Ask Sophia: Data Access Governance (DAG)
See who can reach sensitive data and why, then right-size access across cloud, SaaS, and On-Prem in minutes.
Ask Sophia: Data Access Governance (DAG)
See who can reach sensitive data and why, then
right-size access across cloud, SaaS, and On-Prem
in minutes.
Transcript
Hi, I'm Sophia, Lightbeam's AI product guide.
I help security teams understand where sensitive data exists, who
can access it, and where it may be exposed.
In this short walkthrough, I'll show you how Lightbeam uses AI to discover
sensitive data, connect it to identities, and help reduce risk across your
environment. What would you like to explore?
The real risk here is that sensitive data gets overexposed through inherited
and indirect permissions, so teams think access is controlled when it
actually is not. Lightbeam fixes that by tracing effective access
all the way back to the people in the data, exposing every direct, nested,
and external path, so you can enforce least privilege with audit-ready evidence.
Let me pull up where inherited and external access paths quietly break least
privilege.
Going ahead, the platform flips the focus from files to the people they describe,
surfacing every piece of sensitive data tied to a customer or employee, which
lets you see exposure through the lens of the data subject.
Next, the detailed entity pane aggregates the attributes, the
systems storing them, and any policy violations, giving you
context on why that data matters and where remediation should
start. Once you're done with that, the access matrix reveals
exactly which users and groups can touch that person's records,
answering the critical question of who should have that access at all.
Right after that, the consolidated governance screen surfaces open or
excessive permissions across the estate, tying each over-grant
directly to the sensitive data it endangers.
Moving on, the user-centric view surfaces individuals whose access
levels are risky, so you can prioritize reviews on the most overprivileged
accounts.
Following that, the groups view uncovers the hidden amplification of rights that
often spreads through role memberships, highlighting which groups need
tightening. Now, the object-level panel flips
back to the data itself, showing which files or folders are most
exposed and the exact access paths feeding that risk.
And then, the access review workbench lets you approve, deny,
or flag those entitlements, creating an audit-ready decision trail.
After that, the folder-specific review drills into high-risk zones like
HR or finance, confirming who can see those files and
documenting any remediation steps.
Finally, the audit log captures every review action with timestamps and
reviewer IDs, giving you a ready-to-present evidence package for
regulators.
I help security teams understand where sensitive data exists, who
can access it, and where it may be exposed.
In this short walkthrough, I'll show you how Lightbeam uses AI to discover
sensitive data, connect it to identities, and help reduce risk across your
environment. What would you like to explore?
The real risk here is that sensitive data gets overexposed through inherited
and indirect permissions, so teams think access is controlled when it
actually is not. Lightbeam fixes that by tracing effective access
all the way back to the people in the data, exposing every direct, nested,
and external path, so you can enforce least privilege with audit-ready evidence.
Let me pull up where inherited and external access paths quietly break least
privilege.
Going ahead, the platform flips the focus from files to the people they describe,
surfacing every piece of sensitive data tied to a customer or employee, which
lets you see exposure through the lens of the data subject.
Next, the detailed entity pane aggregates the attributes, the
systems storing them, and any policy violations, giving you
context on why that data matters and where remediation should
start. Once you're done with that, the access matrix reveals
exactly which users and groups can touch that person's records,
answering the critical question of who should have that access at all.
Right after that, the consolidated governance screen surfaces open or
excessive permissions across the estate, tying each over-grant
directly to the sensitive data it endangers.
Moving on, the user-centric view surfaces individuals whose access
levels are risky, so you can prioritize reviews on the most overprivileged
accounts.
Following that, the groups view uncovers the hidden amplification of rights that
often spreads through role memberships, highlighting which groups need
tightening. Now, the object-level panel flips
back to the data itself, showing which files or folders are most
exposed and the exact access paths feeding that risk.
And then, the access review workbench lets you approve, deny,
or flag those entitlements, creating an audit-ready decision trail.
After that, the folder-specific review drills into high-risk zones like
HR or finance, confirming who can see those files and
documenting any remediation steps.
Finally, the audit log captures every review action with timestamps and
reviewer IDs, giving you a ready-to-present evidence package for
regulators.
