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 pinkpixel-dev/skills-collection-1 --skill analyzing-pdf-malware-with-pdfidgit clone --depth 1 https://github.com/pinkpixel-dev/skills-collection-1Wrote 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/pinkpixel-dev/skills-collection-1/analyzing-pdf-malware-with-pdfid)<a href="https://agentmods.dev/skills/pinkpixel-dev/skills-collection-1/analyzing-pdf-malware-with-pdfid"><img src="https://agentmods.dev/badge/skills/pinkpixel-dev/skills-collection-1/analyzing-pdf-malware-with-pdfid/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/pinkpixel-dev/skills-collection-1/analyzing-pdf-malware-with-pdfid"><img src="https://agentmods.dev/badge/skills/pinkpixel-dev/skills-collection-1/analyzing-pdf-malware-with-pdfid.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 | $0.00084 | $0.03056 |
| Opus 5 | $0.00042 | $0.01528 |
| Sonnet 5 | $0.00017 | $0.00611 |
| Haiku 4.5 | $0.00008 | $0.00306 |
Grade A, and why
analyzing-pdf-malware-with-pdfid 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 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( This is a copy
92% identical to analyzing-pdf-malware-with-pdfid — 25 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 — 337 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyzing PDF Malware with PDFiD
When to Use
- A suspicious PDF attachment has been flagged by email security or reported by a user
- You need to determine if a PDF contains embedded JavaScript, shellcode, or exploit code
- Triaging PDF documents before opening them in a sandbox or analysis environment
- Extracting embedded executables, scripts, or URLs from malicious PDF objects
- Analyzing PDF exploit kits targeting Adobe Reader or other PDF viewer vulnerabilities
Do not use for analyzing the rendered visual content of a PDF; this is for structural analysis of the PDF file format for malicious objects.
Prerequisites
- Python 3.8+ with Didier Stevens' PDF tools installed (
pip install pdfid pdf-parser) - peepdf installed for interactive PDF analysis (
pip install peepdf) - pdftotext from poppler-utils for extracting text content safely
- YARA with PDF-specific rules for malware family identification
- Isolated analysis VM without a PDF reader installed (prevent accidental opening)
- CyberChef for decoding embedded Base64, hex, or deflate streams
Workflow
Step 1: Initial Triage with PDFiD
Scan the PDF for suspicious keywords and structures:
# Run PDFiD to identify suspicious elements
pdfid suspect.pdf
# Expected output analysis:
# /JS - JavaScript (HIGH risk)
# /JavaScript - JavaScript object (HIGH risk)
# /AA - Auto-Action triggered on open (HIGH risk)
# /OpenAction - Action on document open (HIGH risk)
# /Launch - Launch external application (HIGH risk)
# /EmbeddedFile - Embedded file (MEDIUM risk)
# /RichMedia - Flash content (MEDIUM risk)
# /ObjStm - Object stream (used for obfuscation)
# /URI - URL reference (contextual risk)
# /AcroForm - Interactive form (MEDIUM risk)
# Run with extra detail
pdfid -e suspect.pdf
# Run with disarming (rename suspicious keywords)
pdfid -d suspect.pdf
PDFiD Risk Assessment:
━━━━━━━━━━━━━━━━━━━━━
HIGH RISK indicators (any count > 0):
/JS, /JavaScript -> Embedded JavaScript code
/AA -> Automatic Action (triggers without user interaction)
/OpenAction -> Code runs when document is opened
/Launch -> Can launch external executables
/JBIG2Decode -> Associated with CVE-2009-0658 exploit
MEDIUM RISK indicators:
/EmbeddedFile -> Contains embedded files (could be EXE/DLL)
/RichMedia -> Flash/multimedia (Flash exploits)
/AcroForm -> Form with possible submit action
/XFA -> XML Forms Architecture (complex attack surface)
LOW RISK indicators:
/ObjStm -> Object streams (obfuscation technique)
/URI -> External URL references
/Page -> Number of pages (context only)
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 337 lines · 84 tokens per session scan A 5b0b44b860df
analyzing-pdf-malware-with-pdfid is a skill published in the GitHub repository pinkpixel-dev/skills-collection-1 (7 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 84 tokens to every session and 3,056 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). It is 92% identical to analyzing-pdf-malware-with-pdfid, differing in 25 lines, and is treated as a copy.
Other skills, from other repositories
analyzing-pdf-malware-with-pdfid
Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious…
analyzing-pdf-malware-with-pdfid
A guide for examining a PDF’s internal structure to find malicious content without opening it in a PDF reader. It looks for JavaScript, automatic actions, exploit code, embedded files, and other suspicious objects.
analyzing-pdf-malware-with-pdfid
Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious…
analyzing-pdf-malware-with-pdfid
Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious…
analyzing-pdf-malware-with-pdfid
Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious…
analyzing-pdf-malware-with-pdfid
Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious…