ai-logic-scanner

ai-logic-scanner is a skill for Claude Code, Codex from marcosd4h/DeepExtractRuntime. It costs 81 tokens per session (2,789 once invoked), scanned A, original, MIT.

An AI-based scanner for finding logic flaws in Windows program files, such as authentication bypasses, authorization mistakes, confused-deputy issues, privilege escalation, and state-machine errors. It follows call chains across DLLs and has a separate agent check its findings.

In plain words
What is it for?
Use it to scan a module, inspect an RPC handler or COM method, or investigate a call chain leading from an entry point to a privileged operation.
Why use it?
It helps identify security bugs caused by incorrect decisions or trust assumptions rather than simple code patterns. This is useful when a flaw depends on how several functions work together.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads .claude/ paths; mentions subagents.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python .claude/skills/decompiled-code-extractor/scripts/find_module_db.py --list.

Good fit Use it to scan a module, inspect an RPC handler or COM method, or investigate a call chain leading from an entry point to a privileged operation.

Compare 6 skills from other repositories ↓
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/ai-logic-scanner

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.

agentmods badge for ai-logic-scanner

README.md
[![agentmods](https://agentmods.dev/badge/skills/marcosd4h/deepextractruntime/ai-logic-scanner.svg)](https://agentmods.dev/skills/marcosd4h/deepextractruntime/ai-logic-scanner)
Your own site
<a href="https://agentmods.dev/skills/marcosd4h/deepextractruntime/ai-logic-scanner"><img src="https://agentmods.dev/badge/skills/marcosd4h/deepextractruntime/ai-logic-scanner.svg" alt="Measured on agentmods" height="20"></a>
Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,789 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00081 $0.02789
Opus 5 $0.00041 $0.01394
Sonnet 5 $0.00016 $0.00558
Haiku 4.5 $0.00008 $0.00279

Measured 8d ago against content hash 0e0732146560, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

ai-logic-scanner 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 8d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/_common.py, scripts/build_threat_model.py, scripts/prepare_context.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/ai-logic-scanner/SKILL.md · 273 lines

How it starts

The opening of the file, as written. The whole thing — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Logic Scanner

Purpose

Find exploitable logic vulnerabilities in Windows PE binaries using LLM-driven code analysis instead of regex pattern matching. The scanner builds a cross-module callgraph from attacker-reachable entry points, classifies every node (MUST_READ / KNOWN_API / TELEMETRY / LIBRARY), and delivers code to the AI agent in depth-level batches. The agent analyzes each batch for authentication, authorization, state management, and trust boundary flaws, returns taint-guided requests for deeper functions, and reads deeper code itself via Shell -- iterating until max depth or taint termination.

This is NOT a pattern scanner. All vulnerability detection decisions are made by the LLM agent using adversarial prompting, invariant decomposition, and type-specific specialist knowledge. A separate skeptic agent independently verifies each finding.

When to Use

  • Scan a module for logic vulnerabilities (auth bypass, state machine errors, confused deputy, privilege escalation)
  • Analyze a specific RPC handler or COM method for authorization gaps
  • Deep analysis of a call chain from an entry point to privileged operations
  • AI-driven vulnerability research on decompiled Windows service binaries
  • When static analysis produces too many false positives or misses subtle logic bugs that require understanding control flow and state

When NOT to Use

  • Memory corruption (buffer overflows, integer overflows, UAF) -- use ai-memory-corruption-scanner or /memory-scan
  • Code lifting or rewriting -- use code-lifter
  • General function explanation -- use re-analyst or /explain

Data Sources

SQLite Databases (primary)

Individual analysis DBs in extracted_dbs/ provide the raw data:

  • functions.decompiled_code -- Hex-Rays decompiled C (read on demand)
  • functions.assembly_code -- x64 assembly ground truth (read on demand)
  • functions.simple_outbound_xrefs -- Callgraph edges
  • functions.function_signature -- Parameter types and names
  • file_info.exports -- Exported functions
  • file_info.entry_point -- PE entry points

Read the full file on GitHub · 273 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.

  1. 8d ago First seen · 273 lines · 81 tokens per session scan A 0e0732146560

Subscribe to this mod's changes

ai-logic-scanner is a skill published in the GitHub repository marcosd4h/DeepExtractRuntime (19 stars, last pushed 4mo ago), licensed MIT. It adds 81 tokens to every session and 2,789 once invoked, about $0.0004 per session on Opus 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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