What is map-attack-surface?

A reverse-engineering workflow that finds and ranks every likely way an attacker can enter a Windows program file, including exports, callbacks, COM methods, RPC handlers, and network handlers.

Use it to inventory entry points in an analyzed Windows binary and prioritize them based on reachable security-sensitive operations.

Important entry points may be hidden behind callbacks, object interfaces, or dispatch code rather than appearing as simple exported functions.

map-attack-surface — Skill for Claude Code and Codex by marcosd4h

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

git clone --depth 1 https://github.com/marcosd4h/DeepExtractRuntime

agentmods

npx agentmods add skills/marcosd4h/deepextractruntime/map-attack-surface

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/marcosd4h/deepextractruntime/map-attack-surface/github.svg)](https://agentmods.dev/skills/marcosd4h/deepextractruntime/map-attack-surface)

Your own site

<a href="https://agentmods.dev/skills/marcosd4h/deepextractruntime/map-attack-surface"><img src="https://agentmods.dev/badge/skills/marcosd4h/deepextractruntime/map-attack-surface/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/marcosd4h/deepextractruntime/map-attack-surface"><img src="https://agentmods.dev/badge/skills/marcosd4h/deepextractruntime/map-attack-surface.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 131 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,956 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00131	$0.02956
Opus 5.5	$0.00052	$0.01182
Sonnet 5.5	$0.00026	$0.00591
Haiku 4.5	$0.00013	$0.00296

Measured 1mo ago against content hash c0dbaa91a38e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

map-attack-surface scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/_common.py, scripts/discover_entrypoints.py, scripts/generate_entrypoints_json.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/map-attack-surface/SKILL.md · 291 lines

How it starts

The opening of the file, as written. The whole thing — 291 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Attack Surface Mapper

Purpose

Answer: "Where can an attacker enter this binary?"

Automatically discover, classify, and rank every possible entry point in an analyzed Windows PE binary, from obvious DLL exports to hidden COM vtable methods, RPC stubs, callback registrations, and socket dispatchers. Each entry point is ranked by attack value using callgraph reachability to dangerous operations.

When NOT to Use

General module-level triage or function classification -- use classify-functions or generate-re-report
Tracing attacker-controlled input to specific sinks -- use taint-analysis
Understanding what a specific function does -- use re-analyst or /explain
PE-level import/export dependency mapping -- use import-export-resolver

Data Sources

SQLite Databases (primary)

Individual analysis DBs in extracted_dbs/ provide:

file_info.entry_point -- PE-detected entry points
file_info.exports -- All exported functions with signatures
file_info.tls_callbacks -- TLS callback metadata with threat scoring
db.get_imports() / file_info.imports -- Imported APIs (flat rows from the v3 table or nested JSON complement)
functions.simple_outbound_xrefs -- Callgraph edges for reachability analysis
functions.vtable_contexts -- COM/WRL vtable reconstructions
functions.dangerous_api_calls -- Dangerous API sinks per function
functions.string_literals -- String patterns (pipe names, RPC protocols)

Finding a Module DB

Reuse the decompiled-code-extractor skill's find_module_db.py:

python .claude/skills/decompiled-code-extractor/scripts/find_module_db.py --list
python .claude/skills/decompiled-code-extractor/scripts/find_module_db.py appinfo.dll

Quick Cross-Dimensional Search

To search across function names, strings, APIs, classes, and exports in one call:

python .claude/helpers/unified_search.py <db_path> --query "SearchTerm"
python .claude/helpers/unified_search.py <db_path> --query "SearchTerm" --json

Read the full file on GitHub · 291 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago Changed c0dbaa91a38e
1mo ago First seen · 291 lines · 131 tokens per session scan A e527dd56c49d

Subscribe to this mod's changes

map-attack-surface is a skill published in the GitHub repository marcosd4h/DeepExtractRuntime (21 stars, last pushed 1mo ago), licensed MIT. It adds 131 tokens to every session and 2,956 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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