Know where your sensitive data lives, before someone else does.
Argus runs a lightweight agent inside your cloud, finds every place sensitive data lives, shows you exactly what's exposed, and fixes it on your approval - without your data ever leaving your environment.
No data leaves your environment. No inbound ports opened. No sample sets uploaded to a third-party. Just structured findings - that you control.
01
Deploy the agent
A single deployment module drops the agent into your cloud environment. No firewall changes, no inbound ports, no shared credentials. It's running in minutes.
02
Discover & classify
Argus finds every datastore - S3, RDS, DynamoDB, Redshift - and intelligently scans the files most likely to hold sensitive data. Less noise, faster results.
03
Fix it and prove it
Every finding carries the fix. Approve it, watch it run, and let a verification rescan confirm it worked. If it didn't, roll it back in one click.
Architecture
Your data never leaves your environment.
A split control-plane / data-plane design that satisfies the strictest data residency reviews. Customer data is processed inside the customer's VPC; only structured, non-reversible findings cross the boundary.
No inbound ports
The agent makes outbound HTTPS calls only. Your perimeter stays closed - no firewall changes, no VPN, no public endpoint to defend.
Read-only until you say otherwise
Discovery and scanning are read-only. The narrow set of write permissions that automated remediation needs is a separate, opt-in grant you review and can revoke in one click - no static keys, no shared secrets.
Insights, not data
Only structured findings - counts, categories, risk levels - cross the boundary. The sensitive data itself never leaves. Throttled scanning and automatic backoff keep it production-safe.
01Discover
Find the data. Then find everyone who can reach it.
An inventory is only half the answer. Argus maps the datastores that hold sensitive data and the identities standing next to them, in the same pass.
Every datastore, found and classified
S3, RDS, DynamoDB and Redshift discovered from a single agent, then scanned where sensitive data is most likely to live - so you get coverage without the noise.
PII, financial, health, credentials and IP detected out of the box
CSV, JSON, PDF, DOCX, XLSX and more - record-aware sampling
Every finding carries a detection and statistical confidence
The identities standing next to it
Argus reads your IAM graph alongside the data, so a bucket full of SSNs is never just a bucket - it is a bucket and the seven principals who can read it.
Over-privileged, stale, external and no-MFA access, flagged per identity
Cross-account and high-risk service access surfaced explicitly
Every identity scored on what it can reach, not just what it is
02Detect
Not every finding deserves your Tuesday.
Argus scores what it finds on what the data is, how the store is configured and who can reach it - then puts the one thing that actually matters at the top.
Alerts with a lifecycle, not a firehose
Findings are deduplicated into alerts that carry severity, status and full attribution - which datastore, which account, which region, which data types.
Active, investigating, contained and resolved - tracked, not just raised
Every alert names its source datastore and the records behind it
Group related alerts into an incident and work them together
Risk you can triage by impact
Every datastore and identity is scored, then ranked. Top risk drivers show what is pushing the number up, so the queue explains itself.
Exposure, sensitivity, volume and reachability as separate sub-scores
Top risk datastores and top risk identities side by side
Distribution across critical, high, medium, low and minimal
Your rules, not just ours
Write policies for what your organisation actually cares about - residency, retention, classification, encryption - and Argus raises a violation the moment a datastore drifts out of line.
Recommendations, deduplicated
Twelve findings on one bucket collapse into one prioritised fix, with the risk it removes and the effort it costs attached. No wall of tickets to triage by hand.
Detection you can audit
Confidence scores, sample sizes and the extrapolation behind every count are on the record - so a number in a board deck can be defended, not just quoted.
03Remediate
Most DSPM stops at the finding. This is where Argus starts.
Build the fix once as a workflow. Argus dispatches it to the agent in your account, verifies it worked with a rescan, and keeps the door open to undo it.
01
Dry run first
Every workflow can run as a simulation that reports exactly what it would change, and changes nothing. See the diff before you own it.
