here’s a pragmatic plan that works whether you’re in government, critical infrastructure, or a regulated enterprise.

Step 1: Map your “trade-exposed” attack surface

You’re trade-exposed if you rely on:

• foreign-made hardware/firmware in network paths
• globally distributed suppliers and integrators
• export-controlled compute (AI chips, accelerators) in your stack
• telecom providers for identity, recovery, and out-of-band comms

Deliverable: a one-page map of systems where geopolitics can change your risk profile (availability, patch access, vendor support, replacement lead time).

Step 2: Put AI where it measurably shrinks dwell time

Pick two metrics and defend them:

• MTTD (mean time to detect) for identity abuse and lateral movement
• MTTR (mean time to respond) for privilege escalation and persistence

Then deploy AI capabilities only where they move those metrics. If the tool can’t prove impact within 60–90 days, cut it.

Step 3: Build “deterrence by denial” into identity, not just endpoints

Nation-state operators love credentials because credentials blend in.

Priorities that reduce their advantage:

• phishing-resistant MFA for privileged roles
• conditional access tied to device posture
• continuous session risk scoring (impossible travel, abnormal token use)
• rapid credential invalidation workflows

AI helps by identifying subtle identity anomalies—but you still need the authority to act on them quickly.

Step 4: Prepare for telecom disruption like it’s a fire drill

If your incident response plan assumes SMS works, assume it fails.

Do the boring work:

• alternate MFA methods for admins
• offline recovery codes stored securely
• secondary comms channels for IR coordination
• tabletop exercises that simulate carrier compromise

AI can support these exercises by generating realistic adversary timelines and testing alert coverage against those sequences.

“People also ask” (and straight answers)

Are sanctions useless for cybersecurity?

No. They can constrain individuals and signal norms. But they are not a reliable control for preventing intrusion. Build defenses as if sanctions change nothing.

Does AI actually stop nation-state attackers?

AI doesn’t “stop” attackers by itself. It compresses the time window attackers need to succeed by improving detection, correlation, and response consistency.

What’s the biggest AI risk in security operations?

Overtrust. If teams treat AI outputs as facts without verification, they’ll miss stealthy activity—or automate the wrong containment action. AI should be a force multiplier, not the decision-maker of record.

The real test: can you defend even when policy wobbles?

Trade negotiations will keep colliding with cybersecurity priorities. That’s not a partisan statement—it’s a structural one. Economic policy moves fast, threat actors move faster, and defenders are stuck operating critical systems that can’t be “paused” until diplomacy settles.

If you’re leading security in government, defense, telecom, or any enterprise that depends on them, the winning posture is clear: assume cyber activity continues, then invest in deterrence by denial. AI belongs in that plan when it shortens detection and response cycles, strengthens supply chain visibility, and helps humans make faster, higher-confidence decisions.

If your organization had to operate through a major telecom compromise next week, what would break first—identity, communications, or visibility? That answer tells you exactly where to start.