adjudicating-taint-paths

adjudicating-taint-paths is a skill for Claude Code from UnboundCompute/security-agent-skills. It costs 128 tokens per session (1,383 once invoked), scanned A, original, MIT.

A method for checking whether untrusted input can travel through source code to a dangerous operation, such as running a command, opening a file, or executing a database query. A scanner result or suspected code path is treated as a lead until the live source confirms it.

In plain words
What is it for?
Use it to trace request data, headers, filenames, environment values, or deserialized fields into risky operations during an authorized security review.
Why use it?
It helps separate real, reachable security bugs from code that only looks dangerous. It records the evidence for accepting or rejecting each finding.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the security-agent-skills plugin — 194 skills shipped together

Good fit Use it to trace request data, headers, filenames, environment values, or deserialized fields into risky operations during an authorized security review.

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Install with agentmods
npx agentmods add skills/unboundcompute/security-agent-skills/adjudicating-taint-paths
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 UnboundCompute/security-agent-skills --skill adjudicating-taint-paths
Clone the repo
git clone --depth 1 https://github.com/UnboundCompute/security-agent-skills

Made for: Claude Code.

Or install security-agent-skills, the plugin that ships this one along with the rest of its 194 skills.

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 adjudicating-taint-paths

README.md
[![agentmods](https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/adjudicating-taint-paths/github.svg)](https://agentmods.dev/skills/unboundcompute/security-agent-skills/adjudicating-taint-paths)
Your own site
<a href="https://agentmods.dev/skills/unboundcompute/security-agent-skills/adjudicating-taint-paths"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/adjudicating-taint-paths/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.

agentmods 80×15 button for adjudicating-taint-paths

Your own site · 80×15
<a href="https://agentmods.dev/skills/unboundcompute/security-agent-skills/adjudicating-taint-paths"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/adjudicating-taint-paths.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 128 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,383 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.
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 $0.00128 $0.01383
Opus 5 $0.00064 $0.00691
Sonnet 5 $0.00026 $0.00277
Haiku 4.5 $0.00013 $0.00138

Measured 11d ago against content hash 8e6143228d3d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

adjudicating-taint-paths 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.

skills/adjudicating-taint-paths/SKILL.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Adjudicating taint paths: lead → decided finding

A lead is a fact about structure - "an input-shaped value can reach a dangerous sink." It is never a verdict. Adjudication is the disciplined work of deciding whether that structural possibility is a real, reachable bug on the current source, and recording the decision so it isn't re-litigated next pass.

When to use

  • A scanner or candidate list flagged a sink and you must confirm or kill it.
  • You spotted a sink by hand and want to know if attacker input reaches it.
  • You need to kill a plausible-looking lead with evidence, not vibes.

Scope check

Authorized source only (your own, OSS, CTF, in-scope engagement). If you can't name the authorization, stop.

The loop

  1. Name source and sink precisely. Which exact argument of which sink is dangerous, and what is the actual untrusted entry - a request param, header, filename, env var, deserialized field? Vague framing ("user input reaches it somewhere") is how false positives survive.

  2. Trace the reverse cone into the sink. What values can flow into this sink argument? This enumerates every origin. If none trace back to an untrusted source, the lead is dead - kill it, record why.

  3. Trace the forward cone from the source. Where does the untrusted value go? If it never touches the sink, the lead is dead. Forward and reverse must agree; if they don't, you mis-specified an endpoint - fix it and redo.

  4. Get a witness path. The strongest evidence is a concrete source → … → sink path. Good tooling returns either a witness or an honest negative ("no path"). A witness is a hypothesis to verify, not a proof.

  5. Confirm every hop against live source. Read the actual body of each function on the path at the commit you're adjudicating. Verify the value is genuinely carried hop-to-hop and is not: reassigned to a constant/trusted value; validated, sanitized, or encoded by a guard on the path; narrowed to a safe type or bounded before the sink; or never actually passed by any caller.

Read the full file on GitHub · 113 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. 11d ago First seen · 113 lines · 128 tokens per session scan A 8e6143228d3d

Subscribe to this mod's changes

adjudicating-taint-paths is a skill published in the GitHub repository UnboundCompute/security-agent-skills (5 stars, last pushed 2d ago), licensed MIT. It adds 128 tokens to every session and 1,383 once invoked, about $0.0006 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 2026-08-31.

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