02
A human approves
Semi-automatic by default: the fix is queued, a named reviewer approves or rejects it, and the decision is on the audit trail. Fully automatic is opt-in, per workflow.
03
Verified, not assumed
A run is not green when the API call returns. It goes to verifying, a rescan re-derives the posture, and only then does the finding close.
04
Undo within 24 hours
Argus snapshots the pre-execution state. If a fix breaks something downstream, roll it back in one click and the original state comes back.
Today Argus remediates S3 (block public access, default encryption, versioning, bucket policy) and IAM (disable access keys, detach over-privileged policies, enforce MFA). Everything runs through the agent already in your account, under the same read-plus-remediate role you signed off on.
04Prove it
The audit answer, derived from the scan.
Findings tie to the controls they touch across eight frameworks, with the affected datastores and an estimated exposure attached - so an audit question has an answer, not a spreadsheet.
Control-level status, not a questionnaire
Every control is evaluated against what the agent actually observed. When a signal could not be read, Argus says so rather than guessing a pass.
Coverage is reported next to the score, so an unassessed control never hides inside a green number
Violations broken down by framework, category and severity
Export an evidence pack for auditors in one click
GDPR
EU privacy
HIPAA
US health
PCI DSS
Card data
SOX
Financial
ISO 27001
InfoSec
SOC 2
Trust criteria
CCPA
California
GLBA
Financial privacy
Trust
We are asking for access to your cloud. Here is what guards it.
SSO and SAML
Bring your identity provider. Sessions follow it.
MFA enforced
Required on every account, not offered as a setting.
Granular RBAC
Per-section permissions, down to the individual action.
Full audit log
Every mutation recorded with actor, target and before-and-after values.
Encrypted at rest
Credentials and findings encrypted; scan payloads never leave your VPC.
Tenant isolation
Every query is tenant-scoped. One customer can never read another's data.
FAQ
Answers to the questions security teams ask first.
Does any of our data ever leave our environment?
No. The agent runs in your VPC, scans datastores in your account, and only sends back structured findings - counts, categories, confidence scores. Raw bytes, sample contents, and sensitive payloads stay in your environment.
What permissions does the agent need?
For discovery and scanning: read-only S3 ListBucket / GetObject, RDS Describe* and limited query, DynamoDB Scan with throttling, and Redshift read-only. Automated remediation needs a second, separate grant covering only the actions its workflows perform. The IAM policy ships with the Terraform module - review it, narrow it, sign off on it.
Will Argus change things in our account on its own?
Only if you turn it on, and only where you point it. Remediation is disabled per tenant until an admin enables it. Workflows default to semi-automatic, so a named human approves each run before anything is applied, and every workflow can be dry-run first. Fully automatic dispatch is opt-in per workflow. Argus snapshots the pre-execution state, so a successful run can be rolled back for 24 hours, and approvals, runs and rollbacks all land on the audit log.
How does the sampling actually decide what to scan?
A weighted scoring model considers file path, name, size, content-type hints, and bucket tags. A LightGBM classifier trained on labeled examples ranks files by likelihood of containing sensitive data. Adaptive limits cap scan time per bucket; stratified sampling ensures fair coverage across prefixes.
How long does it take to deploy?
Roughly five minutes of setup work, plus the time it takes for your usual deployment pipeline to apply. Most teams are running their first scan within an hour of starting.
Does it support Azure or GCP?
AWS today; Azure (Blob, SQL, Cosmos DB) is on the roadmap, GCP after that. The agent's provider abstraction is designed for additional clouds - adding one is integration work, not architecture work.
What's the deployment model - SaaS, hybrid, on-prem?
Hybrid by design. The control plane (auth, dashboards, audit, RBAC) runs as SaaS. The data plane (the scanning agent) runs in your VPC. Customer data only touches the data plane; only structured findings cross to the control plane.
See where your sensitive data lives.
Talk with us about your environment. We'll show you how Argus works, scope a pilot, and help you get visibility fast - without any sales-process drag.
