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Security audit

context-token-budget

Security checks for vulnerabilities and agentic risk

Overview

This skill is a local token-budget checker that reads user-supplied text or files and does not show hidden persistence, network use, destructive actions, or privilege escalation.

Installers should expect a simple local CLI that can read a user-specified file to estimate token usage. Consider narrowing activation terms if accidental invocation would be annoying, and treat its token counts as rough estimates rather than exact model tokenizer results.

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
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Findings (4)

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The trigger terms are very broad, including generic words like 'context' and 'token', which can cause the skill to activate in ordinary conversations unrelated to budgeting. This increases the chance of unintended invocation, unnecessary context processing, and user confusion, though it does not by itself enable code execution or direct data exfiltration.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
84% confidence
Finding

The description advertises bilingual/Chinese behavior as part of the skill's operation without indicating that the user can opt in or out. This can override user language expectations, cause unwanted output shaping, and in agent systems may lead to policy drift or unnecessary prompt expansion.

Content

No source excerpt is available for this finding.

Autonomous Decision Making

Medium
Category
Excessive Agency
Confidence
85% confidence
Finding

Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Content

Scanner excerpt · SKILL.md (reported line 80)May include surrounding context.

md
| Gated | Minimal privilege, fail-closed exit codes, dangerous ops denied by default |

### Safety boundary
- Static analysis only; never auto-executes external commands.
- On risk detection → FAIL (fail-closed); human decides.
- Does not delete / modify / publish anything on the user's behalf.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
82% confidence
Finding

The file presents the skill name and primary description in both English and Chinese, but does not indicate whether this bilingual requirement is optional, user-selectable, or tied to a justified region-specific constraint. Under the stated policy, forcing a specific language or locale without opt-in can be a natural-language policy issue.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.