find-CNetworkMessages_dtor

find-CNetworkMessages_dtor is a skill for Claude Code from HLND2T/CS2_VibeSignatures. It costs 76 tokens per session (1,540 once invoked), scanned A, original, MIT.

A reverse-engineering procedure for locating the virtual destructor of CNetworkMessages in a Counter-Strike 2 binary. Reverse engineering examines compiled software to identify how it works.

In plain words
What is it for?
It is for inspecting the CNetworkMessages virtual-function table, checking its last entries, and decompiling candidate functions with IDA Pro.
Why use it?
It gives a repeatable way to narrow down destructor candidates instead of searching the binary without a defined method.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit It is for inspecting the CNetworkMessages virtual-function table, checking its last entries, and decompiling candidate functions with IDA Pro.

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Install with agentmods
npx agentmods add skills/hlnd2t/cs2_vibesignatures/find-cnetworkmessages_dtor
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add HLND2T/CS2_VibeSignatures --skill find-cnetworkmessages_dtor
Clone the repo
git clone --depth 1 https://github.com/HLND2T/CS2_VibeSignatures

Made for: Claude Code.

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 find-CNetworkMessages_dtor

README.md
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Your own site
<a href="https://agentmods.dev/skills/hlnd2t/cs2_vibesignatures/find-cnetworkmessages_dtor"><img src="https://agentmods.dev/badge/skills/hlnd2t/cs2_vibesignatures/find-cnetworkmessages_dtor/github.svg" alt="Measured on agentmods" height="20"></a>

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<a href="https://agentmods.dev/skills/hlnd2t/cs2_vibesignatures/find-cnetworkmessages_dtor"><img src="https://agentmods.dev/badge/skills/hlnd2t/cs2_vibesignatures/find-cnetworkmessages_dtor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 76 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,540 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00076 $0.01540
Opus 5.5 $0.00030 $0.00616
Sonnet 5.5 $0.00015 $0.00308
Haiku 4.5 $0.00008 $0.00154

Measured 2mo ago against content hash f8a6f081ec5d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

find-CNetworkMessages_dtor 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 2mo ago.

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.

.claude/skills/find-CNetworkMessages_dtor/SKILL.md · 157 lines

How it starts

The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Find CNetworkMessages_dtor

Locate CNetworkMessages_dtor vfunc in CS2 networksystem.dll or libnetworksystem.so using IDA Pro MCP tools.

Deterministic Preprocessor

Normal analyzer runs use ida_preprocessor_scripts/find-CNetworkMessages_dtor.py. It selects the ABI-defined destructor slot from CNetworkMessages_vtable.{platform}.yaml and regenerates func_sig with the shared deterministic signature generator. This Agent skill is only the fallback when that preprocessor fails; the trusted finalizer replaces any Agent-provided func_sig from func_va before accepting the output.

Method

1. Load CNetworkMessages VTable from YAML

ALWAYS Use SKILL /get-vtable-from-yaml with class_name=CNetworkMessages.

If the skill returns an error, STOP and report to user.

Otherwise, extract:

  • vtable_numvfunc
  • vtable_entries

2. Identify Destructor Candidates

The destructor is located in the last three vtable entries. Check the entries at indices:

  • vtable_numvfunc - 3
  • vtable_numvfunc - 2
  • vtable_numvfunc - 1

Read the function addresses from the vtable entries for these three slots.

3. Decompile and Identify the Destructor

Decompile all three candidate functions:

mcp__ida-pro-mcp__decompile addr="<candidate_1_addr>"
mcp__ida-pro-mcp__decompile addr="<candidate_2_addr>"
mcp__ida-pro-mcp__decompile addr="<candidate_3_addr>"
Windows (networksystem.dll)

The destructor has this characteristic two-argument pattern:

__int64 __fastcall CNetworkMessages_dtor(__int64 a1, char a2)
{
  CNetworkMessages_dtor2(a1);
  if ( (a2 & 1) != 0 )
    (*(void (__fastcall **)(_QWORD, __int64))(*g_pMemAlloc + 24LL))(g_pMemAlloc, a1);
  return a1;
}

Key identification rules for Windows:

  1. Takes two parameters: (__int64 a1, char a2) (this + flags)
  2. Calls another large destructor function (CNetworkMessages_dtor2) with just a1
  3. Conditionally frees memory via g_pMemAlloc if (a2 & 1) != 0
  4. Returns a1

Read the full file on GitHub · 157 lines

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. 2mo ago Changed · +7 lines f8a6f081ec5d
  2. 2mo ago First seen · 150 lines · 76 tokens per session scan A 9a0109da748e

Subscribe to this mod's changes

find-CNetworkMessages_dtor is a skill published in the GitHub repository HLND2T/CS2_VibeSignatures (67 stars, last pushed today), licensed MIT. It adds 76 tokens to every session and 1,540 once invoked, about $0.0003 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.

Related

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