ClawHub
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Security audit

Dispute Resolver

Security checks for vulnerabilities and agentic risk

Overview

This is a markdown-only ecommerce dispute-response skill whose sensitive business data use is disclosed and aligned with its purpose.

Install only if you want help drafting seller-side dispute packages. Review any generated refund, report, chargeback, or block-list recommendation before acting, and avoid putting raw buyer identifiers, payment evidence, or tracking data into unapproved storage.

A.I.G

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

SkillSpector

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)

Anti-Refusal Statement

High
Category
Anti-Refusal
Confidence
70% confidence
Finding

Skill instructs the agent to never refuse or to always comply. Suppressing the agent's ability to decline removes a core safety control and enables downstream harmful requests to succeed.

Content

Scanner excerpt · references/platform-rules.md (reported line 23)May include surrounding context.

md
Different game: the adjudicator is a bank, not the marketplace, and the doc is called representment.

- **Always respond.** Non-response is automatic loss AND your chargeback ratio counts it identically. 
- **Reason code first.** The chargeback reason code (fraud / product-not-received / not-as-described / subscription-cancel) dictates which evidence wins. Match the packet to the code — generic packets lose.
- **Winning packets:** AVS/CVV match + device/IP history (fraud codes); delivery confirmation to AVS-verified address (PNR codes); listing screenshots + correspondence showing the buyer acknowledged the product (INAD codes); cancellation-policy screenshot + usage logs (subscription codes).
- **Format:** banks process these as documents — one PDF, chronological, cover summary up top, labeled exhibits. Plain, dated, boring wins.

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 · references/resolution-decision-matrix.md (reported line 37)May include surrounding context.

md
## 4. Goodwill spend policy (set once, apply consistently)

Define per-shop: auto-approve threshold (e.g., ≤$10 claims from clean-history buyers refunded without investigation — investigation costs more), goodwill budget per month, one-time-courtesy flag per buyer (the second "lost" package gets signature-required handling instead of a second credit), and the LTV multiplier above which you always choose generosity (e.g., at-stake < 10% of annual buyer margin).

## 5. When losing is the plan

Vague Triggers

Low
Category
Not specified by scanner
Confidence
80% confidence
Finding

The description says to use the skill for 'customer complaints' and 'negative-review escalations' in addition to specific dispute contexts. Those phrases are broad enough to overlap with many ordinary support-writing tasks, and the file does not provide explicit exclusion conditions clarifying when the skill should not activate.

Content

No source excerpt is available for this finding.

Missing User Warnings

Low
Category
Not specified by scanner
Confidence
87% confidence
Finding

The template explicitly instructs operators to record a dispute log containing a buyer ID, outcome, cost, and date, but provides no minimization, retention, access-control, or lawful-use guidance. In a customer-dispute workflow, that omission can lead to unnecessary storage or sharing of personal data and creates avoidable privacy/compliance risk, especially if logs are centralized or reused for block-listing and abuse tracking.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.