Malicious PDF — malware analysis report

Static analysis result for SHA-256 0cf40997ff43c0d4…

MALICIOUS

PDF

41.6 KB Created: 2020-10-27 06:50:20 +02:00 Authoring application: wkhtmltopdf 0.12.5 (via Qt 4.8.7) First seen: 2020-12-26
MD5: e9112a3a7f706ab84db0681ae7ee0e2a SHA-1: e036fdcc1e50cabfdea6e175f510989ffaba1a8d SHA-256: 0cf40997ff43c0d40fb92a29da52bebbaabfa31ecdd9c1a490c4d8d5a8b13a99
194 Risk Score

Machine Learning

  • Nyx PDF Classifier malicious score 1.0000

Heuristics 5

  • PDF links to known malicious redirector infrastructure critical PDF_MALICIOUS_REDIRECTOR_LINK
    PDF 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.
  • Small PDF contains mass external PDF link farm critical PDF_SEO_LINK_FARM
    Small 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.
  • Image lure linking to an SEO redirector (free-download phishing) high PDF_SEO_UTM_REDIRECTOR_LINK
    PDF 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.
  • Object number defined twice with different bodies info PDF_DUPLICATE_OBJ_BODY_INCREMENTAL
    The 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.
  • Embedded URL info EMBEDDED_URL
    One 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.me/123?keyword=chain+come+along+for+sale In PDF document text
    • https://cdn-cms.f-static.net/uploads/4413457/normal_5f952dd3d1fef.pdfIn PDF document text
    • https://cdn-cms.f-static.net/uploads/4375690/normal_5f8fb75007e45.pdfIn PDF document text
    • https://cdn-cms.f-static.net/uploads/4371788/normal_5f8a86915e98e.pdfIn PDF document text
    • http://www.ascendercorp.com/In extracted file (font_00_sfnt_off000065ea.bin)
    • http://www.ascendercorp.com/typedesigners.htmlIn extracted file (font_00_sfnt_off000065ea.bin)
    • https://s3.amazonaws.com/saxefi/job_offer_letter_format.pdfIn PDF document text
    • https://s3.amazonaws.com/jebokizez/wibexalabututirakipif.pdfIn PDF document text
    • https://s3.amazonaws.com/vaxebisapesi/kikadefuvilekosudaxon.pdfIn PDF document text
    • https://s3.amazonaws.com/gupuso/suxuzeruja.pdfIn PDF document text
    • https://s3.amazonaws.com/ribowexulo/63151267029.pdfIn PDF document text
    • https://s3.amazonaws.com/xovajukoxin/tnpsc_assistant_system_engineer_study_material.pdfIn PDF document text
    • https://s3.amazonaws.com/sugaguxagu/bapogoj.pdfIn PDF document text
    • https://s3.amazonaws.com/jasadavebaga/nodebivagumep.pdfIn PDF document text
    • https://s3.amazonaws.com/henghuili-files2/35774421219.pdfIn PDF document text
    • https://s3.amazonaws.com/susopuzupure/acrylamide_in_coffee.pdfIn PDF document text
    • https://s3.amazonaws.com/jiwisigetizoxif/how_to_listen_effectively.pdfIn PDF document text
    • https://s3.amazonaws.com/leguvefu/35600502830.pdfIn PDF document text
    • https://s3.amazonaws.com/mijedusovineti/learn_python_language.pdfIn PDF document text
    • https://cdn.shopify.com/s/files/1/0478/9754/2822/files/chief_education_officer_dehradun.pdfIn PDF document text
    • https://cdn.shopify.com/s/files/1/0499/3938/2430/files/gozukazojajebev.pdfIn PDF document text
    • https://cdn.shopify.com/s/files/1/0435/0862/9659/files/lofadiwetux.pdfIn PDF document text
    • https://cdn.shopify.com/s/files/1/0432/1460/2401/files/nufagubokukuzi.pdfIn PDF document text
    • https://cdn.shopify.com/s/files/1/0428/5834/8703/files/17374400488.pdfIn PDF document text
    • https://cdn.shopify.com/s/files/1/0499/1595/3320/files/writing_two_step_equations_worksheet_answers.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 extracted file (font_00_sfnt_off000065ea.bin)

Extracted artifacts 2

Files carved from inside the sample during analysis.

FilenameKindSourceSize
font_00_sfnt_off000065ea.bin pdf-font-stream PDF embedded font (sfnt) at offset 0x65EA 5200 bytes
SHA-256: b7b00627cef89e13e79ca866112a9e01d6b041546174c8c44fc17a037ca20b14
font_01_sfnt_off0000776c.bin pdf-font-stream PDF embedded font (sfnt) at offset 0x776C 9896 bytes
SHA-256: 9a72949221c5a43cba8e530b32272630c8a80b6123d3a0013aee48bca287a4ba