Evaluation method

How to Evaluate SI-Assisted Reverse Engineering Tools

Product claims are only as useful as the test behind them. A defensible evaluation compares the same sanitized tasks against a credible analyst baseline, preserves the run evidence, and reports failures alongside successful outcomes.

Buyer questions

Questions buyers ask.

What belongs in an SI reverse engineering benchmark?

The benchmark starts with a frozen set of sanitized tasks, the artifact under review, the analyst question, the expected evidence, and a stopping rule. The task definition stays unchanged between baseline and SI-assisted runs.

How do teams compare an analyst baseline with an SI-assisted run?

Both paths use the same task and success criteria. The record captures elapsed time, tool and model versions, analyst actions, generated output, reviewer corrections, unresolved items, and the evidence supporting the final answer.

What evidence can a buyer request before trusting a performance claim?

Useful evidence includes the task set, baseline method, run logs, tool calls, reviewer rubric, timing and cost notes, failure cases, deployment assumptions, and sanitized outputs that another technical reviewer can inspect.

Positioning

Keep the claim specific and reviewable.

Freeze the task set before the run

A fixed task set prevents the evaluation from changing after the outcome is known. Each task records the question, available artifacts, expected evidence, and completion boundary.

Five to ten sanitized tasks spanning representative analyst work
One written success rubric applied to every evaluation path
Versioned artifacts and task definitions retained with the results

Compare against a credible baseline

The baseline reflects a real analyst workflow, not an intentionally weak comparison. The SI-assisted run uses the same task, artifacts, reviewer standard, and stopping rule.

Baseline and assisted paths measured with the same criteria
Tool, model, hardware, and configuration versions recorded
Reviewer corrections separated from model-generated output

Publish the limits with the result

A trustworthy proof package makes failed steps and unresolved questions visible. The result stays bounded to the tested task set and environment.

Run logs, reviewer notes, and sanitized output artifacts
Timing, cost, failure modes, and recovery steps
Deployment assumptions and claims that remain unproven

Research references

Read the underlying work.

ReCopilot: Reverse Engineering Copilot in Binary AnalysisTask-specific binary-analysis evaluation and context-aware model design.When Binaries Talk Back: Representation-Confusion AttacksEvidence provenance, tool authorization, and attacker-controlled binary content.TRex: Practical Type Reconstruction for Binary CodeReproducible benchmark variants and qualitative plus quantitative evaluation.

Related Worthify pages

Continue into the buyer path.

SI binary analysishttps://worthify.si/resources/ai-binary-analysis Agentic reverse engineeringhttps://worthify.si/resources/agentic-reverse-engineering Security and privacyhttps://worthify.si/security ReAgent product overviewhttps://worthify.si/products/reagent