Self-hosted vs cloud security scanning
Self-hosted vs cloud security scanning: a balanced comparison for Azerbaijani business, grounded in how Argus Pentest works.
Enterprise Security Scanning Strategy
Organizations today face a critical choice between the convenience of cloud-based security scanning and the rigorous control of self-hosted deployments. While SaaS solutions offer rapid setup, they often struggle with the complexities of authenticated access and data residency. A self-hosted AI testing platform solves these challenges by integrating security audits directly into the organization's own infrastructure, ensuring that sensitive scan data, credentials, and reports never leave the internal environment. As one of the three core engines of the Argus platform, this security module operates in a unified deployment alongside QA and AI engines. By sharing a single console, sign-in, and encrypted credential store, the system streamlines the transition from functional testing to security auditing. This integrated approach allows for authenticated dynamic security scanning of enterprise web applications and their APIs, moving beyond the surface-level analysis of unauthenticated scans to uncover vulnerabilities hidden behind login walls.
Key Advantages of Self-Hosted Scanning
Complete data sovereignty by keeping all scan data, credentials, and reports on your own infrastructure without external SaaS dependencies.
Deep authenticated scanning that operates as a real logged-in user via session cookies and bearer tokens retrieved from an encrypted store.
High-fidelity reporting through a live re-verification process that quarantines unverified findings to prevent them from inflating severity totals.
Strict environment control via an explicit allow-list, ensuring scans are only executed against deliberately approved targets.
Architectural flexibility using the open-source Deep Eye engine, which can be upgraded or replaced via CLI contracts without platform disruption.
Honest failure reporting that distinguishes between environment issues, such as authentication failures, and actual security vulnerabilities.
Core Capabilities of Argus Pentest
Authenticated Scanning
Utilizes a scripted login through the QA engine’s encrypted credential store to obtain session cookies and bearer tokens, enabling access to the authenticated surface.
AI-Driven Payloads
Employs AI models for precise payload generation and finding triage using a text-in, text-out approach, excluding vision-based processing.
Strict Target Control
Enforces a rigorous security boundary where scans run exclusively against an explicit allow-list of approved targets.
Automated API Synthesis
Seeds a synthesized API specification from endpoints discovered during the login and crawl process to ensure comprehensive API coverage.
Intelligent Triage
Automatically re-checks every finding against the live target; findings without evidence or reachable endpoints are quarantined from severity totals.
The Self-Hosted Scanning Process
Frequently Asked Questions
How does the system handle targets that require authentication?
Targets marked as requiring a login cannot be scanned unauthenticated. The system will refuse the scan entirely rather than running it against a login wall, which prevents the scanner from misinterpreting repeated error responses as multiple exploits.
What happens if the scanner fails to authenticate during a session?
Following the same 'honest-failure' rule as the QA engine, a failure to authenticate is classified as an environment failure rather than a security finding. If the target was reached but could not be exercised, the scan is marked as inconclusive.
How are false positives minimized in the final reports?
Every finding is re-checked against the live target before being counted. If a finding cannot be stood up—due to an unreachable endpoint, a uniform response, or lack of evidence—it is quarantined and excluded from the severity totals.
Can the scanning engine be customized or updated?
Yes. The platform utilizes Deep Eye, an open-source engine driven strictly through its CLI contract. This allows the engine to be upgraded or replaced entirely without requiring changes to the broader platform.
Does the AI model process visual data during the scan?
No. The AI model is used exclusively for payload generation and finding triage on a text-in, text-out basis; it does not utilize vision capabilities.
Secure Your Infrastructure Locally
Experience the control and depth of self-hosted authenticated security scanning with Allmaz.
Request a demo