Your AI security engineer

The fix arrives written. You just say yes.

Every other tool hands you a list and leaves the work with you. This one reads the noise so you don't, works out the handful of issues an attacker could actually use, and writes the change that closes them — as a pull request you approve, or not. Nothing ships without you.

You approve every change · It never reports what it could not prove · One switch stops it all

Example · how two small problems become one big one
Cross-surface attack pathA password left in code and a stolen staff login both lead, through one cloud login that has too much access, to full control of the company's cloud.same keysame userunlockscodea password left in codeSaaSa stolen staff logina cloud logintoo much accesseverythingfull access
AI engineer: kills the leaked password and cuts the over-broad access · you approve first

This is the reasoning the engineer does across your estate — one route, not three unrelated tickets.

What it does

The job you would hire for, done every day.

Not a tool your team has to operate — the work itself, running continuously. You step in only where a judgment call is genuinely yours to make.

01

It looks everywhere, every day

Code, cloud, web, APIs, containers, identity and SaaS — on a floor of 30+ open-source scanners, so you are not quietly missing what a dedicated tool would have caught.

02

It tells you which five matter

Hundreds of alerts become a handful, because it works out which ones an attacker could really use and what they reach. You stop guessing which are real.

03

It writes the change

A pull request, a config change, an access revocation — the actual fix, not remediation advice you still have to implement. It is ready the moment you say go.

04

The evidence is already made

The same work counts toward 27 frameworks, signed and dated. So the answer to your customer's questionnaire is written before they ask.

Why you can trust it

Autonomy you can actually hand the keys to.

An agent that changes your infrastructure has to be safe by construction. Here's how.

You never chase a ghost

It cannot report something it could not prove — no finding without a tool behind it, no claim about your permissions the evaluator did not actually return. If it cannot show you the evidence, you never see the finding.

Routine fixes just happen. Risky ones wait for you

The low-stakes work goes through on its own so it stops piling up. Anything that could break something sits in your inbox until you tap approve — and you set where that line is.

It cannot write to anything until you let it

Every connection is read-only by default and least-privilege. It opens the pull request or drafts the change, and applies it only after you approve. There is no surprise write.

You can show exactly what it did

Every action — the ones you approved and the ones that went through on their own — is recorded in a signed log you can replay. Useful the day an auditor asks, and the day you want to know why something changed.

One switch stops everything

Freeze all autonomous action instantly, and it stays frozen: the switch beats any approval already given, and queued work waits. The one human on the loop stays in control.

The detection is the tools your engineers already trust

Underneath is the leading open source the industry runs on. The agent reasons on top of proven scanners rather than replacing them with something nobody can inspect.

How a fix happens

From scanner output to a signed, approved fix.

STEP 1

A tool fires

An OSS scanner surfaces a candidate. It enters the agent's queue grounded in that tool's evidence.

STEP 2

The agent verifies

It confirms, corroborates across tools, and rates confidence — discarding what it can't substantiate.

STEP 3

It writes the fix

A PR, config change, or identity action — mapped to the CWE and the compliance controls it closes.

STEP 4

You approve

Consequential changes wait for your tap. It applies, then signs the decision into the ledger.

One click, not a chat box

An AI security team you run with actions, not prompts.

No blank prompt to stare at. Your AI Security Engineer and AI Pentester are consoles of one-click actions — each triggers a real agent over your real findings, and anything it changes waits for your approval.

Triage everything

→ A prioritized list — real risk first, the noise collapsed.

Auto-fix the criticals

→ A pull request or config change, ready for you to approve.

Investigate this issue

→ Root cause, blast radius, and how it chains to a crown jewel.

Cloud deep-dive

→ The IAM + reachability paths an attacker could actually use.

Generate evidence

→ A signed, auditor-ready compliance pack.

Launch a pentest

→ An exploitation-proven report with captured PoCs.

Vs the alternatives

A scanner flags. An engineer fixes.

TensorShield
AI security engineer
A scanner
flags only
Hire an engineer
$150k+/yr
Detection on the open source your engineers already trust
Tells you which five matter, not all four hundred
Writes the fix, not remediation advice
You approve anything risky — and can stop it all instantly
Never reports what it could not prove
Shows exactly what changed, when, and who approved it
Cost for an SMB$/mo$/mo$$$$/yr

Category comparison — capabilities vary by vendor and plan.

Hire the engineer that never sleeps.

Connect a system and watch the agent detect, triage, and prepare its first fixes — for free, with you in control of anything that matters.