Four layers, one mission.
Shadow Security is not one product with four features. It is a cybersecurity ecosystem: four distinct efforts aimed at four distinct failures, built in an order where each one makes the next possible.
Shadow Security is an AI-native cybersecurity company. It builds products, infrastructure and communities across cybersecurity education, responsible vulnerability disclosure, data governance, and security assurance.
How it's organised.
Suraksha is a family of two products serving individuals. Shastra and Astra serve organisations. AI is a property of the ecosystem rather than a product in it.
Diagram: Shadow Security sits above four products. Suraksha Labs is for learning and practice. Suraksha VDP is for discovery and disclosure. Shastra is for governance and protection. Astra is for proof and assurance. An intelligence layer of AI runs across all four.
Who each layer is for.
Every product states who it serves and what state it is in. Nothing is described as available before it is.
Suraksha Labs
Early access soonStart with no background at all and build real security skill through investigation: logs, terminals, traffic and evidence, not slides and quizzes.
- Start from zero, with no prior networking, Linux or web knowledge assumed
- Missions, not lectures: logs, a terminal, an objective
- AI acts as a mentor and will not solve the lab for you
Someone got in last night.
A mid-sized company noticed unusual activity on an internal service just after 02:00. You have their logs, their access records and a shell. Nobody will tell you what happened; that's the job.
- Objective
- Find the entry point and establish what the intruder reached.
- Evidence provided
- Access logs · Auth records · Service config · Terminal
Suraksha VDP
PlannedA legitimate route for findings: researchers report responsibly, organisations triage, fix, verify and give credit, with the whole lifecycle on the record.
- A defined channel for vulnerability reporting, not a support inbox
- Triage, fix and verify tracked end to end
- Researchers get credit on the record
The disclosure lifecycle has six stages: discover and report, done by the researcher; triage and fix, done by the organisation; verify, done by both; and recognise, done by the organisation.
- Researcher
Discover
A researcher finds something real.
- Researcher
Report
It goes to a defined channel, not a public thread.
- Organisation
Triage
The report is assessed, deduplicated and prioritised.
- Organisation
Fix
The issue is remediated with the finding on record.
- Both
Verify
The researcher confirms the fix holds.
- Organisation
Recognise
Credit is given, and the work becomes reputation.
Shastra
Pre-registration openData governance as infrastructure rather than paperwork, with a Compliance Copilot you can talk to instead of a dashboard you have to learn.
- Talk to it instead of learning a dashboard
- Integrate flexibly: the proxy and enforcement layers are optional
- Evidence produced as governance happens, not assembled after
“What's blocking our DPDP readiness?”
Four areas are holding you back. Here's the current state.
- Data inventory82% sources mapped
- Consent workflows64% need attention
- Retention policies71% defined
- Vendor reviews55% complete
- Evidence collected91% of current scope
Consent workflows are the highest-impact gap. Want me to walk through the three that need changes?
Astra
PlannedSecurity posture you can show a customer, a partner or a board, assessed against evidence rather than asserted in a questionnaire.
- Assessed against evidence, not a self-answered questionnaire
- Built for organisations asked to prove maturity in procurement
- No accreditation or ISO-equivalence claimed
Sequence: Assess, then Improve, then Verify, then Certify.
Why this order.
The dependency between the layers is why this is a company rather than a portfolio.