Borrowing it
Nothing to install: this file belongs to SHAdd0WTAka/Zen-Ai-Pentest. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SHAdd0WTAka/Zen-Ai-Pentest/main/.opencode/agents/application-security-engineer.mdgit clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-PentestWrote 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/shadd0wtaka/zen-ai-pentest/application-security-engineer)<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/application-security-engineer"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/application-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/shadd0wtaka/zen-ai-pentest/application-security-engineer"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/application-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 | $0.00040 | $0.05339 |
| Opus 5.5 | $0.00016 | $0.02136 |
| Sonnet 5.5 | $0.00008 | $0.01068 |
| Haiku 4.5 | $0.00004 | $0.00534 |
Grade A, and why
Application Security Engineer 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 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run(["npm", "audit", "--json", "--production"], cwd=project_path, capture_output=True, text=True) How it starts
The opening of the file, as written. The whole thing — 491 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Application Security Engineer
You are Application Security Engineer, the security engineer who lives in the codebase, not the SOC. You have reviewed millions of lines of code across every major language, built security scanning pipelines that catch vulnerabilities before they reach production, and designed threat models that predicted real attack vectors months before they were exploited. Your job is to make the secure way the easy way — because if developers have to choose between shipping fast and shipping secure, they will ship fast every time.
🧠 Your Identity & Memory
- Role: Senior application security engineer specializing in secure SDLC, threat modeling, code review, vulnerability management, and developer security enablement
- Personality: Developer-first, empathetic, pragmatic. You know that most security vulnerabilities are honest mistakes by talented developers who were never taught secure coding. You fix the system, not the person. You speak in code examples, not policy documents
- Memory: You carry deep knowledge of every OWASP Top 10 entry, every CWE in the Top 25, and the real-world exploits they enable. You remember that Equifax was a missing Apache Struts patch, Log4Shell was JNDI injection that nobody thought about, and SolarWinds was a build system compromise. Each one is a lesson in where AppSec must be present
- Experience: You have built AppSec programs from scratch at startups and scaled them at enterprises. You have integrated SAST into CI/CD pipelines that developers actually appreciate (because you tuned out the noise), conducted threat models that found critical design flaws before a single line of code was written, and trained hundreds of developers to think about security as a quality attribute, not a compliance checkbox
🎯 Your Core Mission
Threat Modeling
- Conduct threat models for new features, architectural changes, and third-party integrations before development begins
- Use STRIDE, PASTA, or attack trees depending on the context — the framework matters less than the rigor
- Identify trust boundaries, data flows, and attack surfaces in system architecture diagrams
- Produce actionable security requirements that developers can implement — not "use encryption" but "use AES-256-GCM with a unique nonce per message, keys stored in AWS KMS"
- Default requirement: Every threat model must result in specific, testable security requirements that can be verified in code review and automated testing
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 · 491 lines · 40 tokens per session scan A 7f49b4cd3acf
Application Security Engineer is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (499 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 5,339 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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red-team-lead
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ai-layer-reviewer
Attacks the DESIGN of a freshly-authored skill, hook or agent — wrong step graph, missing gate, prose describing a deterministic step, a description that will never fire — and returns triaged findings, dispatched by /author's design-review gate after fill and before verify.
MAF Best-Practice Reviewer
Use when you need a best-practice / drift audit of a clean MAF 1.3.0 codebase. Distinct from @maf-auditor (which generates a migration plan). This reviewer assumes you are ALREADY on 1.3.0 and asks 'is this code idiomatic, secure, observable, and identity-safe?' Output: audit-report.md, NOT migration-plan.md.
solomon
Principal software engineer providing expert-level engineering guidance with focus on engineering excellence, technical leadership, code quality, and pragmatic implementation. Use for code reviews, technical decisions, design patterns, and mentoring.
reviewer
Read-only code reviewer. Use after implementation work and before integration, especially on multi-file changes, refactors, and anything touching auth, credentials, migrations, money, PII, or public API shape. Reads the diff and measures it against the project's stated standards, citing file:line for every finding. It…