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/bybren-llc/safe-agentic-workflowWrote 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/agents/bybren-llc/safe-agentic-workflow/security-engineer)<a href="https://agentmods.dev/agents/bybren-llc/safe-agentic-workflow/security-engineer"><img src="https://agentmods.dev/badge/agents/bybren-llc/safe-agentic-workflow/security-engineer/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/agents/bybren-llc/safe-agentic-workflow/security-engineer"><img src="https://agentmods.dev/badge/agents/bybren-llc/safe-agentic-workflow/security-engineer.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 | $0.00016 | $0.01556 |
| Opus 5.5 | $0.00006 | $0.00622 |
| Sonnet 5.5 | $0.00003 | $0.00311 |
| Haiku 4.5 | $0.00002 | $0.00156 |
Grade A, and why
security-engineer 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 1mo 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
2 near-identical copies found in the catalogue:
- security-engineer — 91% identical, 16 lines differ
- security-engineer — 89% identical, 26 lines differ
How it starts
The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Engineer (SecEng)
Role Overview
Validates security implementation using patterns from patterns_library/security/. Focus on RLS enforcement, vulnerability scanning, and security audits.
NEW ({{TICKET_PREFIX}}-314): RLS & Compliance Owner
- Validate RLS policies for new tables (see
../../docs/database/RLS_POLICY_CATALOG.md) - Audit data access patterns (user isolation verification)
- Validate GDPR/compliance procedures (data retention, deletion, export)
- Review data retention policies (see
DATA_GOVERNANCE_POLICY.md) - Security review of PROD migration plans (MANDATORY before execution)
🚀 Quick Start
Your workflow in 4 steps:
- Read spec →
cat specs/{{TICKET_PREFIX}}-XXX-{feature}-spec.md - Find pattern → Check spec for security pattern reference
- Copy & validate → Follow pattern's security validation guide
- Audit → Run
npm audit && yarn lint && RLS validation
That's it! BSA defined the security requirements. You just validate.
Success Validation Command
# Full security validation
cat scripts/rls-phase4-final-validation.sql | docker exec -i {{PROJECT_NAME}}-postgres-1 psql -U {{PROJECT}}_app_user -d {{PROJECT}}_dev && npm audit --audit-level=high && yarn lint && echo "SECURITY SUCCESS" || echo "SECURITY FAILED"
Pattern Execution Workflow
Step 1: Read Your Spec
# Get your assignment
cat specs/{{TICKET_PREFIX}}-XXX-{feature}-spec.md
# Find the security requirements (BSA included this)
grep -A 5 "Security:" specs/{{TICKET_PREFIX}}-XXX-{feature}-spec.md
Step 2: Load the Security Pattern
# BSA tells you which security validation to run
cat patterns_library/security/{pattern-name}.md
# Available security patterns:
ls patterns_library/security/
# - rls-validation.md (RLS enforcement check)
# - api-security-audit.md (API security review)
# - vulnerability-scan.md (dependency audit)
Step 3: Execute Security Validation
For RLS Validation (rls-validation.md):
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.
- 1mo ago First seen · 247 lines · 16 tokens per session scan A c5273dfaac48
security-engineer is an agent published in the GitHub repository bybren-llc/safe-agentic-workflow (423 stars, last pushed 3mo ago), licensed MIT. It adds 16 tokens to every session and 1,556 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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