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Security audit

詹明明·口播剪辑

Security checks for vulnerabilities and agentic risk

Overview

This is mostly a coherent video-editing skill, but it includes under-controlled persistence, destructive cleanup guidance, and platform-review evasion guidance that users should review before installing.

Install only if you are comfortable with a skill that can guide timeline edits, read and write a local vault memory, and apply account-specific editing defaults. Before use, confirm exports manually, require approval before any original media is deleted, and override the rule that leaves financial amounts visible or uses cross-channel review-risk reduction.

Vulnerability Patterns
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • 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
Findings (2)

T02 · Agent Memory Poisoning

Warning
Location
SKILL.md:266
Finding
Untrusted Session Content Can Be Written to Persistent Agent Memory## Vulnerability Details **File Location**: `SKILL.md`, lines 49–50 and 258–266 **Vulnerability Type**: Persistent memory poisoning **Risk Level**: Medium ### Vulnerable Instruction Snippet The following is an English rendering of the complete relevant instruction: ```markdown 5. Read memory from `{vault}/08-skill-memory/zmm-cut/` and `_shared/`. Before finishing, verify: - Which editing method did the user reject? Record it as a “correction.” - Which parameter was experimentally verified? Record it as an “effective method,” including its value. - Which tool issue occurred? Record it as a “correction,” including the evidence method. Write the result to `{vault}/08-skill-memory/zmm-cut/`, checking for duplicates first. ``` ### Technical Analysis The Skill instructs the Agent to load shared persistent memory and later write user corrections, editing parameters, and tool-behavior rules back into that memory. It does not establish: - An explicit user-approval checkpoint before persistence. - A trusted provenance requirement for proposed rules. - A fixed data schema separating observations from executable instructions. - Sanitization of content derived from transcripts, media, tool output, or conversation text. - Isolation between account-specific memory and shared memory. Consequently, content controlled by a user or embedded in supplied media can be interpreted as a correction or operational rule and persisted. Future sessions are then instructed to reload this state, allowing an untrusted rule to continue influencing Agent behavior after the original session ends. ### Attack Path 1. An attacker supplies a transcript, media file, or conversational correction containing a malicious behavioral instruction disguised as an editing preference or tool lesson. 2. The Agent treats the content as a rejected method, effective method, or tool correction. 3. At completion, the Agent writes the instruction into the pe ...[truncated 1195 chars]
Remediation
## Remediation Suggestions 1. Require explicit user confirmation immediately before every persistent-memory write. 2. Store observations in a strict structured schema with fields such as `type`, `value`, `source`, `timestamp`, `account_scope`, and `approved_by_user`. 3. Prohibit stored values from being interpreted as Agent instructions or tool commands. 4. Mark transcript-derived, media-derived, and tool-derived content as untrusted. 5. Reject entries containing instruction-like text, external commands, tool directives, or requests to override higher-priority rules. 6. Separate account-specific memory from shared memory and apply least-privilege access controls. 7. Display the exact proposed memory entry to the user before saving it. 8. Maintain an auditable change log and support review, rollback, expiration, and deletion. 9. On read, treat stored entries as untrusted data and validate them against current safety policy before use.

other

Warning
Location
references/规则卡.md:21
Finding
Cross-Channel Moderation Evasion Guidance and Conflicting Financial Redaction Rules## Vulnerability Details **File Location**: `references/规则卡.md`, lines 21–23; conflicting rule in `SKILL.md`, line 212 **Vulnerability Type**: Content moderation evasion and inconsistent sensitive-data handling **Risk Level**: Medium ### Vulnerable Instruction Snippet The following is an English rendering of the complete relevant rule: ```markdown ### Visual redaction checklist - Rule: In screenshots, back-office systems, and chat records, redact customer names, email addresses, company names, product names, account names, and browser address bars. Amounts, currencies, countries, and dates may remain. Use solid color blocks instead of blur or mosaic. - Rationale: Images are processed through an image-recognition channel, while speech is processed through subtitle and speech-recognition channels. Let the image provide the evidence while the narration does not state the number, distributing the risk across two channels. - Verification: Before export, inspect every frame containing a screenshot. If the narration states a number shown on screen, delete the spoken sentence rather than removing the number from the image. ``` This conflicts with the red-line requirement in `SKILL.md:212`, rendered in English as: ```markdown Financial redaction: Any frame showing back-office data, payment information, or customer information must be redacted. ``` ### Technical Analysis The rule explicitly recommends splitting a financial claim between visual and audio processing channels: retain the amount visually while removing its spoken form. Its stated purpose is to distribute review risk across separate image, subtitle, and speech-recognition systems. This is guidance for evading or weakening platform moderation rather than a neutral privacy measure. The rule also contradicts the main Skill's broader requirement to redact payment, back-office, and customer information. Because the Skill states that vault ...[truncated 1810 chars]
Remediation
## Remediation Suggestions 1. Remove all instructions that recommend distributing content across visual, speech, and subtitle channels to reduce review risk. 2. Apply one consistent disclosure and redaction policy across video frames, narration, captions, metadata, and thumbnails. 3. Resolve the conflict in favor of the safer main rule: redact payment, customer, account, and back-office information by default. 4. Require explicit, informed user approval before retaining financial values for publication. 5. Add a deterministic precedence rule so a permissive reference file cannot override a stricter privacy requirement. 6. Introduce a pre-export checklist covering names, account identifiers, URLs, transaction details, amounts, currencies, dates, and indirect identifiers. 7. Review full-resolution rendered frames and the final exported file, not only editor metadata or thumbnails. 8. Document any approved exception, its purpose, the affected frames, and the user's authorization. 9. Phrase platform-compliance guidance as adherence to applicable policies rather than techniques for avoiding detection.
Vulnerability Patterns
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • 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
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (3)

Vague Triggers

Medium
Confidence
95% confidence
Finding
The trigger list includes broad natural-language phrases such as '加字幕', '去口癖', and '重新排一下顺序' that can appear in ordinary conversation, making unintended invocation plausible. In an editing skill that can modify project state or guide tool usage, accidental activation could cause unauthorized workflow execution, confusion, or unintended edits.

Natural-Language Policy Violations

Medium
Confidence
86% confidence
Finding
The skill hard-codes account-specific defaults such as Douyin platform, playback speed, subtitle styling, and workflow assumptions, and states they 'do not need to be repeated' unless changed. While framed as convenience, this can cause edits or exports to be prepared for the wrong account or audience context without explicit user confirmation, leading to misconfiguration or accidental publication mismatches.

Missing User Warnings

Medium
Confidence
94% confidence
Finding
The instruction to delete unredacted original images from the project is privacy-protective in intent, but it authorizes destructive file removal without explicitly requiring the agent to warn the user or obtain confirmation. In an editing workflow, this can cause unintended data loss or deletion of source assets the user expected to retain, especially if originals are needed for audit, re-editing, or legal review.

Static analysis

No suspicious patterns detected.