MALICIOUS
152
Risk Score
Malware Insights
MITRE ATT&CK
T1566.002 Spearphishing Attachment
T1204.002 Malicious Link
The sample is a PDF file identified as malicious by a machine learning classifier and heuristic rules. It contains a significant number of embedded links, with at least one pointing to a known malicious redirector. The document body, though heavily obfuscated, contains the URL 'https://ttraff.cc/wix?keyword=modern+control+engineering+ogata', which is also listed as a malicious redirector. The presence of a link farm suggests an attempt to distribute malicious content or conduct phishing operations.
Machine Learning
- Nyx PDF Classifier malicious score 1.0000
Heuristics 4
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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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Small PDF contains mass external PDF link farm critical PDF_SEO_LINK_FARMSmall PDF contains many clickable external PDF links, mostly clustered on one host. This matches generated SEO/link-farm PDF carriers used to route users into malicious or unwanted-software delivery chains, rather than a normal document citation pattern.
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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://ttraff.cc/wix?keyword=modern+control+engineering+ogata
- https://static.usrfiles.com/ugd/b8c837_41a4300a82a9462787159e78bc8f7f84.pdf
- https://static.usrfiles.com/ugd/b8c837_d4960a152b724b51b4f3158374e3ba99.pdf
- https://static.usrfiles.com/ugd/99965f_6809d334c90046f8a99689565c9168ec.pdf
- https://static.usrfiles.com/ugd/b8c837_0dacff84051347828630362e22c5b731.pdf
- https://static.usrfiles.com/ugd/b8c837_3ca58c4e6cab43598fca0da527ce038e.pdf
- https://static.usrfiles.com/ugd/b8c837_236f357a6a844886b6b9d1d0f9d061e1.pdf
- https://static.usrfiles.com/ugd/82e28d_761f9a5728c34367a31115fd36651fd2.pdf
- https://static.usrfiles.com/ugd/23e9be_6502e734e6704028abbdbae5dac9461e.pdf
- https://static.usrfiles.com/ugd/93c935_84870a89864241f19c5d55e7bed5514f.pdf
- https://cdn.shopify.com/s/files/1/0434/8359/4909/files/fibovupujufidinomib.pdf
- https://cdn.shopify.com/s/files/1/0434/4935/2349/files/gumesoxexoseko.pdf
- https://cdn.shopify.com/s/files/1/0437/5507/7781/files/affective_learning_theory.pdf
- https://cdn.shopify.com/s/files/1/0463/3427/9837/files/cch_axcess_dashboard.pdf
- https://cdn.shopify.com/s/files/1/0432/6116/5723/files/55515862825.pdf
- https://cdn.shopify.com/s/files/1/0430/2359/7725/files/nufumifutireni.pdf
- https://cdn.shopify.com/s/files/1/0429/8866/7034/files/37190946224.pdf
- http://www.w3.org/1999/02/22-rdf-syntax-ns#
- http://purl.org/dc/elements/1.1/
- http://ns.adobe.com/pdf/1.3/
- http://ns.adobe.com/xap/1.0/
- http://ns.adobe.com/xap/1.0/mm/
- http://ns.adobe.com/xap/1.0/rights/
- https://cdn.shopify.com/s/files/1/
Extracted artifacts 2
Files carved from inside the sample during analysis.
| Filename | Kind | Source | Size |
|---|---|---|---|
font_00_sfnt_off00004c85.binbf8a0f966565c53ba778402fa2ad5b4d29474553549d1904cb11e82f23ce101f |
pdf-font-stream | PDF embedded font (sfnt) at offset 0x4C85 | 4936 bytes |
font_01_sfnt_off00005d5e.bind528b13ba038386d3b12b0ff2979a08216f434ce4948861f1a40d6beaaafada8 |
pdf-font-stream | PDF embedded font (sfnt) at offset 0x5D5E | 10164 bytes |
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