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Find CNetworkMessages UnserializeMessageInternal

Organization
HLND2T
find-CNetworkMessages_UnserializeMessageInternal

Final-guarantee fallback for the find-CNetworkMessages_UnserializeMessageInternal preprocessor. Recovers CNetworkMessages::UnserializeMessageInternal (its func_va/func_rva/func_size/func_sig plus CNetworkMessages vtable slot) in CS2 networksystem.dll / libnetworksystem.so. Use when the deterministic preprocessor (ida_preprocessor_scripts/find-CNetworkMessages_UnserializeMessageInternal.py) could not locate the target because the stored func_sig no longer matches and its xref-string anchors ("size_exceeded_max", "netmessage") yield an empty candidate set. Trigger: CNetworkMessages_UnserializeMessageInternal

Overview

PublisherHLND2T
RepositoryCS2_VibeSignatures
Skill namefind-CNetworkMessages_UnserializeMessageInternal
Stars
67
Forks
11
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by HLND2T on GitHub. Read the source before you install it.

Installation

Install the Find CNetworkMessages UnserializeMessageInternal AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/HLND2T/CS2_VibeSignatures/tree/main/.claude/skills/find-CNetworkMessages_UnserializeMessageInternal
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/HLND2T/CS2_VibeSignatures.git /tmp/CS2_VibeSignatures
mkdir -p .claude/skills
cp -r /tmp/CS2_VibeSignatures/.claude/skills/find-CNetworkMessages_UnserializeMessageInternal .claude/skills/find-CNetworkMessages_UnserializeMessageInternal
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Find CNetworkMessages UnserializeMessageInternal in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Find CNetworkMessages UnserializeMessageInternal on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Find CNetworkMessages UnserializeMessageInternal is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Find CNetworkMessages_UnserializeMessageInternal (final-guarantee fallback)

Recover CNetworkMessages::UnserializeMessageInternal in CS2 networksystem.dll / libnetworksystem.so using IDA Pro MCP tools.

This is the Agent fallback for the find-CNetworkMessages_UnserializeMessageInternal skill: it runs only when the preprocessor returned failure. The preprocessor tries to reuse the previous build's func_sig and then falls back to two xref-string anchors; on a new build any of those can miss:

  • the stored func_sig breaks when the prologue is rewritten;
  • the xref-string fallback breaks when "size_exceeded_max" or "netmessage" lose their direct string xref — these are passed to __MakeGlobalSymbolCaseSensitive, a bare call whose string argument is frequently shared or folded so the XrefsTo lookup returns an empty set (this is exactly how it failed on 14189: empty candidate set for string xref: size_exceeded_max).

Your job is to locate the function by semantic anchors that survive those changes, then emit the YAML.

Realworld Function References

Read the platform-relevant real-world YAMLs before searching in IDA. CNetworkMessages::UnserializeMessageInternal has no dedicated reference YAML, so use the neighbouring CNetworkMessages finders and the ground-truth outputs for context and for the vtable cross-check. Treat addresses, offsets and sizes as reference-build values only; verify every result against the current binary.

  • bin_artifacts/14188b/networksystem/CNetworkMessages_UnserializeMessageInternal.windows.yaml
  • bin_artifacts/14188b/networksystem/CNetworkMessages_UnserializeMessageInternal.linux.yaml
  • bin_artifacts/14188b/networksystem/CNetworkMessages_vtable.windows.yaml
  • bin_artifacts/14188b/networksystem/CNetworkMessages_vtable.linux.yaml
  • bin_artifacts/14188b/networksystem/CNetworkMessages_SerializeInternal.windows.yaml
  • bin_artifacts/14188b/networksystem/CNetworkMessages_SerializeMessageInternal.windows.yaml
  • bin_artifacts/14188b/networksystem/CNetworkMessages_UnserializeFromStream.windows.yaml
  • bin_artifacts/14188b/networksystem/CNetworkMessages_FindOrCreateNetMessage.windows.yaml
  • bin_artifacts/14188b/networksystem/CNetworkMessages_RegisterNetworkCategory.windows.yaml

Background — what CNetworkMessages::UnserializeMessageInternal does

CNetworkMessages::UnserializeMessageInternal(this, msg, stream) is the CNetworkMessages virtual that reads one net message body from a stream:

  • it first obtains the message body size (sub_1801BF610 on Windows / sub_303E40 on Linux) and rejects a size that exceeds the remaining stream bit budget;
  • it asks the stream/context object (a3 vtable) for the associated message descriptor and the caller name/id;
  • when the body size exceeds the per-message cap (default 1500, or a value read from the message descriptor's keyvalues) and the -netmessage_size_exceeded_max command-line option is not set, it builds a small keyvalues block and logs a diagnostic — anchored by the four named keys "name", "id", "size", "max_size" and the two global symbol names "size_exceeded_max", "netmessage";
  • it then copies the body into the destination buffer (raw pointer or g_pMemAlloc-allocated scratch) and returns success/failure.

All accesses that matter for anchoring are immediates and immediate arguments, not this + offset — this is a plain function, so it is identified by its unique constants and its vtable position, not by a struct member.

