Framework Security

06/09/2026

One of the first questions organizations ask when evaluating AI solutions is simple: "What happens to my data?"

Zero Data Retention (ZDR) provides a straightforward answer: your data is processed to generate a response and is not retained afterward.

As AI adoption continues to grow, understanding how vendors handle data privacy, retention, and model training is becoming increasingly important.

Our latest blog explores what Zero Data Retention means, how it works, and why it matters for organizations handling sensitive information.

Zero Data Retention Answers the Easy Question

06/08/2026

If your cyber insurance renewal was tomorrow, would you be confident in your answers?

Insurers are asking tougher questions than ever before, and many of those questions reveal the same security gaps attackers are looking for. Our latest blog breaks down the seven controls underwriters are prioritizing in 2026.

Learn the seven security controls cyber insurers expect in 2026 and how strengthening them can reduce risk, improve resilience, and support renewals.

05/18/2026

CMMC Level 2 readiness is no longer a “future problem” for defense contractors.

In 2026, organizations across the Defense Industrial Base are facing increasing pressure to operationalize cybersecurity controls, document evidence properly, and prepare for third-party assessments tied to DoD contract eligibility.

The biggest challenge we continue to see? Companies often underestimate the operational and documentation maturity required to successfully achieve and maintain compliance.

We put together a practical guide covering:
✔️ CMMC Level 2 requirements
✔️ Assessment expectations
✔️ Common compliance gaps
✔️ Documentation and evidence preparation
✔️ Implementation considerations for 2026

Read the full guide here: https://frameworksecurity.com/post/the-complete-guide-to-cmmc-level-2-certification-in-2026

CMMC compliance helps defense contractors meet DoD cybersecurity requirements by aligning with NIST standards, and Framework Security simplifies the process by providing continuous monitoring, risk visibility, and automated compliance support.

05/14/2026

Most boards are asking the wrong AI question in 2026.

Not: “Are we using AI?”
But: “Do we actually understand the risks we’ve already introduced?”

AI risk is no longer theoretical. It’s operational.

Shadow AI, agentic workflows, prompt injection, third-party model dependencies, data leakage, compliance exposure, reputational damage - these are now board-level concerns, not just IT issues. Recent guidance from NIST and enterprise governance leaders shows that AI risk management is quickly becoming a core business discipline, not an optional security exercise.

What many organizations still miss:

✅ AI governance is not about blocking tools
✅ Traditional cyber risk frameworks are often insufficient
✅ The real challenge is visibility, accountability, and ongoing assessment

See Framework Security's take on what boards should actually be asking in 2026. https://frameworksecurity.com/post/ai-risk-assessments-what-your-board-needs-to-know-in-2026

AI risk assessments use artificial intelligence to automatically identify, evaluate, and prioritize security, compliance, and operational risks so organizations can address the most critical issues faster.

04/14/2026

Many agentic AI concepts perform well in controlled demos, but translating them into reliable production systems introduces a different set of challenges.

At Framework Security, we recently shared our perspective on what it takes to build agentic systems that operate effectively in real-world environments:

https://frameworksecurity.com/post/agentic-design-building-production-tooling

Key considerations:

• Context management is a design constraint, not an afterthought
• System architecture often drives outcomes more than model selection
• Structured inputs, outputs, and tool interactions are critical for consistency
• Reliability comes from disciplined orchestration, not emergent behavior

As organizations continue to operationalize AI, success will depend less on experimentation and more on engineering rigor.

The FWS ATLAS TTPs Mapping provides a systematic operationalization of the MITRE ATLAS adversarial threat framework for applied AI/ML security assessments. Each technique is mapped to current open-source and commercial tooling with documented procedures, addressing a recognized gap between threat mo...

04/13/2026

A recent report highlights a significant shift in how vulnerabilities are being discovered. Anthropic’s latest research indicates that AI systems can identify thousands of previously unknown (zero-day) vulnerabilities across major operating systems and browsers, with a reported 72% exploit success rate.

This is not just an incremental improvement in tooling, it represents a step change in capability.

At this scale, vulnerability discovery is no longer constrained by human bandwidth. AI can continuously analyze complex codebases, identify weaknesses, and validate exploitability at a pace that materially compresses the timeline between discovery and risk exposure.

For security teams, this raises important considerations:
• The window between vulnerability discovery and exploitation is shrinking
• Traditional patching cycles may no longer be sufficient on their own
• Greater emphasis is needed on detection, response, and runtime protections

While this research demonstrates the defensive potential of AI, it also underscores how quickly these capabilities could be leveraged offensively.
Security strategies will need to evolve accordingly, prioritizing resilience, visibility, and speed.

📄 Full report: https://lnkd.in/gQ4CEYtr

This link will take you to a page that’s not on LinkedIn

01/27/2026

The Crunchbase breach isn’t just another headline — it’s a case study in modern cyber risk.

Identity, access, and visibility failures continue to cause real business impact long before “advanced exploits” ever matter.

What leaders should actually take away →
https://frameworksecurity.com/post/what-the-crunchbase-breach-reveals-about-modern-cyber-risk

In January 2026, Crunchbase confirmed a data breach after stolen files were posted online by a known threat actor. For a company whose business is built on trusted business intelligence, the incident landed hard — not because it was unusual, but because it followed a familiar pattern that many org...

01/20/2026

Most organizations are racing to adopt AI.
Very few are securing it.

AI introduces new data paths, new decision risks, and new ways to fail at scale. Treating AI risk as “someone else’s problem” is no longer an option.

Read our latest blog: AI Risk Is Now a Cybersecurity Problem.

https://frameworksecurity.com/post/ai-risk-is-now-a-cybersecurity-problem

Artificial intelligence is no longer experimental. It’s embedded in core business processes—security operations, customer support, analytics, development, and decision-making. And as AI adoption accelerates, so does the reality most organizations are only beginning to confront:

01/14/2026

Security programs don’t usually fail because teams did something wrong. They fail because the business outgrew the assumptions they were built on.

January is when this gap becomes obvious—budgets reset, strategies shift, AI adoption accelerates.

We put our thinking into this piece 👇

https://frameworksecurity.com/post/your-security-program-didnt-break----the-business-changed