DEV Community: Security Expert

Most Cybersecurity Systems Are Already Obsolete — AI Just Made It Worse

Security Expert — Tue, 28 Apr 2026 09:31:22 +0000

Cybersecurity isn’t evolving gradually anymore.
It’s being forced into a new reality by AI-driven attacks.

In recent incidents, attackers didn’t break into systems—they logged in.

Using tools like Microsoft Teams and Slack, they impersonated IT helpdesk staff, convinced employees to grant access, and deployed malware inside trusted workflows.

Let that sink in:
👉 No firewall bypass
👉 No zero-day exploit
👉 Just human trust, manipulated at scale

The Shift No One Can Ignore

Trust is Being Weaponized

AI-generated emails, deepfake voices, and hyper-personalized messages are making social engineering far more effective than traditional attacks.

What used to be “phishing” is now behavioral manipulation at scale.

Collaboration Tools Are the New Entry Point

Teams. Slack. Email.

The very tools built to improve productivity are now becoming primary attack surfaces.

Because they operate inside trusted environments,
they bypass suspicion by design.

Detection is Already Too Late

Most organizations still rely on detection-based security:

Alerts
Logs
Post-incident response

But modern attacks:

Execute in seconds
Move laterally using legitimate access
Blend into normal activity

By the time you detect them,
they’re already inside your system.

The Real Problem

There’s a growing gap between:
👉 Attack speed (AI-powered, automated)
👉 Response speed (manual, delayed)

And that gap is where breaches happen.

The Only Way Forward: AI-Native Security

To defend against intelligent attacks, security must become intelligent itself.

That means shifting to:

Predictive threat modeling
Real-time behavioral anomaly detection
Automated (agentic) response systems
Zero Trust architectures

This isn’t about improving existing systems.
This is about rebuilding security for an AI-first world.

Final Thought

You can’t defend against adaptive, intelligent attacks
with static, rule-based systems.

The question is no longer:
“Are you secure?”

It’s:
“How long until your current system fails?”

We’re moving from AI-assisted systems agentic systems that execute workflows.

Security Expert — Fri, 24 Apr 2026 10:26:38 +0000

A simple way to think about it:

Input → Decision → Action → Outcome

Instead of stopping at prediction or insight, the system:

interprets incoming data (APIs, docs, events)
makes context-aware decisions (rules + models)
triggers actions (updates, workflows, responses)
feeds outcomes back for improvement

This pattern is starting to replace a lot of manual orchestration in:

document processing
internal ops
request handling
decision workflows

The challenge isn’t building models anymore.
It’s designing systems that actually execute reliably at scale.

Curious how are you handling orchestration today?
Still human-in-the-loop heavy, or moving toward autonomous flows?

From Copilots to Agents

Security Expert — Mon, 13 Apr 2026 10:27:32 +0000

Most AI implementations today are still reactive.

You give input → it responds.
You prompt → it generates.

But that model is starting to break.

We’re seeing the rise of Agentic AI—systems that don’t just generate outputs,but execute workflows with defined goals.

This introduces a different way to think about system design:

From Functions to Outcomes

Instead of calling isolated functions, systems are designed to achieve outcomes across multiple steps.

From Prompts to State

Context is no longer a single input—it’s persistent, evolving, and influences decisions over time.

From Control to Guardrails

You don’t micromanage every step.
You define boundaries, and the system operates within them.

From Execution to Orchestration

The role of developers shifts toward designing how systems think, decide, and act—not just what they output.

The real challenge isn’t building these systems.
It’s deciding where you’re comfortable letting them act.

Because once systems stop waiting,
your architecture, monitoring, and trust models all need to evolve.

Curious how others here are approaching this
Are you experimenting with agent-based systems in production yet?

Zero‑Loss AI Agents

Security Expert — Fri, 10 Apr 2026 09:49:41 +0000

AI agents are moving from toy demos into critical paths: patient journeys, security operations, and money flows. As engineers and architects, we can’t treat them like generic chatbots with a fancy wrapper.

What “zero‑loss” means in practice

For us, a zero‑loss agent has three non‑negotiables:

Secure by design: identity, authorization, and data boundaries defined up front.

Auditable by default: every action, input, and decision reason is traceable.

System‑native: the agent lives inside existing workflows and infrastructure, not glued on the side.

Concrete domains

Healthcare: intake, monitoring, ambulatory care, revenue workflows, EHR‑integrated processes.

Security: Zero Trust, Identity‑First MFA, AI‑assisted detection and response, 24/7 MDR‑style operations.

Fintech: high‑volume transactions, KYC/risk checks, reconciliation and reporting pipelines.

Technical questions worth asking

When we design or review an agent integration, we ask:

Can we reconstruct every action it took from logs alone?

What data stores can it reach, and under which identities?

What are the explicit “do not cross” boundaries?

How does it fail—silently, loudly, or safely?

If you can’t answer those questions confidently, the agent is not production‑ready—especially not around patients, security events, or capital.

Curious what other teams are doing here:
Are you already putting AI agents in high‑stakes paths, or still prototyping at the edges?

