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 reverse-engineering-binaries-with-binary-ninjagit 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/reverse-engineering-binaries-with-binary-ninja)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/reverse-engineering-binaries-with-binary-ninja"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/reverse-engineering-binaries-with-binary-ninja.svg" alt="Measured on agentmods" 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 | $0.00072 | $0.00697 |
| Opus 5 | $0.00036 | $0.00349 |
| Sonnet 5 | $0.00014 | $0.00139 |
| Haiku 4.5 | $0.00007 | $0.00070 |
Grade A, and why
reverse-engineering-binaries-with-binary-ninja 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 4d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reverse Engineering Binaries With Binary Ninja
When to Use
- You want to reverse a binary with Binary Ninja and automate analysis via its Python API (function enumeration, IL traversal, annotation, extraction).
- You need to leverage MLIL/HLIL for cleaner analysis of obfuscated code.
Do not use the headless API to execute the sample — Binary Ninja performs static analysis. Run in an isolated environment and treat inputs as malicious.
Prerequisites
- Binary Ninja with the
binaryninjaPython API available (the script degrades gracefully and generates a script skeleton if the API is not importable).
Safety & Handling
- Static analysis does not execute the sample; keep inputs isolated.
Workflow
Step 1: Generate an analysis script skeleton
python scripts/analyst.py skeleton --emit functions,strings --out bn_extract.py
Emits a Binary Ninja Python script that opens a view, iterates functions, and exports
functions/strings to JSON using the real API (open_view, bv.functions, bv.get_strings).
Step 2: Choose the IL level
Use LLIL for close-to-assembly, MLIL for variable/SSA reasoning, and HLIL for readable pseudo-code; traverse instructions and operands programmatically.
Step 3: Automate annotation
Rename symbols (func.name), add comments (bv.set_comment_at), and create tags for findings.
Step 4: Run and aggregate
Execute the script (headless or in the UI console) and aggregate the JSON output.
Validation
- The skeleton uses real API calls (
binaryninja.open_view,bv.functions). - The chosen IL level matches the analysis goal.
- Exported JSON contains plausible functions/strings.
Pitfalls
- Headless licensing differences (Commercial vs Personal) affecting
open_viewavailability. - Confusing IL levels and operand structures across LLIL/MLIL/HLIL.
- Long analysis times on large binaries — scope function ranges.
References
- See
references/api-reference.mdfor the skeleton generator. - Binary Ninja API and IL docs (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.
- 4d ago First seen · 90 lines · 72 tokens per session scan A 4d8d30d0effd
reverse-engineering-binaries-with-binary-ninja is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 72 tokens to every session and 697 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 2026-09-03.
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