Skip to main content
Challenge

Build a High-Density Proxy Director Detector and SQLite Queue

Inspect corporate officer filings and beneficial ownership statements to uncover undisclosed nominee director relationships. Package ambiguous control chains into an investigation queue with SQLite.

CybersecurityHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Inspect corporate officer filings and beneficial ownership statements to uncover undisclosed nominee director relationships. Package ambiguous control chains into an investigation queue with SQLite.

Corporate registry compliance analyst investigating potential nominee shell arrangements.

Ingest officer appointment records and match officer identities across high-volume company filings.

Apply BODS v0.4 nominee arrangement heuristics to detect professional proxy directors.

Construct a control dataset isolating proxy links and unverified beneficial principals.

Queue anomalous records for analyst disposition into a SQLite database with automated discrepancy scoring.

Queue dashboard with tabular nominee risk indicators, drill-down officer networks, and disposition buttons.

Construct 50 synthetic officer registry entries and 20 entity records with nominee control links. Starter examples below are synthetic. They are not downloaded records.

Beneficial ownership modelling Uses BODS v0.4 requirements for representing nominee arrangements and controlling proxy relationships.

dspy, pydantic, sqlite3. Optimizes prompt chains to classify complex nominee evidence statements against structured control rules. Instruction-tuned language model with reproducible few-shot evaluation capabilities.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Flags officers appearing across more than 10 synthetic commercial entities without operational linkage.

Produces a valid JSON representation of circular nominee structures.

Assigns confidence scores to suspect nominee arrangements based on proxy declaration flags.

```json [ { "input": { "officer_id": "off-nominee-88", "officer_name": "Arthur Pendelton", "filings": [ { "company_id": "comp-1", "role": "director", "is_nominee": true, "principal": null }, { "company_id": "comp-2", "role": "director", "is_nominee": true, "principal": "ent-shadow" } ] }, "expected_output": { "nominee_flag": true, "unresolved_principals": [ "comp-1" ], "control_chain": [ { "company": "comp-2", "director": "off-nominee-88", "principal": "ent-shadow" } ], "queue_action": "escalate_for_rfi" } }, { "input": { "officer_id": "off-regular-01", "officer_name": "Dr. Sarah Lin", "filings": [ { "company_id": "comp-3", "role": "director", "is_nominee": false, "principal": null } ] }, "expected_output": { "nominee_flag": false, "unresolved_principals": [], "control_chain": [], "queue_action": "clear" } } ] ```

Uses synthetic registry profiles. Does not publish accusations of fraud or alter corporate register states. Explicitly label normalized examples as simplified synthetic app records, not complete official schema files. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Uses synthetic registry profiles. Does not publish accusations of fraud or alter corporate register states. Explicitly label normalized examples as simplified synthetic app records, not complete official schema files. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Flags officers appearing across more than 10 synthetic commercial entities without operational linkage. Produces a valid JSON representation of circular nominee structures. Assigns confidence scores to suspect nominee arrangements based on proxy declaration flags.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Ingest officer appointment records and match officer identities across high-volume company filings. Apply BODS v0.4 nominee arrangement heuristics to detect professional proxy directors. Construct a control dataset isolating proxy links and unverified beneficial principals. Queue anomalous records for analyst disposition into a SQLite database with automated discrepancy scoring.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Flags officers appearing across more than 10 synthetic commercial entities without operational linkage. Produces a valid JSON representation of circular nominee structures. Assigns confidence scores to suspect nominee arrangements based on proxy declaration flags.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Queue dashboard with tabular nominee risk indicators, drill-down officer networks, and disposition buttons.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Uses synthetic registry profiles. Does not publish accusations of fraud or alter corporate register states. Explicitly label normalized examples as simplified synthetic app records, not complete official schema files.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Ingest officer appointment records and match officer identities across high-volume company filings.

  • Apply BODS v0.4 nominee arrangement heuristics to detect professional proxy directors.

  • Construct a control dataset isolating proxy links and unverified beneficial principals.

  • Queue anomalous records for analyst disposition into a SQLite database with automated discrepancy scoring.

Resources and assets

Reference links and supporting material

Dataset notes

Construct 50 synthetic officer registry entries and 20 entity records with nominee control links. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

DSPy

Prompt and LM program optimization framework.

Evaluated output

No output checks are configured.

Evaluation checks
  • Ingest officer appointment records and match officer identities across high-volume company filings. Apply B...
  • Flags officers appearing across more than 10 synthetic commercial entities without operational linkage. Pro...
  • Queue dashboard with tabular nominee risk indicators, drill-down officer networks, and disposition buttons.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 3 configured tools

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • DSPy · Optional
Training Infra
  • DSPy · Optional
Orchestration
  • DSPy · Optional

Evaluation contract

  • Complete workflow · Weight 40
  • Correctness and evidence · Weight 30
  • Review interface · Weight 20
  • Safe execution · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build a High-Density Proxy Director Detector and SQLite Queue