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AI security incident: @zereight/mcp-gitlab has multiple safety-control bypasses: execute_graphql read-only...

Source disclosure: September 15, 2026 | Published on Radar: October 14, 2026 | Source: GitHub Security Advisory | Classification confidence: 45%

Source disclosure is when the advisory appeared in this source (or was added to a catalog), not a confirmed date of exploitation. Radar publication is when this page became available.

This incident is part of the public archive and includes explicit AI-related signals from the cited source material. Review methodology.

@zereight/mcp-gitlab has multiple safety-control bypasses: execute graphql read-only + allow-list bypass, unauthenticated transports, session-exhaustion DoS Summary @zereight/mcp-gitlab exposes GitLab to an LLM agent while relying on read-only mode, a project allow-list, and transport auth as its safety controls. Five defects defeat those controls.

Why This Is AI-Related

This page is treated as AI-specific because the source material references llm, which places the issue inside an AI workflow, model, assistant, or supporting dependency rather than a generic software bulletin.

  • llm

Affected Workflow

Check inference endpoints, parsing layers, queues, and file processing jobs that support AI features.

Likely Attack Path

An attacker can drive resource exhaustion or crash conditions in the vulnerable component through crafted traffic or content.

Impact

The advisory describes an availability or resource-exhaustion path that can disrupt AI-serving components and supporting automation. Severity HIGH. Classification confidence 45%. Source channel GHSA.

Detection And Triage Signals

  • Latency spikes or worker restarts on AI-serving endpoints
  • Memory or CPU saturation after malformed requests or artifacts
  • Queue backlogs, timeouts, or repeated crash loops in model services

Recommended Response

  • Identify inference endpoints, parsing jobs, or queues that rely on the affected component.
  • Apply vendor mitigations and add rate, size, or input controls to reduce exhaustion risk during triage.
  • Monitor latency, restart frequency, queue backlog, and saturation indicators for active disruption.

Compliance And Business Impact

Availability failures can interrupt customer-facing AI features and force emergency rollback or capacity isolation.

Sources

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