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 UnboundCompute/security-agent-skills --skill hunting-formula-injection-in-exportsgit clone --depth 1 https://github.com/UnboundCompute/security-agent-skillsWrote 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/unboundcompute/security-agent-skills/hunting-formula-injection-in-exports)<a href="https://agentmods.dev/skills/unboundcompute/security-agent-skills/hunting-formula-injection-in-exports"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/hunting-formula-injection-in-exports/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/unboundcompute/security-agent-skills/hunting-formula-injection-in-exports"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/hunting-formula-injection-in-exports.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 | $0.00192 | $0.02128 |
| Opus 5.5 | $0.00077 | $0.00851 |
| Sonnet 5.5 | $0.00038 | $0.00426 |
| Haiku 4.5 | $0.00019 | $0.00213 |
Grade A, and why
hunting-formula-injection-in-exports 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.
How it starts
The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hunting formula injection in exports: when a cell runs code on open
An application that lets users store text and later offers an export to a spreadsheet format has quietly built a delivery channel. Spreadsheet programs decide whether a cell is data or a formula by its first character: a leading equals, plus, minus, or at sign marks a formula, and so does a leading tab or carriage return that the program strips before parsing. So a value a user typed into a profile field, a comment, or a device name, stored verbatim and written into a downloaded report, becomes live code when an administrator opens that report. The formula can pull other cells out to an attacker URL through a web or hyperlink function, invoke a legacy dynamic-data exchange command that launches a program, or display misleading content the recipient trusts. The bug lives in the export writer, not the input page, and the victim is the person who opens the file. You find it by tracing stored untrusted fields into every export and checking whether dangerous leading characters are neutralized.
When to use
- The application exports user-controlled data to CSV, TSV, or a spreadsheet workbook format.
- A stored field (name, comment, description, tag) is written into a downloaded report opened by staff.
- An admin, finance, or analytics workflow opens exports of user-submitted content in a spreadsheet.
Scope check
Test formula injection only against applications you own or are authorized to assess, and open confirming exports only in an isolated spreadsheet environment with no network egress and no sensitive cells, because a live formula can call out or launch a program on the machine that opens it. Never plant a payload where a real recipient would open it. If you can't name the authorization, stop.
The loop
- Establish that the export writes cells without neutralization first. Locate every code path that produces a CSV, TSV, or workbook export and read how it writes each cell. This is the false-positive killer: if the writer prefixes at-risk cells with a safe character, wraps values so the leading token is inert, forces the cell type to text, or strips leading formula characters, a stored value cannot become a formula and there is no bug. Name the exports that write stored values verbatim.
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.
- 2mo ago First seen · 140 lines · 192 tokens per session scan A fe1ac0bdcacf
hunting-formula-injection-in-exports is a skill published in the GitHub repository UnboundCompute/security-agent-skills (24 stars, last pushed 1mo ago), licensed MIT. It adds 192 tokens to every session and 2,128 once invoked, about $0.0008 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 2026-09-05.
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