Continuous pentesting
Keep adversarial testing current between manual engagements, so meaningful changes can be tested instead of waiting for the next scheduled assessment.
Autonomous Adversarial Security
Know what an attacker can actually reach.
RedMaw is an autonomous adversarial security platform that continuously tests your applications, SaaS identities, internal infrastructure and AI systems to prove what an attacker can actually reach.
- Internet
- Application
- Credential
- Internal Network
- Customer Data
Each hop validated by successful exploitation
Attack surfaces changed. Security testing did not.
Modern companies do not have one attack surface. They have public applications, APIs, SaaS platforms, cloud identities, internal systems, developer tools, secrets, AI endpoints, models, and increasingly agents with access to business systems.
Security products usually inspect those environments separately. Attackers do not.
They start from whatever foothold works and then ask the only question that matters to them, which is what can be reached from here.
A vulnerable endpoint gives up a credential, that credential unlocks a SaaS account, and the integration sitting behind it reaches customer data. Somewhere else entirely, a malicious document steers an AI system that holds permission to call a production tool.
The individual weakness matters, but the route it opens matters more.
Four surfaces. One adversary.
Where RedMaw tests
Each surface has its own techniques and boundaries. The question stays the same.
01
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?
02
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?
03
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?
04
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?
A scanner finds weaknesses. RedMaw tries to use them.
A vulnerability scanner earns its place, because it gives you broad, repeatable coverage of known weaknesses, and you should keep it. But finding something that might be a problem and proving an attacker can reach it are different jobs, and only one of them ends the argument.
A scanner reports
What might be wrong.
An exposed service, an old package, a weak configuration, an endpoint that looks wrong. The coverage is broad and it runs the same way every time, which is exactly why it is worth keeping.
RedMaw asks
What happens when it is used.
The same weakness, this time exercised adversarially inside the approved scope, along with the evidence of whatever actually succeeded.
The questions that change the answer
- Can the endpoint expose another user's record?
- Can the leaked credential authenticate successfully?
- Can the OAuth grant reach sensitive data?
- Can the model be manipulated into revealing hidden instructions?
- Can the finding still be exploited after the developer says it is fixed?
The point is not a longer list of findings.
It is knowing which of them actually change what an attacker can reach, so that everything else can wait its turn.
Evidence can include
- The affected asset or identity
- The successful technique
- The access achieved
- The data or system reached
- The sequence that made the finding material
Where supported, that evidence is signed and tamper-evident, and session recording lets an engineer replay how the finding was produced rather than take it on trust. Mapping the behavior to MITRE ATT&CK then gives everyone reading it the same technical language.
Operating loop
Discover → Attack → Prove → Prioritize → Remediate → Re-attack
Security testing stops being an event on the calendar and becomes a loop that keeps running.
- 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.
A finding closes by proof, not by a checkbox.
Most security workflows lose their authority the moment a ticket is created. A scanner reports a weakness, a ticket gets opened, someone marks it Done, and from that point on the organization believes the exposure is gone. Nobody has gone back to check whether the attack still works.
RedMaw keeps the security state instead, so a finding travels from discovered to validated, prioritized, assigned, remediated and retested before it is allowed to close or reopen.
A ticket can say Done. RedMaw still re-runs the attack.
RedMaw does not trust a checkbox. It re-hacks the fix.
Closed by proof
If the exploit path is gone the finding closes, and if it still works the finding stays open, or reopens carrying evidence from the latest attempt.
Continuous, not point-in-time.
A pentest is a snapshot. Your environment keeps changing after the report is delivered.
RedMaw runs on a continuous schedule, picks up deployment triggers as they happen, and re-runs AI security validation whenever a model changes.
The goal is simple: test exposure closer to the moment it is introduced.
After the report ships
- Applications deploy
- APIs change
- Permissions drift
- SaaS integrations are added
- Secrets leak
- Models are retrained
Operating models
Run it, or have us run it.
One engine sits underneath each motion. The difference is who operates it.
01
Self-serve
Your team runs it. You define the scope, run the testing and review the evidence, and remediation goes into the workflows your engineers already live in.
02
Managed
Our operators run the testing and triage what comes out of it, while authorization, scope and the decision to remediate stay with you.
03
Dedicated
Larger and regulated teams get a dedicated hosted environment, secure outbound connectivity for authorized internal reach, and integrations built to fit how they already work.
Evidence for the conversations security teams already have to win.
Security reviews, customer questionnaires and audits all ask for the same thing in different words, which is proof that something was tested and proof that it was fixed. RedMaw produces that record as a by-product of doing the work.
Evidence feeds
- PCI DSS 4.0
- GDPR
- SOC 2 and ISO-oriented programs
- NIS2
- DORA
- EU AI Act
Solutions
Start with the security problem
The use case changes. The security lifecycle does not.
Security validation
Move from possible exposure to proven exposure by testing whether a weakness can actually create unauthorized access, data exposure or another material security outcome.
Attack-path validation
Prioritize security work by what a finding can reach, not only by the severity label attached to the weakness that started the investigation.
Technology and SaaS
Protect tenant data while product teams ship quickly, answer enterprise security reviews and introduce AI features that create new application and model attack surfaces.
- Developer
- GitHub
- Secret
- Cloud Account
- Production
Financial services
Continuously validate exposure around customer financial data, payment flows and regulated digital services while preserving evidence for resilience and DORA-oriented security programs.
- Compromised Identity
- Core Banking Platform
- Customer Financial Records
Insurance
Validate the systems and identities around policyholder and claims data while supporting resilience, underwriting scrutiny and security programs that span modern and legacy technology.
- Compromised Identity
- Claims Platform
- Policyholder Records
Resources
Technical writing
BlogPerspective
The catalogue is not the boundary of the attack surface
A weakness does not start working on the day it gets an identifier, because it was already working. The identifier only marks the point at which defenders found out.
· 5 min read
GuidesGuide
What DORA actually requires of security testing
DORA changes the testing conversation from isolated evidence toward an operating resilience process that can be demonstrated.
· 4 min read
ResearchResearch
Four surfaces, fragmented security ownership
Organizations assign security ownership by technology. Attackers organize around reachable trust.
· 3 min read
Stop assuming you are secure. Prove it.
Continuously test what an attacker can actually reach, fix what matters, and prove the exposure is gone.