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Security audit

huawei-cloud-cloudrobo-weight-layout

Security checks for vulnerabilities and agentic risk

Overview

The checkpoint workflow is coherent, but its claim that model files cannot execute code is unsafe for supported dependency versions.

Review the loader's safety guidance before use. Prefer safetensors, use maintained dependencies with relevant security fixes, and load checkpoints from trusted sources. Do not treat weights_only=True as a guarantee that arbitrary model files are safe. Installed dependency versions and actual checkpoint contents were unavailable for this review; no cloud credentials are needed.

Vulnerability Patterns
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
Vulnerability Patterns
  • MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
  • MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Findings (2)

Skill declares no tool scope ('permissions' or 'allowed-tools') but code capabilities were detected: file_read.

Medium
Category
MCP Least Privilege
Confidence
70% confidence
Finding

Without declared permissions the skill's intent is opaque and cannot be validated.

Content

No source excerpt is available for this finding.

The module claims to perform only path discovery, but also deserializes checkpoint contents.

Low
Category
Excessive Agency
Confidence
96% confidence
Finding

The module documentation at L08-L10 explicitly limits its behavior to locating the output root and selecting a checkpoint. In contrast, load_state_dict reads and deserializes checkpoint contents through safetensors or torch.load, crossing from path discovery into processing serialized model data. The weights_only=True restriction limits loading risks but does not resolve this documentation contradiction.

Content

No source excerpt is available for this finding.