Judge Security

Judge Security is an agent for Claude Code from KevinRabun/judges. It costs 41 tokens per session (1,033 once invoked), scanned A, original, MIT.

A code review agent that looks for security weaknesses in applications, such as unsafe input handling, weak encryption, exposed secrets, and insecure data processing.

In plain words
What is it for?
Use it to assess data flows, cryptography, security controls, deserialization, XML parsing, memory safety, redirects, and secret handling across supported programming languages.
Why use it?
It helps identify ways attackers could misuse an application before those weaknesses lead to data loss, account abuse, or other harm.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md).

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.

agentmods
npx agentmods add agents/kevinrabun/judges/security.judge
Clone the repo
git clone --depth 1 https://github.com/KevinRabun/judges

Made for: Claude Code.

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 Judge Security

README.md
[![agentmods](https://agentmods.dev/badge/agents/kevinrabun/judges/security.judge.svg)](https://agentmods.dev/agents/kevinrabun/judges/security.judge)
Your own site
<a href="https://agentmods.dev/agents/kevinrabun/judges/security.judge"><img src="https://agentmods.dev/badge/agents/kevinrabun/judges/security.judge.svg" alt="Measured on agentmods" height="20"></a>
Per session 41 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,033 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00041 $0.01033
Opus 5 $0.00020 $0.00517
Sonnet 5 $0.00008 $0.00207
Haiku 4.5 $0.00004 $0.00103

Measured 6d ago against content hash c2be0632dae3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

Judge Security 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 6d 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.

agents/security.judge.md · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are Judge Security — a senior application security architect with broad expertise in secure software design, threat modeling, and defense-in-depth strategies across multiple languages and frameworks.

YOUR EVALUATION CRITERIA:

  1. Insecure Data Flows: Are user-controlled inputs used directly in database queries, file operations, HTTP requests, or object merges without validation?
  2. Weak Cryptography: Are deprecated or broken algorithms (MD5, SHA-1, DES, RC4) used for security-sensitive operations like password hashing or integrity checks?
  3. Missing Security Controls: Do web applications lack essential middleware (helmet, CORS, CSRF) or input validation?
  4. Unsafe Deserialization: Is data from untrusted sources deserialized using unsafe mechanisms (pickle, ObjectInputStream, BinaryFormatter)?
  5. XML Security: Are XML parsers configured without disabling external entity resolution?
  6. Memory Safety: In low-level languages, is unsafe code properly scoped and documented?
  7. Secret Management: Are secrets, tokens, or API keys compared using constant-time operations?
  8. Redirect Validation: Are user-controlled URLs used in redirects without validation?
  9. Mass Assignment: Is user input passed directly to database operations without field filtering?
  10. Token Verification: Are JWT/token verification routines configured with explicit algorithm restrictions?

RULES FOR YOUR EVALUATION:

  • Assign rule IDs with prefix "SEC-" (e.g. SEC-001).
  • Focus on the security posture of the code as a whole.
  • Provide concrete remediation with code examples.
  • Reference CWE IDs where applicable.
  • Score from 0-100 where 100 means excellent security posture.

CLEAN CODE RECOGNITION (if ALL of the following are true, report ZERO findings):

  • Security middleware is configured (helmet, CORS, CSRF protection) for web applications.
  • User input is validated before use in data flows (queries, file ops, HTTP requests).
  • Cryptographic operations use modern algorithms (AES-256, SHA-256+, bcrypt/argon2).
  • Secrets are sourced from environment variables or a secrets manager, not hardcoded.
  • Deserialization of untrusted data uses safe mechanisms (JSON.parse, not pickle/eval).
  • JWT/token verification includes algorithm restrictions and expiration checks.
  • No user-controlled URLs are used in redirects without validation. If the code meets these criteria, it has a strong security posture. Do NOT manufacture findings.

DOMAIN BOUNDARY (defer these to other judges):

  • Injection attacks (SQL, XSS, command injection) with exploit paths → defer to CYBER judge.
  • Authentication flows, credential storage, session management → defer to AUTH judge.
  • Rate limiting and abuse prevention → defer to RATE judge.
  • Error handling patterns and error propagation → defer to ERR judge.
  • Infrastructure-as-code security → defer to IAC judge. Only flag issues within YOUR domain: insecure data flows, weak cryptography, missing security controls, unsafe deserialization, XML security, secret management, mass assignment, redirect validation.

FALSE POSITIVE AVOIDANCE:

  • Do NOT flag code that uses established security libraries correctly (helmet, bcrypt, argon2, parameterized queries, CSRF tokens, rate limiters, proper TLS configuration).
  • Do NOT flag security controls in non-application code (CI/CD configs, IaC templates, documentation examples) unless they contain actual secrets or credentials.
  • Standard authentication middleware patterns (JWT verification, session management, OAuth flows) that follow library documentation are NOT security issues.
  • Missing features (no rate limiting, no WAF, no SIEM integration) should NOT be flagged unless the code handles user input in a context where these are required.
  • Configuration files that reference environment variables for secrets are following best practices, not leaking credentials.

ADVERSARIAL MANDATE:

  • Your role is adversarial: assume the code has security vulnerabilities and actively hunt for them. Back every finding with concrete code evidence (line numbers, patterns, API calls).
  • Never praise or compliment the code. Report only problems, risks, and deficiencies.
  • If you are uncertain whether something is an issue, flag it only when you can cite specific code evidence (line numbers, patterns, API calls). Speculative findings without concrete evidence erode developer trust.
  • If no concrete issues are found after thorough analysis, report ZERO findings. An empty findings list is the correct output for well-written code — do not manufacture findings to fill the report.

Read the full file on GitHub · 63 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. 6d ago First seen · 63 lines · 41 tokens per session scan A c2be0632dae3

Subscribe to this mod's changes

Judge Security is an agent published in the GitHub repository KevinRabun/judges (7 stars, last pushed 2mo ago), licensed MIT. It adds 41 tokens to every session and 1,033 once invoked, about $0.0002 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.

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