application-security-pentesting

application-security-pentesting is a skill for Claude Code, Codex from hamzabellouch/agent-skills. It costs 43 tokens per session (1,752 once invoked), scanned A, original, MIT.

A defensive guide to application security, covering threat modeling, secure code review, vulnerability assessment, and protections against common web risks.

In plain words
What is it for?
Use it to review application code, assess OWASP Top 10 risks, connect static and dynamic security checks to pipelines, and design safer authentication and permissions.
Why use it?
It helps find and fix weaknesses such as injection and cross-site scripting before attackers can use them.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to review application code, assess OWASP Top 10 risks, connect static and dynamic security checks to pipelines, and design safer authentication and permissions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hamzabellouch/agent-skills/application-security-pentesting
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.

Any agent
npx skills add hamzabellouch/agent-skills --skill application-security-pentesting
Clone the repo
git clone --depth 1 https://github.com/hamzabellouch/agent-skills

Made for: Claude Code, Codex.

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 application-security-pentesting

README.md
[![agentmods](https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/application-security-pentesting/github.svg)](https://agentmods.dev/skills/hamzabellouch/agent-skills/application-security-pentesting)
Your own site
<a href="https://agentmods.dev/skills/hamzabellouch/agent-skills/application-security-pentesting"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/application-security-pentesting/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.

agentmods 80×15 button for application-security-pentesting

Your own site · 80×15
<a href="https://agentmods.dev/skills/hamzabellouch/agent-skills/application-security-pentesting"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/application-security-pentesting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,752 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00043 $0.01752
Opus 5 $0.00022 $0.00876
Sonnet 5 $0.00009 $0.00350
Haiku 4.5 $0.00004 $0.00175

Measured 8d ago against content hash 78770c8e1e54, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

application-security-pentesting 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.

Cybersecurity and Penetration Testing/application-security-pentesting/SKILL.md · 185 lines

How it starts

The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Application Security & Penetration Testing Remediation

Overview

This skill provides standards and methodological frameworks for Application Security (AppSec) engineering, threat modeling, vulnerability assessment, and remediation of OWASP Top 10 vulnerabilities. It covers secure code review, static and dynamic analysis (SAST/DAST) integration, security headers configuration, and defensive controls.


1. Core Application Security Principles

  1. Defense-in-Depth Architecture: Never rely on a single defensive boundary. Enforce security controls at every application layer (Network, Gateway, Application Code, Database).
  2. Strict Input Sanitization & Parameterization: Treat all user inputs as untrusted. Enforce parameterized queries (Prepared Statements) for database access to eliminate SQL injection, and context-aware HTML encoding to prevent XSS.
  3. Principle of Least Privilege (PoLP): Grant minimum required API permissions, database permissions, and system rights to microservices and database users.
  4. Secure Authentication & Session Lifecycle: Enforce multi-factor authentication (MFA), secure HTTP-Only SameSite cookies, session rotation on privilege escalation, and strong password hashing algorithms (Argon2id, bcrypt).
  5. Continuous Security Automation (DevSecOps): Integrate Static Application Security Testing (SAST), Dependency Scanning (SCA), and Dynamic Application Security Testing (DAST) into CI/CD pipelines.

2. Threat Modeling & Vulnerability Remediation Lifecycle

[ Application Codebase ]
       │
       ├──▶ [ SAST Scanner (Semgrep / SonarQube) ] ──(Code Flaws)
       ├──▶ [ SCA Scanner (Trivy / Dependabot) ] ────(Vulnerable Dependencies)
       ▼
[ Security Audit Engine ]
       │
       │ 1. Triaging & Threat Modeling (STRIDE / DREAD)
       ▼
[ Security Remediation Pipeline ]
       │ 2. Apply Parameterization & Sanitization
       ▼
[ DAST Verification (OWASP ZAP) ] ──▶ [ Hardened Production Deployment ]
Vulnerability Class Root Cause Primary Defensive Remediation
SQL Injection (SQLi) String concatenation in database queries Parameterized Prepared Statements
Cross-Site Scripting (XSS) Unescaped output rendered in HTML context Content Security Policy (CSP) & DOM Encoding
Broken Access Control Missing authorization checks on record IDs Server-side RBAC / ABAC evaluation
CSRF Cross-origin request forgery on cookie auth Anti-CSRF Tokens & SameSite=Strict cookies
Insecure Direct Object Reference (IDOR) Exposing raw database primary keys Tenant-scoped database queries & UUIDs

Read the full file on GitHub · 185 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. 8d ago First seen · 185 lines · 43 tokens per session scan A 78770c8e1e54

Subscribe to this mod's changes

application-security-pentesting is a skill published in the GitHub repository hamzabellouch/agent-skills (4 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 1,752 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 2026-09-03.

Related

Other skills, from other repositories

code-review-and-quality

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.

addyosmani/agent-skills · 51 tokens

doubt-driven-development

Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high…

addyosmani/agent-skills · 96 tokens

code-simplification

Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.

addyosmani/agent-skills · 51 tokens

agents-consilium

Run external coding agents (Codex, Claude Code, OpenCode, native Grok Build, Gemini) as independent reviewers, stateful repository researchers, or single-agent implementers. Use for multi-model opinions and code review, steerable Grok research, full-access delegation, long-running work, or reattaching to delegated…

CodeAlive-AI/ai-driven-development · 86 tokens

refactoring-csharp

Rename and refactor C# symbols in a .NET solution or multi-solution monorepo with a one-shot Roslyn CLI. Use when the user asks to rename a symbol, preview impact, update references across a solution, or refactor shared projects across several solutions.

CodeAlive-AI/ai-driven-development · 60 tokens

agentic-readiness

Audit and improve repositories for reliable agentic work across Codex and Codex App, Claude Code, and OpenCode. Use when reviewing AGENTS.md or CLAUDE.md quality and discovery, instruction routing in monorepos or meta-repos, agent settings, MCP configuration, skills, subagents, context budgets, or repository…

CodeAlive-AI/ai-driven-development · 76 tokens