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REDMAW

Platform

Risk lives in the connection.

A vulnerability is one fact. An attack path explains what that fact allows an attacker to reach next.

Developer → GitHub → Secret → Cloud Account → Production
  1. Developer
  2. GitHub
  3. Secret
  4. Cloud Account
  5. Production

Each hop validated by successful exploitation

An attacker does not see isolated findings.

Security products often produce separate findings because they inspect separate systems. An attacker sees opportunities that connect.

A public endpoint exposes a credential. A developer identity can access GitHub. A repository contains a secret. The secret authenticates to a cloud account. The cloud account reaches production.

Each step may belong to a different security product. The attacker only cares that the route works.

Four canonical paths

The same logic, across four surfaces

No single step needs to look catastrophic in isolation. The route is the risk.

Applications

  1. Internet
  2. Application
  3. Credential
  4. Internal Network
  5. Customer Data

An application weakness matters more when it produces a credential. The credential matters more when it works internally. The internal foothold matters more when it reaches customer data.

SaaS & Identity

  1. Compromised Identity
  2. SaaS Platform
  3. Sensitive Customer Records

An account compromise becomes material when its permissions, grants or tokens expose sensitive records. The blast radius is defined by effective access, not by the username.

Developer access

  1. Developer
  2. GitHub
  3. Secret
  4. Cloud Account
  5. Production

Developer access becomes infrastructure access when source repositories contain secrets or integration credentials. The path connects identity, source, credentials, cloud access and production.

AI Systems

  1. Malicious Content
  2. AI Agent
  3. Tool Call
  4. Production Database

An AI issue becomes materially different when the system has authority to act. Content influences the model, the model influences a tool call, the tool reaches production data.

Prioritization

Attack paths change what you fix first.

Suppose two findings carry similar severity.

Finding A

Difficult to exploit, and it reaches an isolated system.

Finding B

Gives an ordinary user a credential that unlocks a sensitive SaaS application.

A flat severity score can make them look similar. Attack-path context does not. The question becomes: which finding changes what the attacker can reach?

Proof comes before path confidence.

A graph built from assumptions is not security proof.

A path becomes useful when its important steps are supported by adversarial evidence. That is why the platform leads with validated exploitation rather than with an impressive-looking diagram.

Availability

Platform vision vs automated chaining

The attack-path model is central to RedMaw, and the current availability boundary still matters.

Today RedMaw tests supported surfaces and preserves findings and evidence in a common state. The deeper automation that dynamically chains every step across all four surfaces is not shipped.

Roadmap: not shipped

The paths above describe the attacker model the platform is built around, and are used to explain why reachability drives prioritization. Assembling every hop end to end automatically is not something RedMaw does today.
  • Automated cross-surface attack-path chaining

Reachability is how attackers think. RedMaw proves the hops it can prove.

From path to remediation

Attack-path context should survive into the fix.

A developer or security engineer should be able to understand not only what is broken, but why it matters and what it enables.

After the relevant issue is remediated, RedMaw re-tests it. If the path is no longer viable, the security state changes.

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.