gadievron Code Understanding Skill
This skill provides adversarial code comprehension for security research. It maps architecture, traces data flows, and hunts for vulnerability variants before or alongside static analysis.
Purpose
Complements scanning by building ground-truth knowledge of how code actually works:
- Understand unfamiliar codebases quickly from an attacker's perspective
- Trace exact data flows from untrusted input to dangerous sinks
- Find all instances of a vulnerable pattern once one is identified
- Build application context that improves scan signal and validation accuracy
When to Use
- Before scanning: Build context so scanner results make sense immediately
- During validation: Trace a finding's real path through the code
- After a finding: Hunt for variants of the same pattern elsewhere
- On unfamiliar code: Map architecture before launching any analysis
Modes
| Mode | Command flag | Purpose |
|---|---|---|
| Map | --map |
Build high-level context: entry points, trust model, data paths |
| Trace | --trace <entry> |
Follow one flow source → sink with full call chain |
| Hunt | --hunt <pattern> |
Find all variants of a pattern across the codebase |
| Teach | --teach |
Explain unfamiliar code, frameworks, or patterns in depth |
Modes can be combined. Map → Trace → Hunt is the natural attack progression.
[CONFIG] Configuration
output_dir: resolved by raptor-run-lifecycle start understand
confidence_levels:
high: "Direct code evidence — quote the line"
medium: "Inferred from context — state the assumption"
low: "Speculative — flag explicitly, verify before acting on"
flow_format: source → transform(s) → sink
[EXEC] Execution Rules
- Read actual code before making any claim. Do not rely on naming conventions or assumptions.
- Quote the exact line (file path + line number) as proof for every assertion.
- When tracing a flow, follow it until it terminates — don't stop at the first interesting function.
- When hunting variants, search the full codebase. Do not stop at the first match.
- When teaching, explain the mechanism, not just the name. Show the code that implements it.
- Produce structured output (context-map.json, flow-trace.json, variants.json) for integration with validation pipeline.
- libexec scripts: Run
libexec/scripts exactly as shown in the prompts — do not prependbash,exportcommands, absolute paths, or additional shell logic. The permission system auto-approveslibexec/raptor-*commands only when run in this exact form.
[GATES] MUST-GATEs
GATE-U1 [READ-FIRST]: Never describe how code works without reading it. If you haven't read a file, say so and read it before continuing.
GATE-U2 [ATTACKER-LENS]: When reading any code path, ask: where does trust transfer? Where are checks missing? Where does user input influence execution? These questions drive analysis, not just "does this code do what the comment says."
GATE-U3 [FULL-FLOW]: When tracing a data flow, follow every branch: happy path, error paths, middleware, async handlers. A missing check in an error path is still a missing check.
GATE-U4 [VARIANT-COMPLETE]: A variant hunt is not complete until the full codebase has been searched. If a pattern appears in one place, assume it appears in others until proven otherwise.
GATE-U5 [EVIDENCE-ONLY]: Confidence levels must match evidence. High confidence requires a quoted line. Medium requires a stated assumption. Low must be flagged and not acted on until verified.
[STYLE] Output Formatting
- File references:
path/to/file.py:42format throughout - Flow format:
source (file:line) → transform (file:line) → sink (file:line) - Confidence inline:
(confidence: high — file:line)or(confidence: medium — assumed from X) - No red/green status indicators (perspective-dependent)
- JSON outputs go to
$WORKDIR/for pipeline integration
Integration with Validation Pipeline
Shared inventory: MAP-0 runs build_checklist() to produce checklist.json with SHA-256 checksums per file. This is the same inventory used by /validate Stage 0. Coverage tracking (checked_by per function) is cumulative across both skills.
Checklist item schema (checklist.json → files[].items[]):
| Field | Type | Values / Notes |
|---|---|---|
name |
string | Function/global/macro/class name |
kind |
string | "function", "global", "macro", "class" |
line_start |
int | First line of the item |
line_end |
int|null | Last line (null if unknown) |
signature |
string | Full signature (functions only) |
checked_by |
list[str] | Run IDs that have reviewed this item |
metadata |
object | Language-specific: visibility, params, return_type, attributes |
The field is kind, not type. Source: core/inventory/extractors.CodeItem.
Output schemas are aligned with the validation pipeline's formats (attack-surface.json, attack-paths.json, findings.json).
Stages
| Stage | Mode | Gate(s) | Output |
|---|---|---|---|
| Map | --map |
U1, U2 | context-map.json |
| Trace | --trace |
U1, U2, U3, U5 | flow-trace-<id>.json |
| Hunt | --hunt |
U1, U4, U5 | variants.json |
| Teach | --teach |
U1, U5 | none --- inline output |
See stage-specific files for detailed instructions.
Optional: runtime probe (Map only)
If the target has a runnable binary, MAP-7 in map.md describes how
to corroborate the static map with a sandbox(observe=True) probe.
The runtime observation lands under a runtime_observation key in
context-map.json with correlations against entry points and sinks
— an entry point whose file the binary actually reads is
"runtime-confirmed" rather than only structurally identified.
Skip when the target is library/source-only or when the operator has no consent to execute the binary.
Notice
This analysis is performed for defensive purposes, security research, and authorized security testing only.
Source: gadievron/raptor → .claude/skills/code-understanding/SKILL.md