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.
npx skills add h4vzz/awesome-ai-agent-skills --skill dynamic-application-security-testinggit clone --depth 1 https://github.com/h4vzz/awesome-ai-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/skills/h4vzz/awesome-ai-agent-skills/dynamic-application-security-testing)<a href="https://agentmods.dev/skills/h4vzz/awesome-ai-agent-skills/dynamic-application-security-testing"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/dynamic-application-security-testing/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/skills/h4vzz/awesome-ai-agent-skills/dynamic-application-security-testing"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/dynamic-application-security-testing.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 | $0.00026 | $0.02159 |
| Opus 5 | $0.00013 | $0.01079 |
| Sonnet 5 | $0.00005 | $0.00432 |
| Haiku 4.5 | $0.00003 | $0.00216 |
Grade A, and why
dynamic-application-security-testing 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 7d 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
88% identical to dynamic-application-security-testing — 9 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dynamic Application Security Testing
This skill enables the agent to perform Dynamic Application Security Testing (DAST) against running web applications and APIs. Unlike static analysis, DAST interacts with the application at runtime — sending crafted HTTP requests, fuzzing input parameters, and analyzing responses to detect vulnerabilities such as SQL injection, cross-site scripting, server misconfigurations, broken authentication, and insecure API endpoints. The agent configures scan profiles, handles authenticated scanning, interprets results, and produces actionable remediation reports.
Workflow
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Define Target Scope and Scan Policy — Specify the target URL, application type (traditional web app, SPA, REST API, GraphQL), and scan boundaries. Define which paths and domains are in scope to prevent scanning unintended targets. Select a scan policy: passive-only for low-risk reconnaissance, active for full vulnerability probing, or API-specific for endpoint fuzzing.
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Configure Authentication — For applications behind a login, configure the scanner with valid credentials or session tokens. Set up form-based authentication by specifying the login URL, username/password fields, and a logged-in indicator string. For API testing, configure Bearer tokens, API keys, or OAuth flows so the scanner can reach authenticated endpoints.
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Execute the DAST Scan — Launch the scan using the selected tool (OWASP ZAP, Burp Suite, or Nuclei). The scanner first spiders the application to discover endpoints, then actively probes each endpoint with attack payloads. Monitor scan progress and resource consumption to avoid overwhelming the target environment.
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Analyze and Classify Findings — Review scan results and classify each finding by vulnerability type, severity (using CVSS), confidence level, and affected URL. Filter out informational noise and false positives by verifying that the reported response actually demonstrates the vulnerability.
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Generate Remediation Report — Produce a structured report containing each finding with the vulnerable URL, HTTP request/response evidence, severity rating, CWE identifier, OWASP category mapping, and specific remediation guidance. Export in HTML, JSON, or SARIF format for integration with issue trackers.
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.
- 7d ago First seen · 163 lines · 26 tokens per session scan A 0c712d7fbb9e
dynamic-application-security-testing is a skill published in the GitHub repository h4vzz/awesome-ai-agent-skills (34 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 2,159 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to dynamic-application-security-testing, differing in 9 lines, and is treated as a copy.
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