MALICIOUS
154
Risk Score
Machine Learning
- Nyx PDF Classifier malicious score 1.0000
Heuristics 5
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PDF links to known malicious redirector infrastructure critical PDF_MALICIOUS_REDIRECTOR_LINKPDF contains a clickable URI to redirector infrastructure used by a known malicious PDF SEO/adware delivery campaign. These documents typically rely on user interaction and redirect chains rather than a PDF parser vulnerability.
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Image lure linking to an SEO redirector (free-download phishing) high PDF_SEO_UTM_REDIRECTOR_LINKPDF embeds an image with little or no body text and a clickable link to a multi-word utm_term / FeedBurner-proxied SEO redirector — the 'free ebook / solution-manual / document download' phishing family that ranks for natural-language search queries and routes the user into a payload/redirect chain. The PDF carries no exploit; the risk is the linked destination. Flagged structurally (image lure + SEO redirector) so it does not depend on a ClamAV/ML signature, and regardless of how many filler text pages the lure carries.
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QR-code redirect lure medium SE_QR_LUREDocument instructs the user to scan a QR code with a phone — consistent with QR phishing, but also common in legitimate documents
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Object number defined twice with different bodies info PDF_DUPLICATE_OBJ_BODY_INCREMENTALThe same indirect object (N G) is defined more than once with different body bytes. First-wins and last-wins readers will resolve different content, which is a parser-confusion shape used by targeted PDFs. Body-only differences are common in benign incremental updates, so severity is raised only when the duplicate carries active content.
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Embedded URL info EMBEDDED_URLOne or more URLs were extracted from the document. The URL itself is not a detection — see the per-URL labels for which channel (macro, JS, link annotation, document body, ...) reached each URL.URL https://ggtraff.ru/aws?keyword=health+the+basics+11th+edition+pdf+free In PDF document text
- https://cdn-cms.f-static.net/uploads/4369173/normal_5f8b8f2c1f806.pdfIn PDF document text
- https://cdn-cms.f-static.net/uploads/4368788/normal_5f89cb451adc3.pdfIn PDF document text
- https://cdn-cms.f-static.net/uploads/4384150/normal_5f8f15e48aaeb.pdfIn PDF document text
- https://cdn-cms.f-static.net/uploads/4379500/normal_5f963399151f9.pdfIn PDF document text
- https://cdn-cms.f-static.net/uploads/4413966/normal_5f9a3da6efe1a.pdfIn PDF document text
- https://cdn-cms.f-static.net/uploads/4368497/normal_5f9118da342f0.pdfIn PDF document text
- https://cdn-cms.f-static.net/uploads/4387816/normal_5f983f8c6c28a.pdfIn PDF document text
- https://cdn-cms.f-static.net/uploads/4366987/normal_5f93b897c9d9f.pdfIn PDF document text
- https://cdn-cms.f-static.net/uploads/4383450/normal_5f8c6ed9ddaee.pdfIn PDF document text
- http://www.ascendercorp.com/In PDF document text
- http://www.ascendercorp.com/typedesigners.htmlIn PDF document text
- https://uploads.strikinglycdn.com/files/c1a35bb2-6904-414e-8b75-d1a06fe8fb22/gojuxitizofuvik.pdfIn PDF document text
- https://uploads.strikinglycdn.com/files/c2ed461c-b23a-4c5b-a6ea-96376d440fcd/bonegowewukategimuxemiji.pdfIn PDF document text
- https://uploads.strikinglycdn.com/files/9de5d996-e582-4a34-8774-b9fc2b6a7fd0/python_artificial_intelligence_tutorial.pdfIn PDF document text
- http://www.w3.org/1999/02/22-rdf-syntax-ns#In PDF document text
- http://purl.org/dc/elements/1.1/In PDF document text
- http://ns.adobe.com/pdf/1.3/In PDF document text
- http://ns.adobe.com/xap/1.0/In PDF document text
- http://ns.adobe.com/xap/1.0/mm/In PDF document text
- http://ns.adobe.com/xap/1.0/rights/In PDF document text
- http://scripts.sil.org/OFLIn PDF document text
Extracted artifacts 2
Files carved from inside the sample during analysis.
| Filename | Kind | Source | Size |
|---|---|---|---|
font_00_sfnt_off0000848b.bin |
pdf-font-stream | PDF embedded font (sfnt) at offset 0x848B | 5396 bytes |
SHA-256: 0cc4dc3e1ede18c12105a252e064676ca05ddf6ac0b0e54a9d1d3a3a6487c914 |
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font_01_sfnt_off000096d5.bin |
pdf-font-stream | PDF embedded font (sfnt) at offset 0x96D5 | 12360 bytes |
SHA-256: f573f0f3338cd866d7f12384457059b18ea256716a81462e07a361a7130bc18a |
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