Symosis tests AI applications, retrieval systems, copilots, and agents against agreed adversarial scenarios.
We examine whether manipulated inputs can expose sensitive information, bypass access controls, misuse tools, or trigger unintended actions.
AI security depends on the model alongside application logic, identities, retrieval sources, tools, and infrastructure.
Symosis connects adversarial behavior to security boundaries and business consequences. Testing focuses on what the application can access and do under the agreed conditions.
Assess direct inputs and malicious instructions encountered through documents, retrieval sources, external content, or tool responses.
Determine whether manipulated behavior leads to unauthorized disclosure or action.
Test selected paths for restricted-document access, cross-user or cross-tenant retrieval, sensitive-data disclosure, and relevant access-revocation behavior.
Evaluate unauthorized tool invocation, excessive permissions, manipulated parameters, approval bypass, and actions exceeding the intended task.
Assess authentication, authorization, session isolation, integration weaknesses, and unsafe handling of generated content.
Where relevant, examine manipulated knowledge sources, persistent malicious instructions, execution loops, resource limits, and failure behavior.
Validated findings include:
We distinguish demonstrated impact from hypothetical consequences. Where behavior varies, we document the conditions and repeatability observed.
Define Scope
Agree on applications, environments, accounts, permitted techniques, data handling, and operational boundaries.
Map the Attack Surface
Review architecture, identities, retrieval sources, APIs, tools, and important workflows.
Execute Scenarios
Combine targeted manual testing with appropriate tooling to evaluate the agreed threats and abuse cases.
Validate and Prioritize
Confirm findings, document evidence, and prioritize remediation.
Review and Retest
Walk through results with your team. Where included, retest fixes against the original scenarios.
Symosis can help implement architecture changes, access restrictions, application safeguards, and monitoring improvements.
Client evidence · pending approval
A sanitized technical example, sample deliverable or approved case study for this service will appear here once approved. No results are shown until then.
Malicious instructions placed in content the model later reads, such as a document, web page or email, rather than typed by the user.
It is complementary. It focuses on model behavior, retrieval and tools, and is usually combined with conventional testing of the surrounding application.
Before deployment, before expanding capability, and after material changes to architecture or controls.
Tell us what your application does, which data and tools it accesses, and what you need to validate before deployment or expansion.