Osint Investigation

OSINT Investigation — Public Records Cross-Reference

Investigative framework for public-records OSINT: government contracts, corporate filings, lobbying, sanctions, offshore leaks, property records, court records, web archives, knowledge bases, and global news. Resolve entities across heterogeneous sources, build cross-links with explicit confidence, and produce structured evidence chains.

Python stdlib only. Zero install. Most sources work with no API key.

When to Use

Use when the user asks for:

• "follow the money" — government contracts, lobbying → legislation, sanctions
• Corporate due diligence — who controls company X, where incorporated, board members, filings
• Sanctions screening — is entity X on OFAC SDN, ICIJ offshore leaks
• Property ownership — find recorded deeds/mortgages by name or address
• Litigation history — find federal + state court opinions
• Multi-source entity resolution where naming varies (LLC suffixes, abbreviations)
• Evidence-chain construction with explicit confidence levels
• "what's been said about X" — international news + Wikipedia + Wayback Machine

Core Sources

Corporate & Financial

Property & Courts

Archives & Knowledge

Methodology

1. Entity Resolution

Before cross-referencing, resolve the entity across sources:

• Normalize names (LLC suffixes, abbreviations, DBA aliases)
• Identify unique identifiers (EIN, LEI, CIK, OpenCorporates ID)
• Build a canonical entity record with all known aliases

2. Source-by-Source Query

For each relevant source, query by entity name or identifier:

# SEC EDGAR — search for company filings
curl -s "https://efts.sec.gov/LATEST/search-index?q=%22Company+Name%22" | python3 -c "..."

# USAspending — federal contracts to entity
curl -s -X POST "https://api.usaspending.gov/api/v2/search/spending_by_award/" -d '{"filters":{...}}'

# OFAC SDN — check sanctions list
curl -s "https://www.treasury.gov/ofac/downloads/sdn.csv" | grep -i "entity name"

3. Cross-Link Analysis

Build explicit cross-links between sources:

• Same entity appearing in multiple sources
• Timing correlation (contract award → lobbying registration → legislation)
• Shared addresses, phone numbers, officers across entities

4. Confidence Scoring

For each finding, assign confidence:

• High: Official government record, multiple corroborating sources
• Medium: Single official source, or multiple unofficial sources
• Low: Single unofficial source, unverified

5. Evidence Chain

Construct an evidence chain showing how findings connect:

[Source A: fact 1] → [Source B: fact 2] → [Inference: conclusion]
  confidence: High      confidence: Medium     confidence: Medium

Output

Produce a structured investigation report:

# OSINT Investigation: [Entity / Topic]

## Executive Summary
[2-3 paragraph overview of findings]

## Entity Profile
- **Canonical Name**: ...
- **Aliases**: ...
- **Identifiers**: EIN, LEI, CIK, etc.
- **Known Addresses**: ...

## Findings by Source

### SEC EDGAR
[Findings with dates, filing types, key data]

### USAspending
[Contract awards, amounts, dates, agencies]

### OFAC SDN
[Sanctions status: CLEAR / MATCH (with details)]

### [Other sources...]

## Cross-Link Analysis
[Explicit connections between findings across sources]

## Evidence Chain
[Step-by-step reasoning from raw data to conclusions]

## Confidence Assessment
[Summary of confidence levels for key conclusions]

## Sources
[All URLs queried, with access dates]

Save to .poirot/outputs/osint-{entity}-{YYYYMMDD}.md.

Pitfalls

• Name variants: "Acme LLC", "Acme L.L.C.", "Acme" may be different entities. Normalize but don't assume.
• Stale data: Public records may lag. Note the record's date.
• False positives: Sanctions list partial name matches need full record review. Don't report a match without verifying the full entry.
• Rate limits: Government APIs may rate-limit. Add delays between requests.
• Legal caution: OSINT findings are leads, not proof. Frame as "evidence suggests" not "proven".