Security You Can Prove

Brava’s Security Operations Platform simulates attacks to improve detections, reduce ingest volume, and automate incident response. We're leading the new era of SOC certainty.

Agent run · AWS production
01:24
Goal
Test our AWS environment against a ransomware attack
  1. Signs in with a leaked access key
    Initial access
    Detected
  2. Maps your S3 buckets and backups
    Discovery
    Detected
  3. Gives itself admin rights
    Privilege escalation
    Gap closed
    Detection written. Attack re-run. Alert fired.
  4. Switches off audit logging
    Defense evasion
    Gap closed
    Logs restored, detection added. Attack re-run. Alert fired.
  5. Encrypts backups with its own key
    Impact
    Detected
Detection coverage5 / 5

2 gaps closed and proven by re-running the attack.

Detection Coverage

Brava runs the attack each rule was written for, and shows you which ones stayed silent.

Evidence-Backed Investigation

Ask in plain English. Every report cites the raw events behind it.

SIEM Hygiene

Broken detections, schema drift and dead log sources surface the day they happen.

65–85% Lower SIEM Cost

Measured across our customers.

How It Works

Attack simulation tools stop at a report of what failed. Brava rewrites the detection, fixes the telemetry, and runs the attack again until it fires. Then it repeats the loop whenever your environment changes.

01

Run the Attack

You describe a threat. AI agents plan the attack path, run each technique in your environment or a mirror of it, and record every event it produces.

02

Capture the Telemetry

Each event is fingerprinted field by field, so you can see what was logged, what was empty, and what got cut off.

03

Write the Detection

Rules are generated in your SIEM's own query language, using only fields the evidence shows are there.

04

Confirm It Fires

The attack runs again, and Brava checks that a real alert showed up in your real SIEM.

01
01
02
03
04
Rule decay

Every SIEM Breaks Over Time. Brava Fixes Yours Before an Attacker Finds Out.

Detections break when your environment changes: a log source moves, a field is renamed, a parser is updated. The rule raises no error, so nobody notices until it misses an attack. Brava runs real attacks, finds the rules that stayed silent, and rewrites them.

Gaps found24

One Platform, Three Jobs

Works alongside the SIEM you already have.

Detection Validation

Test Every Rule Against a Real Attack

Give Brava a goal, like testing your AWS environment against ransomware. It picks the techniques, runs each one, and checks whether your SIEM alerted. Every square on the matrix links to a run you can replay.

  • Scheduled game days. Re-test your detections automatically after every change.
  • Gaps you can act on. Each one comes with the log source that would close it.
  • A score your board understands. One readiness number, backed by real runs.
See a Validation Run
MITRE ATT&CK · enterprise
71%
Scan complete
Initial Access
Execution
Persistence
Priv. Escalation
Defense Evasion
Exfiltration
ValidatedPartialBlindNo telemetryTop gap
Investigation

Investigate in Plain English

Ask Aquarium a question the way you would ask a senior analyst. It plans the queries, searches every source at once, follows up on what it finds, and writes the report with the evidence attached.

  • Thinks in steps. Breaks the question down per source and adjusts as results come back.
  • Searches beyond the SIEM. Archived logs, EDR, and cloud audit trails in a single pass.
  • Shows its work. Every finding links to the raw events behind it.
Watch an Investigation
Aquarium · investigation
Report ready
Who read the finance archive bucket after hours, and did anything leave the account?
01Plan the investigation6 queries · 4 sources
02Query every source1,540,882 events read
03Correlate and re-plan3 leads · 1 confirmed
04Write the report14 citations
Aquarium archive1.2MCrowdStrike NG-SIEM84kCloudTrail221kOkta4.1k
Confirmed214 objects read by ci-deploy-role from an address outside the VPC, 02:14–02:31 UTC.
Ruled outBoth console logins in the window were the on-call rotation, MFA present.
Report written · 14 citations · 6.2sNothing left your tenant
Data Pipelines

Cut SIEM Costs Without Losing Evidence

Brava sends your SIEM the events your detections need and moves the rest to low-cost storage. Nothing is deleted, and anything can be brought back.

  • Routing based on evidence. Data no rule reads stops going to the SIEM.
  • Clean data on the way in. Parse, enrich, and normalize before you pay to index it.
  • Still searchable. Archived data stays available to Aquarium investigations.
See a Pipeline
Pipeline · zscaler-zia → splunk + archive
Active
Zscaler ZIASYSLOG · 5140Brava RouterPARSE · ROUTESplunk0.22 TB/DArchive1.08 TB/D
Ingested
1.3 TB/day
Forwarded to SIEM
0.22 TB/day

Every Day, at Customer Scale

What Brava processes in a single day across customer environments.

2.4 trillion
events read and fingerprinted a day
1,100
attack techniques replayed a day
3,800
detections re-tested against that evidence
140 K
fields mapped, including the ones no rule reads

Rounded, measured over a 24-hour window across customer environments.

83%

less data sent to a customer's SIEM, with every detection still getting the fields it needs.

Before
1.3 TB/day
After
0.22 TB/day

Each square is 0.01 TB a day. The hollow ones weren't deleted. They moved to low-cost storage and can be searched or replayed at any time.

Daily volume · 1 cell = 0.01 TB
To SIEMArchived
Works with your stack
70+ sources and destinations
WIZ company logo with white letters and a sparkle on a blue background.WizStylized shield icon with an outer blue and green border and an inner smaller shield in red and yellow colors, symbolizing security or protection.Google SecOpsSSplunkMMicrosoft SentinelEElasticCCrowdStrike NG-SIEMSSnowflakeAAmazon S3

Plus anything that can write to S3, Kafka, syslog or an HTTP endpoint.

See What Your SIEM Is Missing

Get your readiness score, the detections that can't fire, and the log volume no rule reads.

What you get
  • Readiness score. Your ATT&CK map, backed by real runs.
  • Detections that can't fire. Each rule missing a field it depends on.
  • Unused log volume. Data you pay to store that no rule reads.