Answers from the documentation; checking which model is on duty
Hi - I answer from the OpenSmartRoute documentation: routing, the API, plans and quotas, self-hosting. Ask away, or open a support ticket if you need a person.
Grounded in the docs - follow a source before acting on it.
Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects. Use when triaging a suspicious PDF attachment
Imported from mukul975/anthropic-cybersecurity-skills (skills/analyzing-malicious-pdf-with-peepdf/SKILL.md) via skills.sh. Install upstream with npx skills add mukul975/anthropic-cybersecurity-skills --skill analyzing-malicious-pdf-with-peepdf. Copyright stays with the author (Apache-2.0).
Analyzing Malicious PDF with peepdf
When to Use
When triaging suspicious PDF attachments from phishing emails
During malware analysis of PDF-based exploit documents
When extracting embedded JavaScript, shellcode, or executables from PDFs
For forensic examination of weaponized document artifacts
When building detection signatures for PDF-based threats
Prerequisites
Python 3.8+ with peepdf-3 installed (pip install peepdf-3)
pdfid.py and pdf-parser.py from Didier Stevens suite
Isolated analysis environment (VM or sandbox)
Optional: PyV8 for JavaScript emulation within peepdf
Optional: Pylibemu for shellcode analysis
Workflow
Triage with pdfid: Scan PDF for suspicious keywords (/JS, /JavaScript, /OpenAction, /Launch, /EmbeddedFile).
Interactive Analysis: Open PDF in peepdf interactive mode to explore object structure.
Install analyzing-malicious-pdf-with-peepdf and it becomes one more candidate the router can pick - when it fits.
A listing is a routing target with a manifest: what it does, which domains it covers, what it costs and who publishes it. Once installed it sits beside your own models and tools, is scored like any other candidate for each request, and shows up in the trace when it wins. Ratings come from workspaces that installed it, one per account.
When a provider is down or over quota the request moves on; the trace says it did.
Use it
Copy one of these into your project. Installing also returns the manifest and these snippets.
# after Install: the listing is in your workspace's routing pool - a plan picks it for its slotcurl-s-X POST https://api.opensmartroute.ai/api/v1/route -H 'Authorization: Bearer $OSR_API_KEY' -H 'Content-Type: application/json' -d '{"text": "...", "plan": true}'
Manifest
An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.
{
"ocm": "1",
"id": "mukul975-anthropic-cybersecurity-skills-analyzing-malici-4e49e7",
"kind": "skill",
"name": "analyzing-malicious-pdf-with-peepdf",
"description": "Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects. Use when triaging a suspicious PDF attachment from a phishing email, analyzing a PDF-based exploit document, or building detection signatures for weaponized PDF threats.",
"publisher": "mukul975",
"version": "1.0.0",
"capabilities": {
"domains": [
"coding"
],
"tags": [
"skill-md",
"malware-analysis",
"pdf",
"peepdf",
"pdfid",
"pdf-parser",
"static-analysis",
"reverse-engineering",
"dfir",
"skills-sh"
],
"languages": [
"en"
]
},
"quality_prior": 0.6,
"examples": [
"Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects. Use when triaging a suspicious PDF attachment from a phishing email, analyzing a PDF-based exploit document, or building detection signatures for weaponized PDF threats."
],
"primary": false,
"metadata": {
"source": {
"provider": "skills.sh",
"repository": "https://github.com/mukul975/anthropic-cybersecurity-skills",
"path": "skills/analyzing-malicious-pdf-with-peepdf/SKILL.md",
"ref": "HEAD",
"url": "https://www.skills.sh/mukul975/anthropic-cybersecurity-skills/analyzing-malicious-pdf-with-peepdf",
"key": "mukul975/anthropic-cybersecurity-skills/skills/analyzing-malicious-pdf-with-peepdf/SKILL.md"
},
"license": "Apache-2.0"
},
"instructions": "# Analyzing Malicious PDF with peepdf\n\n## When to Use\n\n- When triaging suspicious PDF attachments from phishing emails\n- During malware analysis of PDF-based exploit documents\n- When extracting embedded JavaScript, shellcode, or executables from PDFs\n- For forensic examination of weaponized document artifacts\n- When building detection signatures for PDF-based threats\n\n## Prerequisites\n\n- Python 3.8+ with peepdf-3 installed (pip install peepdf-3)\n- pdfid.py and pdf-parser.py from Didier Stevens suite\n- Isolated analysis environment (VM or sandbox)\n- Optional: PyV8 for JavaScript emulation withi",
"cost": {
"context_tokens": 620
}
}
Fetch it by URL: GET /api/v1/registry/mukul975-anthropic-cybersecurity-skills-analyzing-malici-4e49e7/manifest?version=1.0.0
Reviews
Star ratings from people who tried it. One review per account; edit yours any time.
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