Sentry Observability

Security checks across malware telemetry and agentic risk

Overview

This is a coherent Sentry observability skill, but users should handle telemetry, Sentry credentials, and mutation-capable CLI examples carefully.

Install this only if you want OpenClaw telemetry stored in Sentry. Use a dedicated Sentry project and least-privilege token, review the referenced plugin source before deploying it, scrub secrets and personal data from logs/traces, consider lowering trace sampling or disabling log forwarding, and require explicit confirmation before running Sentry API commands that change or delete resources.

SkillSpector

By NVIDIA

Vulnerability Patterns

Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code

Findings (6)

Context-Inappropriate Capability

Medium

Confidence: 94% confidence
Finding: The reference exposes a generic `sentry api` interface plus examples for state-changing operations such as resolving issues, assigning issues, creating projects, and deleting projects. In an agent skill framed as observability and investigation tooling, documenting arbitrary mutation capabilities broadens the action surface beyond read-only support and can enable unintended or unauthorized changes if an agent uses this reference naively.

Missing User Warnings

Medium

Confidence: 93% confidence
Finding: The skill instructs users to send errors, logs, traces, and events to a third-party SaaS without a prominent upfront warning about privacy, secrets exposure, or regulated data transfer. In practice, observability pipelines often capture stack traces, request metadata, user identifiers, and log contents, so enabling this without clear warning can lead to unintended exfiltration of sensitive data.

Missing User Warnings

Medium

Confidence: 97% confidence
Finding: The documentation includes a concrete `DELETE` example for removing a project without any warning about irreversibility, scope, or need for elevated approval. In an agent-consumable CLI reference, this makes destructive behavior easy to invoke and could lead to loss of monitoring configuration and observability data access.

Missing User Warnings

Medium

Confidence: 84% confidence
Finding: The `issue explain` feature is described as AI-powered root cause analysis and explicitly notes requirements like GitHub integration and code mappings, which implies code and issue context may be sent to or processed by an AI system. Without a privacy, data-sharing, or consent warning, users or agents may expose sensitive source, stack traces, or incident context unintentionally.

Missing User Warnings

Low

Confidence: 79% confidence
Finding: The event output is documented as including URL, user_id, environment, browser, OS, and full stack trace, which can contain personal data or sensitive operational details. Even though this is expected for observability tooling, omitting a privacy warning increases the risk of overexposure in shared terminals, logs, or automated agent outputs.

Missing User Warnings

Medium

Confidence: 91% confidence
Finding: The guide explicitly instructs operators to forward structured logs, errors, and performance traces to Sentry, but it does not warn that these telemetry streams can contain sensitive user prompts, message contents, tokens, identifiers, stack traces, or internal system metadata. In an observability plugin context this omission is significant because the documented behavior encourages broad third-party data export by default, including `tracesSampleRate: 1.0` and log forwarding, which increases the chance of privacy, compliance, or secret-leakage incidents.

VirusTotal

65/65 vendors flagged this skill as clean.

View on VirusTotal