Robustness principle — anchor on constants, not on string xrefs

Do not rely on the preprocessor's func_sig or on the "size_exceeded_max" / "netmessage" string xrefs — both are what failed. Instead anchor on the keyvalues key-hash immediates, which are compiled directly into the function and are globally unique to it (verified on 14188b, both platforms):

Key32-bit immediate (hex)
"id"0x18BE5E5F
"size"0x82E324C5
"max_size"0x9EFBD7ED

Each of these three values appears exactly once in the whole binary, and that occurrence is inside CNetworkMessages::UnserializeMessageInternal. ("name"'s immediate 0x70E8F456 is not unique — do not use it as a primary anchor.)

The vtable slot is then derived from the resolved address, never carried over from the previous build.

Output inventory

This is a real vtable vfunc with a body, so the YAML carries both func_* fields and the vtable slot fields. Offsets/indices/sizes are reference values from build 14188b — verify against the binary, do not assume.

#Output symbolKindWindowsLinuxWriter skill
1CNetworkMessages_UnserializeMessageInternalreal vtable vfuncfunc_va 0x1800e1f60, size 0x2f2, vtable CNetworkMessages slot 4 / 0x20func_va 0x2b1b60, size 0x2da, vtable CNetworkMessages slot 4 / 0x20/write-vfunc-as-yaml

Platform gating: the symbol is produced on both platforms. The vtable slot is 4 (0x20) on both — but still resolve it from the vtable rather than assuming, since the vtable can be reordered independently.

Step 0. Skip targets already produced

If CNetworkMessages_UnserializeMessageInternal.<platform>.yaml already exists in the analyzer-reported artifact module directory and parses to a non-empty mapping, skip it — the preprocessor or an earlier fallback wrote it. Never derive the artifact path from the binary directory; use the directory reported by the analyzer (also readable as CS2VIBE_ARTIFACT_DIR).

Step 1. Load the CNetworkMessages vtable

ALWAYS Use SKILL /get-vtable-from-yaml with class_name=CNetworkMessages to obtain the authoritative vtable_va, vtable_symbol and vtable_entries for the current build. You need this to assign the vtable fields in Step 3 and to cross-check the resolved address.

The expected_input for this skill is exactly this CNetworkMessages_vtable.{platform}.yaml, so it must already exist when the fallback runs. If /get-vtable-from-yaml errors, STOP and report to user.

Step 2. Locate the function by its unique key-hash immediates

Search the whole image for each 4-byte little-endian immediate. Any one of them is sufficient; require that at least two agree on a single function start.

mcp__ida-pro-mcp__py_eval code="""
import ida_bytes, ida_funcs, idc, idaapi
vals = {"id": 0x18BE5E5F, "size": 0x82E324C5, "max_size": 0x9EFBD7ED}
lo, hi = idaapi.inf_get_min_ea(), idaapi.inf_get_max_ea()
for name, v in vals.items():
    b = v.to_bytes(4, 'little')
    found = set(); s = lo; n = 0
    while n < 40:
        a = ida_bytes.find_bytes(b, s, hi)
        if a == idaapi.BADADDR:
            break
        f = ida_funcs.get_func(a)
        if f:
            found.add((hex(f.start_ea), idc.get_func_name(f.start_ea)))
        s = a + 1; n += 1
    print(name, hex(v), sorted(found))
"""

The function start returned for the three values is CNetworkMessages_UnserializeMessageInternal.

Positive confirmation (optional, use when the immediates are ambiguous): the target is the only function that calls __MakeGlobalSymbolCaseSensitive (Windows _MakeGlobalSymbolCaseSensitive) twice in a row with the arguments "size_exceeded_max" then "netmessage", immediately after building the "name"/"id"/"size"/ "max_size" keyvalues block. Confirm by scanning the candidate's own strings/calls:

mcp__ida-pro-mcp__py_eval code="""
import idautils, ida_funcs
f = ida_funcs.get_func(0x0)  # <-- candidate start
strings = idautils.Strings(default_setup=False)
sm = {s.ea: str(s) for s in strings}
hits = []
for ea, txt in sm.items():
    for x in idautils.XrefsTo(ea, 0):
        if f.start_ea <= x.frm < f.end_ea:
            hits.append(txt[:40]); break
print(sorted(set(hits)))
"""

A correct candidate's own strings include "max_size" and usually "size_exceeded_max" / "netmessage".

Note: "size_exceeded_max" / "netmessage" may legitimately have no XrefsTo at all in some builds (the preprocessor hit exactly this on 14189). Their absence is not evidence against a candidate — that is why the key-hash immediates above are the primary anchor and the strings are only a confirmation aid.

