orca-supply-chain-exposure

orca-supply-chain-exposure is a skill for Claude Code from orcasecurity/orca-skills. It costs 115 tokens per session (2,699 once invoked), scanned A, original, MIT.

A cloud supply-chain exposure checker for suspect software packages and versions. A software supply chain is the collection of external packages and tools an application depends on; the checker finds matching packages in the environment and identifies affected assets.

In plain words
What is it for?
Use it after a security advisory to check package names and versions, locate deployed copies, and identify which systems may be exposed.
Why use it?
It removes the manual work of comparing an advisory or indicator list with package inventories and software bills of materials. This helps determine whether a reported package campaign or vulnerability is actually present.

Skill for Claude Code

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

Part of the orca-skills plugin — 19 skills shipped together

Good fit Use it after a security advisory to check package names and versions, locate deployed copies, and identify which systems may be exposed.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/orcasecurity/orca-skills/orca-supply-chain-exposure
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 orcasecurity/orca-skills --skill orca-supply-chain-exposure
Clone the repo
git clone --depth 1 https://github.com/orcasecurity/orca-skills

Made for: Claude Code.

Or install orca-skills, the plugin that ships this one along with the rest of its 19 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 orca-supply-chain-exposure

README.md
[![agentmods](https://agentmods.dev/badge/skills/orcasecurity/orca-skills/orca-supply-chain-exposure/github.svg)](https://agentmods.dev/skills/orcasecurity/orca-skills/orca-supply-chain-exposure)
Your own site
<a href="https://agentmods.dev/skills/orcasecurity/orca-skills/orca-supply-chain-exposure"><img src="https://agentmods.dev/badge/skills/orcasecurity/orca-skills/orca-supply-chain-exposure/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 orca-supply-chain-exposure

Your own site · 80×15
<a href="https://agentmods.dev/skills/orcasecurity/orca-skills/orca-supply-chain-exposure"><img src="https://agentmods.dev/badge/skills/orcasecurity/orca-skills/orca-supply-chain-exposure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 115 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,699 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00115 $0.02699
Opus 5 $0.00057 $0.01350
Sonnet 5 $0.00023 $0.00540
Haiku 4.5 $0.00012 $0.00270

Measured 12d ago against content hash 61d16509732f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

orca-supply-chain-exposure 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 12d 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/orca-supply-chain-exposure/SKILL.md · 294 lines

How it starts

The opening of the file, as written. The whole thing — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Orca Supply Chain Exposure Skill

Answers the question: "From this list of suspect packages, which are we actually running, where, and at what version?"

Replaces a manual sweep of inventory + SBOM queries with a single parallel check. Optimized for the moment after an MDR / vendor / news advisory lands and the team needs an exposure answer in minutes.

Usage

/orca-supply-chain-exposure @antv/util @antv/g2 @antv/g6
/orca-supply-chain-exposure log4j-core 2.14.1
/orca-supply-chain-exposure xz-utils 5.6.0,5.6.1

Or natural language:

  • "are we exposed to the @antv npm attack?"
  • "check these packages: react-devtools 4.28.0, axios 0.21.0"
  • "any assets with xz-utils 5.6.x?"
  • "supply chain check on this IOC list"

The user may paste a bullet list, a comma-separated list, or a table. Parse it.

Processing Logic

Step 1: Parse the package list

Build a normalized list of (package_name, suspected_versions[]). If the user only gave package names with no versions, treat any version found in the environment as a positive hit and rely on Orca's CVE data to confirm vulnerability.

Step 2: Run parallel exposure queries

For each package, run two queries in parallel:

Query A: Direct inventory lookup

discovery_search:
  search_phrase: "assets with package <name>"
  limit: 50

Query B: CVE-driven lookup (catches assets where Orca already flags the package as vulnerable)

discovery_search:
  search_phrase: "assets with vulnerable <name> package"
  limit: 50

Batching rule: Run all packages' Query A and Query B in parallel — one tool-call batch per package isn't enough, batch across packages. For 20 packages, that's 40 parallel discovery_search calls in one message.

Step 3: Match version ranges

For each asset returned, extract the installed version from the discovery_search response and compare against the user's suspected version list:

  • Vulnerable Match: installed version is in the suspected range.
  • Below Range: installed version is older than the vulnerable range (not affected).
  • Above Range: installed version is newer (patched or unrelated).
  • Unknown Version: discovery_search didn't return a version — flag and recommend a manual SBOM check in Orca UI.

Read the full file on GitHub · 294 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. 12d ago First seen · 294 lines · 115 tokens per session scan A 61d16509732f

Subscribe to this mod's changes

orca-supply-chain-exposure is a skill published in the GitHub repository orcasecurity/orca-skills (50 stars, last pushed 5d ago), licensed MIT. It adds 115 tokens to every session and 2,699 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 2026-08-30.

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