Framework Security

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.

Agentic Design & Building Production Tooling - Mar 26, 2026 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...

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

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