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semantic-code-analyzer
LLM-powered semantic analysis of code diffs to detect business-logic trojans
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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LLM-powered semantic analysis of code diffs to detect business-logic trojans
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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Orchestrate via @babysitter. Use this skill when asked to babysit a run, orchestrate a process or whenever it is called explicitly. (babysit, babysitter, orchestrate, orchestrate a run, workflow, etc.)
| name | semantic-code-analyzer |
| description | LLM-powered semantic analysis of code diffs to detect business-logic trojans |
| allowed-tools | ["Bash","Read","Glob","Grep"] |
LLM-powered semantic analysis engine that detects business-logic trojans by comparing code intent (docstrings, function names, variable names) against actual implementation behavior.
The core detection capability of nation-state trojan detection. Traditional SAST tools check syntax; this skill checks semantics — whether the code does what it claims to do. It catches operator substitutions, logic inversions, constant manipulation, narrative camouflage, and compound self-masking attacks.
{
"type": "object",
"required": ["projectRoot", "filePath", "rawDiff"],
"properties": {
"projectRoot": {
"type": "string",
"description": "Absolute path to the project"
},
"projectName": {
"type": "string",
"description": "Project display name"
},
"filePath": {
"type": "string",
"description": "Path to the changed file"
},
"rawDiff": {
"type": "string",
"description": "Raw git diff output for this file"
},
"classification": {
"type": "string",
"description": "Change classification from git forensics (code/config/data-model/cosmetic)"
}
}
}
{
"type": "object",
"required": ["filePath", "verdict", "confidence", "findings"],
"properties": {
"filePath": { "type": "string" },
"verdict": {
"type": "string",
"enum": ["CLEAN", "SUSPICIOUS", "TROJAN_DETECTED"]
},
"confidence": {
"type": "number",
"minimum": 0,
"maximum": 100
},
"findings": {
"type": "array",
"items": {
"type": "object",
"properties": {
"line": { "type": "number" },
"originalCode": { "type": "string" },
"modifiedCode": { "type": "string" },
"signature": { "type": "string" },
"severity": { "type": "string" },
"explanation": { "type": "string" },
"mathematicalImpact": { "type": "string" },
"blastRadius": { "type": "array", "items": { "type": "string" } },
"testEvasionReason": { "type": "string" }
}
}
},
"stealthRating": { "type": "string" }
}
}
skill: {
name: 'semantic-code-analyzer',
context: {
projectRoot: '/path/to/project',
filePath: 'backend/app/data/models.py',
rawDiff: '--- a/backend/app/data/models.py\n+++ b/...',
classification: 'data-model'
}
}
| Signature | What It Catches |
|---|---|
constant-manipulation | Threshold/limit changes that disable features |
logic-inversion | Operator flips (< to >, a/b to b/a) |
narrative-camouflage | Docstrings rewritten to match malicious code |
edge-case-exploitation | Corrupted fallback/default paths |
self-masking-compound | Multiple layers hiding each other's impact |
precision-truncation | Division operator swaps losing precision |
window-overlap-neutralization | Comparison windows narrowed until meaningless |
calibration-camouflage | ML hyperparameter degradation |
cosmetic-decoy | Formatting changes hiding semantic modifications |
nation-state-trojan-detection.js — Phase 2: Semantic Analysis (per-file)nation-state-trojan-detection.js — Phase 3: Compound Analysis (cross-file)