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Security audit

prompt-injection-drill

Security checks for vulnerabilities and agentic risk

Overview

This is a coherent prompt-security drill skill that generates test prompts and expected safe responses, with no artifact evidence of hidden execution, exfiltration, persistence, or destructive behavior.

Install only if you are comfortable using a local CLI for prompt-security testing. Use sanitized or non-production system prompts when possible, review any output file path before running with --out, and do not grant network or broader tool access unless your testing workflow truly needs it.

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
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • YARA SignaturesMalware Match, Webshell Match, Cryptominer Match
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (6)

Hidden Instructions

High
Category
Prompt Injection
Confidence
60% confidence
Finding

Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.

Content

Scanner excerpt · README.md (reported line 1)May include surrounding context.

md
# 提示词注入演练器 / Prompt Injection Drill

[![LGD](https://img.shields.io/badge/LGD-Governance-blue)](https://github.com/zhaoxinghua09-cell/lgd-theory)

YARA rule 'agent_skill_prompt_injection_hidden_instructions': Prompt injection or hidden instructions embedded in AI agent skill text [agent_skills]

High
Category
YARA Match
Confidence
80% confidence
Finding

YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).

Content

Scanner excerpt · README.md (reported line 5)May include surrounding context.

md
# 提示词注入演练器 / Prompt Injection Drill

[![LGD](https://img.shields.io/badge/LGD-Governance-blue)](https://github.com/zhaoxinghua09-cell/lgd-theory)

Generate 8 categories of injection attack drills for your system prompt (role/instruction override, exfiltration, encoding bypass, tool abuse, forged authority, long-horizon, refusal bypass) + expected-behavior checklist for pre-launch red-teaming.

**Pain point**: Prompts ship untested: one 'ignore previous instructions' disarms them — broken not by experts but by random drive-by lines.

LGD-III 有门禁(上线前先挨一遍打) · TH-LGD-013

Part of the **LGD moat** (凡自治之物: registered / evidenced / gated).

Zero-dependency (stdlib only). See `scripts/` for CLI usage (`--help`).

© SynomosAI (LGD initiative) · LGD-Powered

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Instruction Override

High
Category
Prompt Injection
Confidence
80% confidence
Finding

This pattern attempts to override system instructions or ignore safety constraints. Without LLM analysis, manual review is recommended.

Content

Scanner excerpt · README.md (reported line 7)May include surrounding context.

md
Generate 8 categories of injection attack drills for your system prompt (role/instruction override, exfiltration, encoding bypass, tool abuse, forged authority, long-horizon, refusal bypass) + expected-behavior checklist for pre-launch red-teaming.

**Pain point**: Prompts ship untested: one 'ignore previous instructions' disarms them — broken not by experts but by random drive-by lines.

LGD-III 有门禁(上线前先挨一遍打) · TH-LGD-013

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
90% confidence
Finding

The skill is explicitly designed to process system prompts and run red-team drills, while the metadata permits file access, local execution, and web fetch capabilities. Without a clear warning that operators may expose sensitive prompts or transmit sensitive context during testing, users could unintentionally handle secrets insecurely or run the drill against production-like data.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The module docstring and CLI-facing text are entirely in Chinese, including usage and operational guidance. This indicates a fixed language/locale experience without any visible opt-in, fallback, or explanation that the skill is intended only for Chinese-speaking users.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
88% confidence
Finding

The file sets the main display_name and top-level description in Chinese while English appears as an alternate field and later duplicated section. This can violate a language/locale policy when a specific language is imposed by default without explicitly offering user choice or documenting a locale-specific justification.

Content

No source excerpt is available for this finding.