Claude Fable 5 reportedly went through 1,000 hours of red teaming before launch.
And still, within 48 hours of being public, someone claimed they found a way around its safeguards.
That should make every security leader pause.
Not because one model had an issue. That will happen.
The bigger concern is how the attack worked.
This was not just one clever jailbreak prompt.
It was closer to a “pack hunt.”
Multiple agents broke a risky request into smaller, harmless-looking pieces. Each piece looked safe on its own. The danger only appeared when the pieces were stitched back together.
That is the part enterprises need to understand.
Most AI guardrails still look at one prompt, one session, one user, or one model at a time.
But attackers are already thinking across sessions, across models, and across agents.
So the question is no longer:
“Did the model refuse the bad prompt?”
The better question is:
“Can we see the full chain of intent?”
This is why AI security needs to move beyond simple prompt filtering.
Enterprises need real guardrails around the entire AI workflow:
Input checks.
Output checks.
Data leakage controls.
Prompt injection protection.
Agent behavior monitoring.
Cross-session visibility.
Policy enforcement across the full AI pipeline.
That is also why solutions like Lakera AI, now part of
@CheckPointSW are becoming so important.
Safe AI adoption is not about slowing teams down.
It is about making sure AI can be used with confidence, without leaking sensitive data, violating policy, or letting harmful outputs slip through because each individual step looked harmless.
AI is powerful.
But before we hand it to every employee, customer, application, and autonomous agent, we need to harness it properly.
Single-prompt security is not enough anymore.
The future is full-pipeline AI security.
#AISecurity #CISO #Cybersecurity #GenAI #AgenticAI #LLMSecurity #CheckPoint #Lakera #AITrust