CVE-2026-58482 (GCVE-0-2026-58482)

Vulnerability from cvelistv5 – Published: 2026-07-20 16:38 – Updated: 2026-07-20 17:33
VLAI
Title
Network-AI: ApprovalInbox HTTP server has no authentication — anyone can approve pending agent actions
Summary
Network-AI, a TypeScript/Node.js multi-agent orchestrator, has a shipped, exported, documented feature called `ApprovalInbox` (`lib/approval-inbox.ts`). It is the network surface of the human-in-the-loop Approval Gate, which `ApprovalGate` uses to require explicit human approval for high-risk operations. The HTTP server it exposes has no authentication of any kind and sets `Access-Control-Allow-Origin: *` on every route, including the state-changing `POST /approvals/:id/approve` and `/deny`. As a result, in versions 5.0.0 through 5.12.1, any party who can send an HTTP request to the inbox port — a co-located process, a container/SSRF on the same host, a remote client when the operator binds a non-loopback address, or any website the operator visits in a browser (via the wildcard CORS) — can enumerate pending approvals and approve them, defeating the entire human-in-the-loop control and causing the gated high-risk action (e.g. a shell command the agent was holding for review) to execute without consent. This issue is fixed in v5.12.2. `ApprovalInbox` now accepts a `secret` option. When set, the mutating endpoints `POST /:id/approve` and `POST /:id/deny` require an `Authorization: Bearer <secret>` header, validated in constant time with `crypto.timingSafeEqual`. `startServer()` already binds to `127.0.0.1` by default; operators exposing the inbox on a network must set a secret.
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-352 - Cross-Site Request Forgery (CSRF)
  • CWE-862 - Missing Authorization
Assigner
Impacted products
Vendor Product Version
Jovancoding Network-AI Affected: >= 5.0.0, < 5.12.2
Create a notification for this product.
Show details on NVD website

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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

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