KNC Inc. Introduces Cyber-Assessment Program to Fight AI-Driven Crime

KNC Inc. has launched a cyber assessment program designed to help financial institutions combat the rising threat of AI-driven financial crime. This proactive solution tests systems against synthetic adversaries, enabling organizations to strengthen their defenses and stay ahead of emerging AI-enabled criminal tactics.

United States, 3rd Dec 2025 – In September 2025, Anthropic revealed what may be the first major cyber-espionage campaign executed primarily by an AI agent—a China-linked operation that used Anthropic’s own tools to probe and infiltrate high-value organizations, including financial institutions and government agencies.

For leaders working in AML, fraud, cyber, compliance, and financial crime intelligence, this incident marks the beginning of a profound shift.
We are entering the era where AI-driven synthetic adversaries will attack financial systems faster—and more intelligently—than any human threat actor ever could.

Here’s what happened, what it means for the financial sector, and why AI red teaming is rapidly becoming a mandatory part of AML and cybersecurity strategy.

The Attack: AI Performed 80–90% of the Intrusion Work

According to Anthropic:

• A state-linked group used Claude and “Claude Code,” an autonomous coding system, to perform most of the attack’s technical workload.
• Roughly 30 global organizations were targeted across the financial, governmental, and technology sectors.
• The attackers bypassed guardrails by posing as a legitimate cybersecurity firm and splitting malicious tasks into micro-steps that looked harmless.
• Only a small number of intrusions succeeded—but the methodology is what alarms experts.

Some researchers argue this was “highly automated hacking,” not fully autonomous AI—but that distinction no longer provides comfort.

The takeaway: AI can already execute complex criminal workflows at machine speed.

Why This Matters for AML and Cybersecurity

This is the first real-world demonstration of what many in the risk community have been anticipating:

AI will soon be able to test a financial institution’s controls before a real criminal ever touches them.

This has unprecedented implications:

1. AI can generate AML-evading transaction flows

An adversarial AI doesn’t probe your system the way a human criminal would—it attacks everything at once. It can test structuring thresholds, exploit typology blind spots, map high-risk corridors, track model drift, and probe cross-border routing weaknesses in a continuous loop. No pauses. No fatigue. It simply iterates, thousands of times per second, until something gives. And the truth is uncomfortable: your monitoring system was never built for that kind of pressure.

2. Guardrail bypassing will be weaponized against banks’ own AI tools

The tactics used to slip past Claude’s safety rules don’t stay in the AI lab—they translate directly into real-world financial crime. The same methods can undermine KYC and KYB onboarding, fool document-verification systems, and imitate behavioural biometrics with unsettling accuracy. They can probe fraud models for weak spots, distort SAR triage automation, and quietly manipulate inference-based AML engines. What worked against an AI assistant can work just as easily against a bank.

If an AI can “mislead” another AI, traditional model validations are no longer enough.

3. Synthetic identities and forged documentation become infinitely scalable

AI can now produce realistic IDs, fabricate corporate documents, and assemble entire clusters of synthetic customers with almost no effort. It can pass liveness checks using deepfakes and generate behaviour patterns that look perfectly clean on paper. What used to take criminal networks time and coordination now happens instantly. This isn’t just scaling fraud and money laundering—it’s industrializing it.

4. Cyber – Fraud – AML becomes a single chain of attack

AI adversaries don’t think in silos. They move through systems as one continuous chain—cyber intrusion, account compromise, fraudulent transfers, laundering, and finally crypto-mixing or off-ramping. Each step feeds the next. And because the attack path is unified, the defense has to be as well. AML, fraud, and cyber can’t afford to act like separate teams anymore; the threat won’t treat them that way.

5. Regulators will soon mandate AI red teaming

Given the geopolitical nature of the Anthropic incident, regulators are expected to require:

• AI red teaming for AML and cyber
• governance frameworks for AI-driven controls
• synthetic identity resistance testing
• vendor and supply-chain AI risk reviews
• cross-border reporting for AI-enabled crimes

This mirrors how cyber standards like SOC2 and PCI DSS emerged—but for financial crime controls.

Synthetic Adversaries Are the New Criminal Class

The threat is not theoretical.
Synthetic adversaries:

• never fatigue
• never reuse the same pattern
• never stop testing controls
• learn instantly from failure
• mimic legitimate customers
• adapt faster than human investigators

If your controls haven’t been tested against AI adversaries, they haven’t been tested at all.

If you don’t let synthetic adversaries attack your controls, real criminals will.

What FSIs Must Do Now

Financial institutions now need to treat AI the same way criminals do—by turning it against their own systems before anyone else does. That starts with AI Red Teaming, using synthetic adversaries to pressure-test onboarding, transaction monitoring, fraud models, APIs, SAR workflows, and authentication layers. Traditional penetration tests can’t touch this level of precision. At the same time, institutions must learn to recognize and resist guardrail bypassing—the fragmented prompts, behavioural mimicry, iterative probing, and synthetic identities that AI attackers will use to slip past controls. AML, fraud, and cyber teams can no longer operate in separate lanes; AI-enabled threats cut across all three, and your intelligence functions need to mirror that convergence. Incident response plans also need a rewrite, because most playbooks assume human timing and human error—and AI adversaries obey neither. And finally, this battle can’t be fought alone. Coordination with regulators, intelligence agencies, and industry peers is now essential, because AI-enabled financial crime isn’t just a compliance headache—it’s a growing national-security concern.

About KNC Inc.

KNC Inc. is a Toronto-based boutique firm specializing in AML intelligence, cyber-enabled financial crime, and asset tracing across North America and the Caribbean.

Founded in 2024, KNC quickly earned recognition after helping disrupt drug trafficking-linked money-laundering networks operating across Canada, the U.S., and the Caribbean—working alongside agencies such as the BPS, CBSA, and other regional law enforcement.

What sets KNC apart is the agility of a specialized team with the operational depth of a major task force. Their cyber assessment program allows financial institutions to proactively test AML, fraud, and cyber defenses against synthetic adversaries—the next generation of AI-enabled criminal threats. 

KNC’s mission is simple – Give institutions the intelligence and technology they need to stay ahead of emerging financial crime.

Learn more at www.knconsulting.ca or connect with Kalvin Nhan on LinkedIn.
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KNC Inc. Introduces Cyber-Assessment Program to Fight AI-Driven Crime

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