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Security: redhat-ai-americas/memory-hub

Security

SECURITY.md

Security Policy

MemoryHub is an agent memory component for OpenShift AI. It stores memories on behalf of users and agents under a scoped, governed model — taking vulnerability reports seriously is a first-class concern.

Reporting a Vulnerability

Please do not file public GitHub issues for security vulnerabilities.

Report vulnerabilities privately through GitHub's private vulnerability reporting:

If for any reason you cannot use GitHub's reporting flow, open a minimal public issue asking for a private contact channel (without disclosing details of the vulnerability).

When reporting, please include:

  • A description of the issue and the affected component (sdk, memory-hub-mcp, memoryhub-auth, memoryhub-core, memoryhub-ui, or the operator / deploy manifests)
  • Steps to reproduce or a minimal proof of concept
  • The version or commit SHA you observed the issue on
  • The impact you believe the issue has (confidentiality, integrity, availability; scoped or cross-tenant)

You should receive an acknowledgement within a few business days. We will work with you to confirm the issue, assess impact, and coordinate a fix and disclosure timeline.

Supported Versions

MemoryHub is pre-1.0 and under active development. Fixes are applied to main; only the latest release of each published package receives security updates:

Package Supported
memoryhub (SDK) Latest release on PyPI
memory-hub-mcp Latest deployed revision
memoryhub-auth Latest deployed revision
Others main branch only

Scope

In scope:

  • Authentication and authorization bypass
  • Tenant isolation violations (cross-scope memory access)
  • Credential or token leakage
  • Injection vulnerabilities in MCP tools, SDK, CLI, or the auth server
  • Container or deployment misconfigurations that weaken FIPS or compliance posture

Out of scope:

  • Findings that require compromising the underlying OpenShift cluster or PostgreSQL instance
  • Denial-of-service via resource exhaustion against unauthenticated endpoints (rate limiting is a deployment concern)
  • Issues only reproducible against example or scaffold code in demos/ or research/
  • Best-practice recommendations without a demonstrated impact

Disclosure

We prefer coordinated disclosure. Once a fix is available, we will credit the reporter (unless anonymity is requested) in the release notes and any GitHub Security Advisory published for the issue.

There aren't any published security advisories