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.
npx skills add meltedinhex/analyst-ai-pack --skill dumping-and-rebuilding-a-pe-from-memorygit clone --depth 1 https://github.com/meltedinhex/analyst-ai-packWrote 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.
[](https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/dumping-and-rebuilding-a-pe-from-memory)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/dumping-and-rebuilding-a-pe-from-memory"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/dumping-and-rebuilding-a-pe-from-memory/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.
<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/dumping-and-rebuilding-a-pe-from-memory"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/dumping-and-rebuilding-a-pe-from-memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00073 | $0.00731 |
| Opus 5 | $0.00036 | $0.00365 |
| Sonnet 5 | $0.00015 | $0.00146 |
| Haiku 4.5 | $0.00007 | $0.00073 |
Grade A, and why
dumping-and-rebuilding-a-pe-from-memory 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dumping and Rebuilding a PE From Memory
When to Use
- You have a process/region dump of an unpacked or injected PE and need a file that loads in a disassembler.
- You need to convert virtual (loaded) layout back toward raw layout and fix the entry point.
Do not use this on a still-packed image — unpack to OEP first. This skill operates on an already-captured dump; it does not execute the sample.
Prerequisites
- A raw PE dump (e.g., from x64dbg Scylla, vaddump) and the OEP if known.
Safety & Handling
- The dump is live malicious code; store password-protected and never execute it.
Workflow
Step 1: Inspect the dumped headers
python scripts/analyst.py inspect dump.bin
Reports whether section RawAddress/RawSize match VirtualAddress/VirtualSize (memory-aligned dumps have raw==virtual) and the current AddressOfEntryPoint.
Step 2: Realign sections to raw layout
python scripts/analyst.py fix dump.bin --oep 0x1234 -o rebuilt.bin
Rewrites each section's PointerToRawData/SizeOfRawData to its virtual layout (the on-disk-from- memory convention) and sets the entry point to the supplied OEP.
Step 3: Reconstruct imports
The dumped image usually has a destroyed IAT; rebuild it with an import reconstructor (Scylla/ ImpRec) using the OEP, then re-inspect.
Step 4: Verify
Confirm the rebuilt file parses, has a valid entry point, and disassembles.
Validation
- Section table is internally consistent (no overlaps, within file size).
- AddressOfEntryPoint points inside an executable section.
- The rebuilt file is accepted by a PE parser/disassembler.
Pitfalls
- Forgetting that memory dumps use virtual alignment — raw offsets must be rewritten.
- Setting an OEP RVA that lies outside any section.
- Skipping IAT reconstruction, leaving call targets pointing at null/garbage.
References
- See
references/api-reference.mdfor the rebuilder. - PE format spec and ATT&CK T1620 (linked in frontmatter).
What ships with it
3 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.
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.
- 11d ago First seen · 94 lines · 73 tokens per session scan A 1964c9c754ff
dumping-and-rebuilding-a-pe-from-memory is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 73 tokens to every session and 731 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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