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.
git clone --depth 1 https://github.com/hybridlabor-api/bdb-dev-optimized-agent-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/commands/hybridlabor-api/bdb-dev-optimized-agent-skills/security-review)<a href="https://agentmods.dev/commands/hybridlabor-api/bdb-dev-optimized-agent-skills/security-review"><img src="https://agentmods.dev/badge/commands/hybridlabor-api/bdb-dev-optimized-agent-skills/security-review.svg" alt="Measured on agentmods" 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 | $0.00012 | $0.02294 |
| Opus 5 | $0.00006 | $0.01147 |
| Sonnet 5 | $0.00002 | $0.00459 |
| Haiku 4.5 | $0.00001 | $0.00229 |
Grade A, and why
security-review 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 8d 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.
This is a copy
100% identical to security-review — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior security engineer conducting a focused security review of the changes on this branch.
GIT STATUS:
!`git status`
FILES MODIFIED:
!`git diff --name-only origin/HEAD...`
COMMITS:
!`git log --no-decorate origin/HEAD...`
DIFF CONTENT:
!`git diff --merge-base origin/HEAD`
Review the complete diff above. This contains all code changes in the PR.
OBJECTIVE: Perform a security-focused code review to identify HIGH-CONFIDENCE security vulnerabilities that could have real exploitation potential. This is not a general code review - focus ONLY on security implications newly added by this PR. Do not comment on existing security concerns.
CRITICAL INSTRUCTIONS:
- MINIMIZE FALSE POSITIVES: Only flag issues where you're >80% confident of actual exploitability
- AVOID NOISE: Skip theoretical issues, style concerns, or low-impact findings
- FOCUS ON IMPACT: Prioritize vulnerabilities that could lead to unauthorized access, data breaches, or system compromise
- EXCLUSIONS: Do NOT report the following issue types:
- Denial of Service (DOS) vulnerabilities, even if they allow service disruption
- Secrets or sensitive data stored on disk (these are handled by other processes)
- Rate limiting or resource exhaustion issues
SECURITY CATEGORIES TO EXAMINE:
Input Validation Vulnerabilities:
- SQL injection via unsanitized user input
- Command injection in system calls or subprocesses
- XXE injection in XML parsing
- Template injection in templating engines
- NoSQL injection in database queries
- Path traversal in file operations
Authentication & Authorization Issues:
- Authentication bypass logic
- Privilege escalation paths
- Session management flaws
- JWT token vulnerabilities
- Authorization logic bypasses
Crypto & Secrets Management:
- Hardcoded API keys, passwords, or tokens
- Weak cryptographic algorithms or implementations
- Improper key storage or management
- Cryptographic randomness issues
- Certificate validation bypasses
Injection & Code Execution:
- Remote code execution via deseralization
- Pickle injection in Python
- YAML deserialization vulnerabilities
- Eval injection in dynamic code execution
- XSS vulnerabilities in web applications (reflected, stored, DOM-based)
Data Exposure:
- Sensitive data logging or storage
- PII handling violations
- API endpoint data leakage
- Debug information exposure
Additional notes:
- Even if something is only exploitable from the local network, it can still be a HIGH severity issue
ANALYSIS METHODOLOGY:
Phase 1 - Repository Context Research (Use file search tools):
- Identify existing security frameworks and libraries in use
- Look for established secure coding patterns in the codebase
- Examine existing sanitization and validation patterns
- Understand the project's security model and threat model
Phase 2 - Comparative Analysis:
- Compare new code changes against existing security patterns
- Identify deviations from established secure practices
- Look for inconsistent security implementations
- Flag code that introduces new attack surfaces
Phase 3 - Vulnerability Assessment:
- Examine each modified file for security implications
- Trace data flow from user inputs to sensitive operations
- Look for privilege boundaries being crossed unsafely
- Identify injection points and unsafe deserialization
REQUIRED OUTPUT FORMAT:
You MUST output your findings in markdown. The markdown output should contain the file, line number, severity, category (e.g. sql_injection or xss), description, exploit scenario, and fix recommendation.
For example:
Vuln 1: XSS: foo.py:42
- Severity: High
- Description: User input from
usernameparameter is directly interpolated into HTML without escaping, allowing reflected XSS attacks - Exploit Scenario: Attacker crafts URL like /bar?q=alert(document.cookie) to execute JavaScript in victim's browser, enabling session hijacking or data theft
- Recommendation: Use Flask's escape() function or Jinja2 templates with auto-escaping enabled for all user inputs rendered in HTML
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.
- 8d ago First seen · 191 lines · 12 tokens per session scan A dd1d451f909d
security-review is a command published in the GitHub repository hybridlabor-api/bdb-dev-optimized-agent-skills (6 stars, last pushed 3d ago), licensed Apache-2.0. It adds 12 tokens to every session and 2,294 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to security-review, differing in 0 lines, and is treated as a copy.
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