Critical: Obfuscation Not Applied in run_experiment() - Issue #79 Results May Be Tainted #81
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Description
Critical Bug: Obfuscation Not Working in Pattern Validation
Problem Summary
The Issue #79 pattern taxonomy validation claimed to use obfuscation testing, but the run_experiment() method does not obfuscate dates before sending them to the LLM. This means the LLM received real dates like "2024-01-02" instead of anonymized dates like "Day T+0".
Evidence
1. Validation Script Calls Non-Obfuscated Method
File: scripts/validation/validate_pattern_taxonomy.py:157
result = self.agent.run_experiment(
experiment_description=experiment_desc, # Contains real date!
date=date_str # Real date: "2024-01-02"
)2. Experiment Description Contains Real Dates
File: scripts/validation/validate_pattern_taxonomy.py:276-281
'0dte_hedging': (
f"Analyze {self.symbol} 0DTE option hedging flows on {date_str}."
# ^^^ This is "2024-01-02", not obfuscated!
)3. LLM Planning Prompt Exposes Date
File: src/agents/market_mechanics_agent.py:494
planning_prompt = f"""
EXPERIMENT REQUEST: {experiment_description}
DATE: {date} # ← LLM sees real date here!4. Analysis Prompt Also Contains Real Date
File: src/agents/market_mechanics_agent.py:652
analysis_prompt = f"""
You are analyzing market data for this experiment: {experiment_description}
# ^^^ Contains "Analyze SPY on 2024-01-02" with real date5. Output Files Confirm No Obfuscation
File: reports/validation/pattern_taxonomy/0dte_hedging_SPY_2024Q1.yaml
- date: '2024-01-02'
date_obfuscated: '2024-01-02' # Should be "Day T+0" if obfuscated!Where Obfuscation DOES Work
The run_batch_experiments() method (line 295-387) does obfuscate properly:
obfuscator = DataObfuscator() if use_obfuscation else None
date_mapping = obfuscator.obfuscate_dates(dates)But the validation script used run_experiment() (singular), not run_batch_experiments() (plural).
Impact Assessment
Severity: CRITICAL
- All Issue Pattern Taxonomy: Focus on Core Mechanical Patterns #79 validation results are potentially tainted
- LLM may have used temporal knowledge (Q1 2024 = post-Fed pivot, tax loss harvesting end)
- Claims of "mechanical pattern detection without context" are invalidated
Mitigation Factors
- Training Cutoff: o3-mini likely trained on data through Oct 2023, so couldn't know specific 2024 events
- Pattern Consistency: 53/53 detection rate suggests real mechanics, not date memorization
- Out-of-Sample Period: Q1 2024 was after training cutoff
Cannot Claim
- ❌ "Obfuscation testing proves patterns work without temporal context"
- ❌ "LLM detected patterns blind to dates/events"
Can Still Claim (With Caveats)
- ✅ "LLM detected patterns on out-of-sample data (post-training cutoff)"
- ✅ "Consistent detection across 53 dates suggests robust pattern recognition"
- ✅ "Pattern mechanics align with academic literature (Buis et al. 2024, Jeannin et al. 2008)"
Fix Required
Option 1: Add Obfuscation to run_experiment()
def run_experiment(self, experiment_description: str, date: str, obfuscate: bool = True) -> Dict:
# Obfuscate date before LLM calls
if obfuscate:
obfuscator = DataObfuscator()
date_mapping = obfuscator.obfuscate_dates([date])
obfuscated_date = date_mapping[date]
# Replace date in experiment_description
experiment_description = experiment_description.replace(date, obfuscated_date)
date_for_llm = obfuscated_date
else:
date_for_llm = date
# Use date_for_llm in all LLM prompts
tool_plan = self._plan_experiment_tools(experiment_description, date_for_llm)
...Option 2: Use run_batch_experiments() for Validation
Modify validator to use the already-working batch method:
# Instead of loop calling run_experiment()
batch_result = self.agent.run_batch_experiments(
dates=dates,
experiment_template=pattern_experiment_template,
use_obfuscation=True # This works correctly!
)Action Items
- Immediate: Fix
run_experiment()to support obfuscation - Validation: Re-run Issue Pattern Taxonomy: Focus on Core Mechanical Patterns #79 tests with proper obfuscation
- Comparison: Compare new results vs. old results (expect similar if patterns are real)
- Documentation: Update CLAUDE.md to reflect corrected methodology
- Reports: Regenerate all
reports/validation/pattern_taxonomy/*.yamlfiles - Integrity Check: If results change significantly, investigate why
Files to Modify
src/agents/market_mechanics_agent.py- Add obfuscation torun_experiment()scripts/validation/validate_pattern_taxonomy.py- Use obfuscated datesdocs/guides/data-obfuscation.md- Document correct usageCLAUDE.md- Update Issue Pattern Taxonomy: Focus on Core Mechanical Patterns #79 status
Timeline
Priority: HIGH - Needed before advisor presentation
Estimated Fix: 2-4 hours
Re-validation: 1-2 hours (53 dates with cache)
Related Issues
- Issue Pattern Taxonomy: Focus on Core Mechanical Patterns #79: Pattern Taxonomy Validation (results need re-validation)
- Issue LLM Pattern Analysis & System Optimization Enhancements #78: Batch LLM Processing (already has working obfuscation)