Step 3. Assign the vtable fields

Look the resolved function start up in the CNetworkMessages vtable entries from Step 1:

mcp__ida-pro-mcp__py_eval code="""
import yaml, os, idaapi
d = os.environ.get('CS2VIBE_ARTIFACT_DIR') or os.path.dirname(idaapi.get_input_file_path())
plat = 'windows' if idaapi.get_input_file_path().endswith('.dll') else 'linux'
v = yaml.safe_load(open(os.path.join(d, f'CNetworkMessages_vtable.{plat}.yaml'), encoding='utf-8'))
ents = {int(k): int(str(x), 16) for k, x in v['vtable_entries'].items()}
tgt = 0x0  # <-- resolved CNetworkMessages_UnserializeMessageInternal start
idx = [k for k, a in ents.items() if a == tgt]
print('vtable_class', v['vtable_class'])
print('match index', idx, 'offset', [hex(i * 8) for i in idx])
"""

Set:

  • vtable_name = CNetworkMessages
  • vfunc_index = <the matching entry index>
  • vfunc_offset = vfunc_index * 8

Verified neighbours you can sanity-check against (14189 Windows): slot 0 = CNetworkMessages_RegisterNetworkCategory, slot 2 = CNetworkMessages_FindOrCreateNetMessage, slot 5 = CNetworkMessages_SerializeMessageInternal, slot 6 = CNetworkMessages_UnserializeFromStream, slot 8 = CNetworkMessages_AllocateAndCopyConstructNetMessageAbstract, slot 11 = CNetworkMessages_RegisterNetworkArrayFieldSerializer, slot 24 = CNetworkMessages_RegisterNetworkFieldChangeCallbackInternal. If the resolved start matches no vtable entry, the function is not the vtable target — return to Step 2. Do not emit the previous build's slot.

Rename the function to CNetworkMessages_UnserializeMessageInternal if it is not already named that:

mcp__ida-pro-mcp__rename batch={"func":[{"addr":"<start>","name":"CNetworkMessages_UnserializeMessageInternal"}]}

Step 4. Generate the signature and write the YAML

  1. ALWAYS Use SKILL /generate-signature-for-function with addr=<resolved start> to obtain a fresh, validated func_sig. (This is a real function with a body — unlike an interface indirect vcall.)

  2. ALWAYS Use SKILL /write-vfunc-as-yaml with:

    • func_name: CNetworkMessages_UnserializeMessageInternal
    • func_addr: the resolved function start
    • func_sig: the signature from step 1
    • vtable_name: CNetworkMessages
    • vfunc_offset: vfunc_index * 8 (from Step 3)
    • vfunc_index: from Step 3

    The YAML must contain all eight fields (func_name, func_va, func_rva, func_size, func_sig, vtable_name, vfunc_offset, vfunc_index) for the platform being processed only. If /write-vfunc-as-yaml cannot take both a func_addr and vtable fields in one call, write the func_* fields with /write-func-as-yaml and then add the vtable fields.

Do not write a partial YAML, and do not carry a stale func_va/vfunc_index forward from a previous build.

Failure handling

  • CNetworkMessages_vtable.<platform>.yaml missing → STOP and report (the skill's expected_input is absent).
  • The key-hash immediates resolve to no function, or disagree on more than one function start → STOP and report which immediate failed, so the references can be extended. Do not guess an address.
  • Never emit the symbol on the wrong platform, and never reuse a previous build's func_va/vfunc_index.

Output YAML filenames

Written under the analyzer-reported artifact module directory, one file per platform:

  • Windows (networksystem.dll): CNetworkMessages_UnserializeMessageInternal.windows.yaml
  • Linux (libnetworksystem.so): CNetworkMessages_UnserializeMessageInternal.linux.yaml

Why this is robust

  • The function is located by immediate hash constants compiled into its body — they cannot be relocated away by string dedup or cross-function string sharing, which is precisely the failure mode that produced the preprocessor's empty candidate set for string xref: size_exceeded_max.
  • The vtable slot is derived from the resolved address, so a vtable reorder is absorbed instead of repeated.
  • A fresh func_sig is generated from the located function, so a rewritten prologue is absorbed too.

Frequently asked questions

What does the Find CNetworkMessages UnserializeMessageInternal AI skill do?

Final-guarantee fallback for the find-CNetworkMessages_UnserializeMessageInternal preprocessor. Recovers CNetworkMessages::UnserializeMessageInternal (its func_va/func_rva/func_size/func_sig plus CNetworkMessages vtable slot) in CS2 networksystem.dll / libnetworksystem.so. Use when the deterministic preprocessor (ida_preprocessor_scripts/find-CNetworkMessages_UnserializeMessageInternal.py) could not locate the target because the stored func_sig no longer matches and its xref-string anchors ("size_exceeded_max", "netmessage") yield an empty candidate set. Trigger: CNetworkMessages_Unserializ...

Why use Find CNetworkMessages UnserializeMessageInternal on TypingMind?

Because you install it once and use it with any model. Find CNetworkMessages UnserializeMessageInternal is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Find CNetworkMessages UnserializeMessageInternal in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HLND2T/CS2_VibeSignatures/tree/main/.claude/skills/find-CNetworkMessages_UnserializeMessageInternal. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Find CNetworkMessages UnserializeMessageInternal?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Find CNetworkMessages UnserializeMessageInternal?

As many as you like. As long as a model supports skills, you can use Find CNetworkMessages UnserializeMessageInternal with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Find CNetworkMessages UnserializeMessageInternal AI skill free?

Yes. It is published on GitHub by HLND2T under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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