Why Sales Efforts Don’t Always Turn Into Revenue

Security Expert — Thu, 09 Apr 2026 12:30:00 +0000

The gap in most SDR workflows
Even with the right ICP, timing is usually off.
A company might be a perfect fit -
just not at that moment.
So outreach lands… but doesn't convert.
What starts to work better
Keep ICP updated (not static lists)
Act on signals (hiring, funding, expansion)
Reach out with real context
Stay consistent on follow-ups

This is where most of the lift comes from.
What teams see when this is done right
3–5x more qualified meetings
30–60% lower cost per pipeline
2–4x higher reply rates
More consistent pipeline without adding SDRs

Same market. Same product.
Just better timing + execution.
Most SDR problems aren't about effort. They come down to who you target, when you reach out, and whether you follow through.
If you want to test this in your own funnel:
https://periscope-tech.com/sales-revenue-agents Free trial available.

I think the AI vs AI cybersecurity debate is missing the real risk

Security Expert — Thu, 02 Apr 2026 12:15:00 +0000

Everyone’s talking about attackers using AI vs defenders using AI.

But after working closely with teams at Periscope Technologies Inc, I’m starting to feel like that’s not where things are breaking.

What we’re seeing more often:

AI inside companies already has:

• Access to sensitive data
• Ability to trigger workflows
• Decision-making power

But very little verification around:

👉 What it’s doing
👉 Why it’s doing it
👉 Whether it should be doing it

Traditional security made sense when:

• Users were human
• Behavior was predictable
• Access was controlled

AI doesn’t fit that model at all.

Feels like we’re focusing heavily on external AI threats…

While ignoring a new category of risk:

Unverified AI execution inside systems

Curious if others here are seeing this?

Or is the focus still mostly on external threats?

periscope-tech.com

$14.5B wiped out in a day after an AI shock overreaction or real signal?

Security Expert — Mon, 30 Mar 2026 10:47:32 +0000

A $14.5B drop in cybersecurity stocks triggered by an AI-related event is being called market volatility.

Not sure I agree.
Feels more like a signal.

AI is moving faster than security can keep up.

And most companies are already using AI internally for:

• Data access
• Decision-making
• Workflow automation

But very few have real control or visibility into:

👉 What it’s doing
👉 What data it’s touching
👉 What decisions it’s making

Working with teams at Periscope, this gap shows up a lot.

Not in adoption.

In control.
Curious how others see this:

Is this just hype…
or an early warning?

https://periscope-tech.com/periscope-secure-access-platform

What basic security checks do you actually follow every week?

Security Expert — Fri, 27 Mar 2026 10:58:16 +0000

In many setups I’ve seen, the real issues aren’t complex — it’s small things getting missed:

Old user/vendor access still active
Backups assumed to be working
Critical updates delayed
Alerts no one checks
No clear owner if something breaks

Individually, these don’t feel urgent.
But that’s usually where problems start.

Do you follow a weekly checklist for this?
Or is it more reactive in your environment?

https://periscope-tech.com/periscope-secure-access-platform

Deploying Agentic AI Safely: Lessons from This Week in AI

Security Expert — Mon, 23 Mar 2026 11:24:45 +0000

This week, agentic AI made headlines:

Kill-switches being implemented
Agents treated like employees with identities
Legal challenges emerging
Dedicated infrastructure for execution

Most deployments fail because control and monitoring aren’t built-in.

At Periscope, we deploy secure, production-ready agentic workflows. Try 1 workflow risk-free for 2 weeks, with monitoring, guardrails, and permissions baked in.

https://periscope-tech.com/agentic-factory

Why Replacing Hospital Systems Fails (And What Actually Works)

Security Expert — Fri, 20 Mar 2026 11:00:55 +0000

Most hospitals already have the systems they need.

EHR. CRM. RCM. Contact center.

The real problem?
They don’t work well together.

That’s where most “AI transformations” go wrong —
they try to replace instead of optimize.

A more practical approach:

Embed AI into existing workflows across
intake → scheduling → care → billing.

Instead of adding complexity, it removes friction.

What changes:

Intake becomes faster

Admin workload drops

Revenue leakage is reduced

No rip-and-replace.
No operational disruption.

Start with one workflow. Measure impact. Expand from there.

Full approach:
https://periscope-tech.com/agentic-factory

SaaS is quietly being replaced by Agent-as-a-Service (AaaS) — are we ready for this?

Security Expert — Tue, 17 Mar 2026 16:26:33 +0000

This week had some interesting signals:

NVIDIA pushing infrastructure for AI agents

Alibaba launching enterprise agent platforms

Feels like we’re moving from SaaS → systems that actually execute tasks.

Not just dashboards, but AI that:

updates systems

triggers workflows

makes decisions

The interesting part:

The biggest challenge isn’t capability.
It’s control.

If an AI agent takes the wrong action inside your stack, the risk is very real.

Curious how people here are thinking about this:

Are you experimenting with agents yet?
Or does this still feel too early / risky?

periscope-tech.com

Fake Claude Code Download Pages Are Delivering Infostealer Malware

Security Expert — Mon, 16 Mar 2026 11:36:59 +0000

As AI development tools continue to grow in popularity, attackers are beginning to exploit their ecosystems.

A recent campaign is distributing fake Claude Code download pages that mimic legitimate installers.

The attack relies on sponsored search advertisements, meaning developers searching for Claude Code may encounter the malicious page before the real one.

If the installation command is copied and executed, the malware deploys infostealers capable of capturing:

• Browser credentials
• Session cookies
• API tokens
• Crypto wallet data

This is another sign that AI tooling ecosystems are becoming a new supply-chain attack vector for developers.

Full threat analysis:
https://blog.periscope-tech.com/new-threat-alert-fake-claude-code-downloads-delivering-infostealers/

cybersecurity #devops #infosec #ai #security