SAST Skills is a collection of agent workflows that inspect web and mobile application code for security vulnerabilities, where SAST means static application security testing. Developers and security reviewers use it to map a codebase, verify possible flaws, and produce a severity-ranked remediation report. The catalogue entries are the project's vulnerability-detection and reporting skills.
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.
npx skills add utkusen/sast-skills --skill sast-jwtgit clone --depth 1 https://github.com/utkusen/sast-skillsWrote 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/utkusen/sast-skills/sast-jwt)<a href="https://agentmods.dev/skills/utkusen/sast-skills/sast-jwt"><img src="https://agentmods.dev/badge/skills/utkusen/sast-skills/sast-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.
<a href="https://agentmods.dev/skills/utkusen/sast-skills/sast-jwt"><img src="https://agentmods.dev/badge/skills/utkusen/sast-skills/sast-jwt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, 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 445 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.
- medium Excessive Agency · line 282 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- low Privilege Escalation · line 436 Skill requests more permissions than appear necessary for its stated functionality. Review if elevated access is justified.Fix: Request only the minimum permissions required. Document why each permission is needed. Remove broad permissions like '*' or 'all'.
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 | $0.00123 | $0.05862 |
| Opus 5 | $0.00062 | $0.02931 |
| Sonnet 5 | $0.00025 | $0.01172 |
| Haiku 4.5 | $0.00012 | $0.00586 |
Grade A, and why
sast-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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
> [Proof-of-concept using jwt_tool, hashcat, or curl. Copies of this mod
1 near-identical copy found in the catalogue:
- sast-jwt — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 488 lines — stays where its author put it; the contents beside it link to each section on GitHub.
JWT Vulnerability Detection
You are performing a focused security assessment to find insecure JSON Web Token (JWT) implementations. This skill uses a two-phase approach with subagents: recon (map the full JWT lifecycle — issuance, verification, and configuration) then analysis (identify every exploitable weakness in those verification sites).
Prerequisites: sast/architecture.md must exist. Run the analysis skill first if it doesn't.
What is an Insecure JWT Implementation
JWTs consist of three Base64URL-encoded parts: header.payload.signature. The header declares the signing algorithm (alg), the payload carries claims (e.g., sub, role, exp), and the signature is a cryptographic proof of integrity. Vulnerabilities arise when the server trusts the token's own claims about how it was signed, fails to verify the signature at all, uses a guessable secret, or trusts attacker-controlled key material embedded in the token itself.
The core pattern: the server does not fully verify the JWT's authenticity and integrity before trusting its claims.
What JWT Vulnerabilities ARE
1. Algorithm confusion — alg: none
The server accepts a JWT whose header declares "alg": "none", bypassing signature verification entirely. An attacker crafts an arbitrary payload, sets alg to none, and omits the signature. If the library processes it, the forged token is accepted.
2. Algorithm confusion — RS256 → HS256 A server configured for RS256 (asymmetric: sign with private key, verify with public key) can be tricked into HS256 mode if the library allows the algorithm to be specified by the token. Since the public key is often retrievable, the attacker signs a forged token with HS256 using the server's public key as the HMAC secret. The server verifies the HMAC using the same public key and accepts the token.
3. Missing or disabled signature verification The server decodes the JWT payload without actually verifying the signature. Common patterns:
- Python (PyJWT):
jwt.decode(token, options={"verify_signature": False}) - Node.js (jsonwebtoken):
jwt.decode(token)instead ofjwt.verify(token, secret) - Manual base64 decode of the payload with no signature check
algorithms=["none"]accepted in the decode call
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.
- 11d ago First seen · 488 lines · 123 tokens per session scan A be3c5b270331
sast-jwt is a skill published in the GitHub repository utkusen/sast-skills (1,307 stars, last pushed 5mo ago), licensed MIT. It adds 123 tokens to every session and 5,862 once invoked, about $0.0006 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 2026-08-30.
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