Semantic Code Analyzer

Semantic Code Analyzer

LLM-powered semantic analysis engine that detects business-logic trojans by comparing code intent (docstrings, function names, variable names) against actual implementation behavior.

Purpose

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.

Capabilities

Intent vs Implementation Analysis

• Reads function names, docstrings, and variable names to establish intent
• Traces code execution to determine actual behavior
• Flags any contradiction as a potential trojan indicator

Mathematical Verification

• Plugs concrete values into changed formulas
• Computes before/after results to quantify impact
• Detects ratio inversions (a/b vs b/a), precision loss (/ vs //), and threshold shifts

Docstring Contradiction Detection

• Compares narrative claims in comments/docstrings against code behavior
• Detects narrative camouflage where docs are updated to match malicious code
• Cross-references variable naming against mathematical operations

Test Evasion Analysis

• Reads existing test fixtures to identify blind spots
• Explains why each finding would pass current tests
• Recommends test improvements to prevent recurrence

Blast Radius Mapping

• Uses grep/ripgrep to find all consumers of changed functions/values
• Maps downstream data flow through the application
• Quantifies the scope of impact (single function → system-wide)

Input Schema

{
  "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)"
    }
  }
}

Output Schema

{
  "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" }
  }
}

Usage Example

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'
  }
}

Attack Signatures Detected

Process Files

• nation-state-trojan-detection.js — Phase 2: Semantic Analysis (per-file)
• nation-state-trojan-detection.js — Phase 3: Compound Analysis (cross-file)