Artificial Intelligence in banking isn’t new, but its speed of deployment and regulatory scrutiny are unprecedented. Banks face a “bandwagon effect,” rushing AI initiatives while balancing risk management, governance, and consumer expectations. Key challenges like explainability and hallucinations require embedding AI into existing model risk frameworks, with strong controls, transparency, and incident readiness to safeguard compliance and trust.

Generative AI governance is complex, with multiple frameworks available to address security, risk, ethics, and compliance. Compare OWASP LLM Top 10, NIST AI RMF & 600-1, ISO/IEC 42001:2023, and CipherNorth’s Foundational Framework to find the right approach for your organization’s maturity and goals.

Not every organization is ready to implement a full AI governance program, but waiting to set guardrails can expose you to real risks like data leakage, misuse, and compliance gaps. At CipherNorth, we recommend a foundational framework, a streamlined set of policies, safeguards, and processes drawn from NIST, ISO, and other trusted sources, that gives organizations a secure starting point for using generative AI responsibly.

ISO/IEC 42001:2023 is an international standard for Artificial Intelligence Management Systems (AIMS), guiding organizations of all sizes to implement responsible AI governance, risk management, transparency, and continuous improvement. Certification demonstrates credible AI oversight, ethical practices, and regulatory alignment.

The NIST AI Risk Management Framework (AI RMF 1.0) offers organizations a structured approach to managing AI risk through four functions: Govern, Map, Measure, and Manage. NIST AI 600-1, released in 2024, extends this framework to the unique challenges of generative AI, addressing issues like hallucinations, copyright, bias, and misuse. Together, they provide a practical foundation for integrating AI governance into existing risk and security programs.

The Department of War’s new Cybersecurity Risk Management Construct (CSRMC) isn’t a revolution, it’s a reframing of existing ideas like continuous monitoring, automation, DevSecOps, and resilience. While the strategic direction is sound, CSRMC lacks the practical guidance such as control sets, telemetry standards, KPIs, and enforcement that operators and contractors need to act. Aligning CSRMC with well-established frameworks like NIST CSF, NIST SP 800-53, CMMC, and CIS Controls would turn vision into practice.

Deciding whether to pay a ransomware demand is never straightforward. While the FBI publicly discourages payment to reduce incentives for attackers, the real cost often comes down to downtime, restoration capability, and hidden expenses such as regulatory fines, litigation, and operational disruption. High-profile cases show that the business impact goes far beyond the ransom itself.

The OWASP Top 10 for Large Language Model (LLM) Applications highlights the most critical security risks in generative AI systems, from prompt injection to data leakage and misinformation. Updated in 2025, it provides organizations with a practical framework to identify vulnerabilities, strengthen application security, and build trust in LLM-powered tools.

Effective incident response (IR) goes beyond plans and playbooks. Learn how to embed IR into business-as-usual, leverage third-party support, run exercises, and continuously improve readiness to protect your organization, customers, and stakeholders.

Generative AI (GenAI) is moving from hype to practical adoption, transforming industries with tools like ChatGPT and Claude. But along with innovation come new risks, from data security and misinformation to compliance and third-party vulnerabilities. This article breaks down what GenAI is, outlines the unique challenges it creates, and explores frameworks like NIST’s AI RMF, ISO/IEC 42001, and OWASP’s LLM Top 10 that can help organizations innovate responsibly.

Salesforce wasn’t hacked, but if you used the Salesloft integration, your customer data could be at risk. This breach is a wake-up call: third-party vendor risk matters for every business, big or small.

One of the most overlooked aspects of incident response is reporting. It’s not flashy like forensics or containment, but it is the thread that runs through every stage of an incident and across every audience that matters, from your technical team to regulators and even the board. When reporting is handled poorly, even the best technical response can unravel into confusion, miscommunication, and costly regulatory fallout. When it’s done well, however, reporting builds trust, maintains alignment across the organization, and demonstrates competence to external stakeholders. That’s why defining cadences, practicing playbooks, and ensuring both organizational and personal reporting discipline is critical, not just for compliance, but for turning response into resilience.

AI hasn’t created new cyber risks - it’s accelerating existing ones. Learn why strong fundamentals and a well-practiced incident response plan matter more than chasing “AI-proof” products, and how CipherNorth helps build real resilience.

Executive reactions can make or break incident response. Learn how to manage roles, decisions, comms, and privilege for effective crisis leadership

Effective incident response needs more than tools. Learn how external partners, retainers, and clear coordination drive faster recovery and resilience.

Third-party vendors add value but also risk. Learn how to prepare for incidents with vendor visibility, data protection, and response coordination.

Continuing in our series on Incident Response, when an incident hits, speed matters. Not just how fast your team spots the problem—but how quickly you can act without creating more damage.

Every breach is unique, and the financial, operational, and reputational impact depends on countless nuanced factors.

SMBs have a hidden strength: smaller, less complex environments mean detection engineering can be focused and high-impact, without a massive budget or staff. The key is knowing which tools and telemetry sources deliver the biggest return on investment.

It’s clear, and the statistics clearly show this, that the size of a security team in an organization grows with the org. A cybersecurity breach doesn’t really care how much revenue a business has, and the response requirements are the same.