Authenticated penetration testing for Government
Authenticated penetration testing for government. Public bodies require on-premise systems so citizen data never leaves the country.
Self-Hosted Authenticated Security Scanning for Government
Public bodies manage vast volumes of citizen records and critical infrastructure that demand strict data sovereignty. Allmaz provides a self-hosted AI testing platform designed to ensure sensitive data never leaves the country, allowing government agencies to identify vulnerabilities within their web applications and APIs without relying on external SaaS dependencies. By keeping all scan data, credentials, and reports on internal infrastructure, agencies can maintain total control over their security posture. As one of the three core engines of the Argus platform, this security scanner shares a unified runtime, model layer, credential store, and cost ledger with the QA and AI engines. Unlike traditional scanners that stop at the login page, this system utilizes authenticated dynamic scanning to penetrate the actual authenticated surface of an application. By operating as a real logged-in user, the platform provides a comprehensive security analysis of the internal endpoints and APIs that are most critical to government operations.
Solving Critical Government Security Challenges
Ensures absolute data sovereignty by keeping all scan data, credentials, and reports on your own private infrastructure.
Eliminates external SaaS dependencies to protect sensitive citizen data from third-party exposure.
Overcomes the 'login wall' via authenticated scanning to test the actual functional surface of public services.
Prevents unauthorized scanning by restricting all operations to an explicit, deliberately managed allow-list of approved targets.
Provides full audit transparency and actionable intelligence through detailed severity-based HTML and JSON reports.
Maintains platform agility through a modular open-source engine that can be upgraded without disrupting the broader ecosystem.
Enterprise-Grade Security Capabilities
Authenticated Dynamic Scanning
Utilizes a scripted login via an encrypted credential store to obtain session cookies and bearer tokens, allowing the scanner to operate as a real logged-in user.
Synthesized API Mapping
Endpoints discovered during login and crawling seed a synthesized API spec, ensuring the scan reaches deep authenticated surfaces rather than stopping at the login page.
Self-Hosted AI Architecture
As part of the Argus platform, the engine shares a runtime, model layer, and credential store, keeping all operations within your controlled environment.
Modular Scanner Engine
Powered by Deep Eye, an open-source engine driven through a CLI contract, allowing for upgrades or replacement without impacting the broader platform.
AI-Driven Payload Generation
The integrated model is used specifically for payload generation and finding triage, utilizing a text-in, text-out approach.
The Authenticated Testing Process
Frequently Asked Questions
How does this solution handle data sovereignty?
The platform is entirely self-hosted, meaning all scan data, credentials, and reports remain on your own infrastructure with no external SaaS dependency.
What happens if the scanner cannot authenticate?
Following a strict honest-failure rule, a scanner that cannot authenticate is treated as an environment failure rather than a security finding.
Can the AI model see sensitive visual data?
No. The model is used strictly for payload generation and triage using a text-in, text-out mechanism; it does not utilize vision.
How are the scan targets managed to prevent accidents?
Scans run only against an explicit allow-list of approved targets; a target must be added deliberately before it can be scanned.
Is the scanning engine proprietary or replaceable?
The scanner uses Deep Eye, an open-source engine driven through a CLI contract, which allows it to be upgraded or replaced without touching the platform.
Secure Your Public Infrastructure
Contact Allmaz to implement self-hosted, authenticated penetration testing that respects government data sovereignty.
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