Company
Stop assuming you are secure. Prove it.
RedMaw is building an autonomous adversarial security platform for organizations that need to know what an attacker can actually reach.
Modern companies depend on applications, SaaS identities, internal infrastructure and AI systems. Security tools often inspect those surfaces separately. RedMaw applies a shared adversarial operating model across them, so the security conversation can move from assumption to validated evidence.
The problem
Security programs contain useful signals, reports and controls, but they still depend on assumptions.
A scanner says a weakness may exist. A ticket says the fix is done. A pentest describes what was true during an engagement. A policy says testing occurs.
RedMaw is built around the gap between those statements and what can actually be proven.
The operating model
Discover → Attack → Prove → Prioritize → Remediate → Re-attack
Security is not complete when a finding appears. The loop matters because the finding is a state, not an event.
- 01
Discover
Map the applications, identities, integrations, infrastructure and AI systems in authorized scope.
- 02
Attack
Execute adversarial technique against the environment as it is actually configured.
- 03
Prove
Capture evidence of what succeeded and what it reached.
- 04
Prioritize
Rank by reach and consequence, and identify path chokepoints.
- 05
Remediate
Hand engineering the path, the evidence and the fix that breaks it.
- 06
Re-attack
Re-test the path. A finding closes only when it can no longer be walked.
Re-attack feeds the next Discover. The loop does not restart from zero. It carries the security state forward.
RedMaw keeps the finding as a security state, connects it to evidence and remediation, then re-runs the relevant validation when the team says the issue is fixed.
Four surfaces. One adversary.
Where the model applies
Current capability varies by surface, and roadmap features are labeled rather than presented as shipped.
Applications
Attack your applications before attackers do.
Adversarial testing of the web applications and APIs you own and authorize, aimed at proving exploitability rather than reporting resemblance to a known pattern.
Example question
What can someone actually do with it?
SaaS & Identity
See what a compromised identity can actually reach.
Testing the customer-controlled identity and permission graph to establish what one compromised account, key or grant can actually expose.
Example question
If this account is compromised, which systems and sensitive records become reachable?
Internal Infrastructure
Assume breach. Now what?
Establishing which internal servers, routers and switches can actually be accessed from an authorized foothold, and what those systems expose. Access is demonstrated and reported, never disrupted.
Example question
If an attacker gains access to this internal service or credential, what high-value systems could become reachable next?
AI Systems
Attack models and agents before you trust them.
Adversarial testing of deployed AI systems and release pipelines, aimed at how the system behaves when the input is hostile rather than expected.
Example question
Can malicious content change what the AI reveals, ignores, or attempts to do?
Why RedMaw exists
Not a larger pile of findings.
The goal is a more defensible answer to the questions that actually matter:
- What is actually exploitable?
- What does it reach?
- What needs to change?
- Did the fix work?
That is the assumption-to-proof spine behind RedMaw.
Stop assuming you are secure. Prove it.
Continuously test what an attacker can actually reach across your applications, SaaS identities, internal infrastructure and AI systems.