auditing-jwt-verification-trust

auditing-jwt-verification-trust is a skill for Claude Code from UnboundCompute/security-agent-skills. It costs 218 tokens per session (2,256 once invoked), scanned A, original, MIT.

A security review of code that verifies JSON Web Tokens, signed data commonly used to identify users or services. It checks whether the server chooses the verification method and key instead of trusting values supplied inside the token.

In plain words
What is it for?
Reviewing token decode and verification code, algorithm settings, key lookups, and claims handling. Checking values such as algorithm, key identifier, and key-location fields.
Why use it?
If token-controlled settings select the algorithm or signing key, an attacker may create a token the server accepts. The review also checks the claims used to make identity decisions.

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 Reviewing token decode and verification code, algorithm settings, key lookups, and claims handling. Checking values such as algorithm, key identifier, and key-location fields.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/unboundcompute/security-agent-skills/auditing-jwt-verification-trust
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 auditing-jwt-verification-trust
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 auditing-jwt-verification-trust

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/unboundcompute/security-agent-skills/auditing-jwt-verification-trust"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/auditing-jwt-verification-trust.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 218 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,256 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 $0.00218 $0.02256
Opus 5 $0.00109 $0.01128
Sonnet 5 $0.00044 $0.00451
Haiku 4.5 $0.00022 $0.00226

Measured 12d ago against content hash 88e20dd1797f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

auditing-jwt-verification-trust 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/auditing-jwt-verification-trust/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Auditing JWT verification trust: when a signed token is verified on the token's own terms

A JSON Web Token is only as trustworthy as the verification code, and the bug is verification that trusts what the token itself supplies: the algorithm from the header, the key from a header-named location. If the server accepts the token's alg, an attacker switches a signature-verified token to an HMAC one signed with the public key, or to none; if it fetches the key from the token's kid, jku, or x5u, the attacker points it at a key they control. You audit it by resolving whether the algorithm is pinned server-side and where the verification key comes from, then checking the claims. This is a source-code audit: the whole value is deciding whether a reported token flaw is actually reachable in this codebase, so the false-positive killers carry the weight. Token-generation entropy belongs to the randomness skill; the OAuth grant dance belongs to the OIDC skill.

When to use

  • You are reviewing the code path that verifies a signed token and uses its claims for an identity decision.
  • You see a decode-or-verify call, an algorithms option, a key lookup by header parameter, or a claims read.
  • You want to know whether an attacker can forge a token this verification call accepts.

Scope check

Audit only systems you own or are authorized to assess, and present a crafted token only against an endpoint in scope, a forged token that verifies grants real access. Adjudicate on the verification call and its options. If you can't name the authorization, stop.

The loop

  1. Resolve the algorithm pinning and the key source first. Read the verification call and its options: is the accepted algorithm pinned to a fixed value server-side, or taken from the token header, and where does the verification key come from (a static preconfigured key or keyset, or a location named by the token's kid, jku, or x5u). These two facts decide whether the header-driven attacks have a sink, so settle them before flagging anything.

Read the full file on GitHub · 139 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 · 139 lines · 218 tokens per session scan A 88e20dd1797f

Subscribe to this mod's changes

auditing-jwt-verification-trust is a skill published in the GitHub repository UnboundCompute/security-agent-skills (5 stars, last pushed 3d ago), licensed MIT. It adds 218 tokens to every session and 2,256 once invoked, about $0.0011 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.

Related

Other skills, from other repositories

prodcheck-review

Review this codebase against the prodcheck pre-production checklists — security, performance, scale, integrations and post-launch readiness. Use when asked to check whether a project is ready to ship, to audit an area before launch, or to work through a specific checklist. Produces evidence with file:line citations…

FarzamHabibi/pre-production-checklist · 70 tokens

integrate-arcjet-guard-genkit

Integrate Arcjet security into a Genkit JS agent using @arcjet/guard — wrap ai.defineTool, put guardMiddleware on generate({ use }) for unwrapped / MCP / filesystem tools, and read a caller-owned id from generate({ context }). Use when asked to add Arcjet to genkit, rate limit its tools, screen inbound messages, or…

arcjet/arcjet-js · 89 tokens

integrate-arcjet-guard-langgraph

Integrate Arcjet security into a LangGraph Graph API agent using @arcjet/guard — wrap tool() / StructuredTool, wrap ToolNode for unwrapped MCP tools, and read threadid for correlation. Use when asked to add Arcjet to a LangGraph StateGraph / ToolNode agent, rate limit its tools, screen inbound messages, or block…

arcjet/arcjet-js · 87 tokens

integrate-arcjet-guard-tanstack-ai

Integrate Arcjet security into a TanStack AI chat() app using @arcjet/guard — put guardMiddleware first on chat({ middleware }) so onBeforeToolCall gates tools, and read a caller-owned id from chat({ context }). Use when asked to add Arcjet to TanStack AI, rate limit its tools, screen inbound messages, or block prompt…

arcjet/arcjet-js · 103 tokens

integrate-arcjet-guard-claude-managed-agents

Integrate Arcjet security into Claude Managed Agents (hosted REST+SSE, beta managed-agents-2026-04-01) using @arcjet/guard — screen user.message / initialevents before sessions.events.send, and gate custom tools on agent.customtooluse. Use when asked to add Arcjet to Claude Managed Agents, rate limit custom tools, or…

arcjet/arcjet-js · 102 tokens

linear-claude-skill

Manage Linear issues, projects, and teams.

Agent-Threat-Rule/agent-threat-rules · 15 tokens