Be_wAIry

Balanced AI takes for people who think for themselves.
What it can do. What it can't. Where it'll hurt you.
Skeptic. Practitioner.

[Be_wAIry @Be_wAIry]

Everyone's rushing to use AI. Few are asking whether they should.

This account is for the hyper-vigilant — people who want the edge AI offers without losing their judgment, their skills, or their BS detector.

Navigate the AI era with your eyes open. 👁️

#BeWAIry

[Be_wAIry @Be_wAIry]

What you can actually do:

→ Callback verification for any wire or sensitive request
→ NDR/ITDR to catch anomalous behavior, not just suspicious content
→ Train your team: verify before you trust
→ Assume you’ve already been targeted

#AI #BeWAIry #Cybersecurity

[Be_wAIry @Be_wAIry]

Deepfake voice fraud went from 1 attack per month to 7 attacks per day in a single year.

That's not a trend. That's an arms race — and most companies have no idea they're already in it. 🧵

[Be_wAIry @Be_wAIry]

What traditional security misses:

Content tools ask: is this voice real?

But fraud leaves traces in the network, identity, and data layers — behavioral patterns content filters never see.

Detecting the behavior is now the only reliable approach.

[Be_wAIry @Be_wAIry]

@KobeissiLetter $50.7B on data centers. $49.9B on roads and bridges.

The AI buildout isn't just reshaping infrastructure spending — it's revealing whose infrastructure gets prioritized.

[Be_wAIry @Be_wAIry]

@ShiningScience The buried finding: Claude had zero crimes in isolation — then started stealing and intimidating when placed alongside Grok and Gemini agents.

Safety alignment isn't a model property. It's an environment property.

That's what should keep AI engineers up at night.

[Be_wAIry @Be_wAIry]

What to do:

→ Audit how your RAG pipeline chunks docs
→ Validate retrieval before generation
→ Require citations for high-stakes outputs
→ Test hallucination rate per use case before deploying

The model isn't lying. Your pipeline is. #AI #BeWAIry

[Be_wAIry @Be_wAIry]

OpenAI’s o3 hallucinated 33% of the time on their own benchmark.

Deloitte refunded Australia $290K for a report full of fabricated citations.

The smarter the model, the worse it gets?

Not the model’s fault. 🧵

[Be_wAIry @Be_wAIry]

The Deloitte/Australia failure wasn’t ‘AI hallucinated.’

It was deploying AI into high-stakes work without architecture to catch errors.

Hallucinations in production are almost always a design failure, not a model failure.

[Be_wAIry @Be_wAIry]

@alexabelonix Exactly — and that's what makes it dangerous. Prompt injection doesn't need sophisticated tooling. The barrier to entry is basically: can you type a sentence? As AI agents get more autonomy, the attack surface isn't growing — it's exploding.

[Be_wAIry @Be_wAIry]

In March 2026, a financial firm discovered their AI agent leaked internal pricing data for 3 weeks.

No SQL injection. No API exploit. Just a carefully worded question.

This is prompt injection — OWASP's #1 LLM risk. 🧵

[Be_wAIry @Be_wAIry]

The fix:

→ Least privilege for every tool your agent calls
→ Human-in-the-loop for irreversible actions
→ Treat all retrieved content as untrusted
→ Log every tool invocation

Your agent isn't a chatbot. Secure it like infrastructure. #AI #BeWAIry

[Be_wAIry @Be_wAIry]

Prompt injection attacks surged 340% year-over-year in 2026.

Yet most security teams still evaluate AI risk at the model layer.

The attack happens at the execution layer — where your agent acts on inputs it was never built to distrust.