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.
git clone --depth 1 https://github.com/ShulkwiSEC/bb-hugenpx agentmods add skills/shulkwisec/bb-huge/jwt-algorithm-confusionWrote 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/shulkwisec/bb-huge/jwt-algorithm-confusion)<a href="https://agentmods.dev/skills/shulkwisec/bb-huge/jwt-algorithm-confusion"><img src="https://agentmods.dev/badge/skills/shulkwisec/bb-huge/jwt-algorithm-confusion/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/shulkwisec/bb-huge/jwt-algorithm-confusion"><img src="https://agentmods.dev/badge/skills/shulkwisec/bb-huge/jwt-algorithm-confusion.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 | $0.00058 | $0.00970 |
| Opus 5 | $0.00029 | $0.00485 |
| Sonnet 5 | $0.00012 | $0.00194 |
| Haiku 4.5 | $0.00006 | $0.00097 |
Grade A, and why
jwt-algorithm-confusion 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 7d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- jwt-algorithm-confusion — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
JWT Algorithm Confusion
When to Use
- When testing APIs or web applications that use JWTs for session management or authentication.
- To attempt to forge arbitrary JWTs (e.g., escalating to 'admin') when the application utilizes an asymmetric signature algorithm (like RS256) and the application's public key can be obtained.
Prerequisites
- Authorized scope and target URLs from bug bounty program
- Burp Suite Professional (or Community) configured with browser proxy
- Familiarity with OWASP Top 10 and common web vulnerability classes
- SecLists wordlists for fuzzing and enumeration
Workflow
Phase 1: Reconnaissance (Finding the Public Key)
# Concept: JWT Algorithm Confusion ```
### Phase 2: Intercepting and Modifying the JWT Header
```json
// {
"alg": "HS256",
"typ": "JWT"
}
Phase 3: Modifying the Payload (Privilege Escalation)
// {
"user": "attacker",
"role": "admin",
"iat": 1716260400
}
Phase 4: Signing the Forged JWT
# jwt_tool.py [ENCODED_HEADER].[ENCODED_PAYLOAD] -S hs256 -k public_key.pem
Decision Point 🔀
flowchart TD
A[Forge JWT ] --> B{Server Accepts? ]}
B -->|Yes| C[Exploit API ]
B -->|No| D[Check None Alg ]
C --> E[Document Flaw ]
🔵 Blue Team Detection & Defense
- Enforce Algorithm Verification: Library Updates: Public Key Secrecy (Symmetric fallback): Key Concepts | Concept | Description | |---------|-------------|
Output Format
Jwt Algorithm Confusion — Assessment Report
============================================================
Target: [Target identifier]
Assessor: [Operator name]
Date: [Assessment date]
Scope: [Authorized scope]
MITRE ATT&CK: [Relevant technique IDs]
Findings Summary:
[Finding 1]: [Severity] — [Brief description]
[Finding 2]: [Severity] — [Brief description]
Detailed Results:
Phase 1: [Phase name]
- Result: [Outcome]
- Evidence: [Screenshot/log reference]
- Impact: [Business impact assessment]
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 124 lines · 58 tokens per session scan A e4fcc16329b0
jwt-algorithm-confusion is a skill published in the GitHub repository ShulkwiSEC/bb-huge (22 stars, last pushed 2mo ago), licensed MIT. It adds 58 tokens to every session and 970 once invoked, about $0.0003 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 2026-09-03.
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