Malicious PDF — malware analysis report

Static analysis result for SHA-256 5d45ebdd64671c18…

MALICIOUS

PDF

24.0 KB
MD5: 0cd5e908bacdeaaf724552b87ed1f8b2 SHA-1: 69e0c71e2a6a4a6a1b0bca710646ad78315cb147 SHA-256: 5d45ebdd64671c182c05e9458cd4c1553eca0609fa7cf53d738db6f792babab4
162 Risk Score

Malware Insights

MITRE ATT&CK
T1203 Exploitation for Client Execution

The sample is a PDF file identified as malicious by multiple heuristics and a machine learning classifier. It contains an exploit for CVE-2010-0188, targeting a vulnerability in Adobe Reader's handling of XFA forms. This exploit is designed to execute arbitrary code on the victim's machine.

Machine Learning

  • Nyx PDF Classifier malicious score 1.0000

Heuristics 5

  • Adobe Reader LibTIFF XFA image exploit — CVE-2010-0188 critical CVE likely CVE_2010_0188
    PDF contains the CVE-2010-0188 exploit template: XFA JavaScript heap-spray setup, a generated TIFF image payload, and assignment of that TIFF data to an XFA image field rawValue to trigger Adobe Reader's LibTIFF parser.
  • ClamAV: Pdf.Exploit.Agent-36821 critical CLAMAV_DETECTION
    ClamAV detected this file as malware: Pdf.Exploit.Agent-36821
  • XFA form low PDF_XFA
    PDF uses XML Forms Architecture — can contain script logic
  • PDF differential parser failed info PDF_DIFFERENTIAL_PARSE_FAILED
    The cross-check parser (pdfminer.six) failed on this file: PDF differential parser failed: PSEOF. Static heuristics still ran and any of their findings above are valid; only the differential cross-check signal is missing.
  • 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 http://www.xfa.org/schema/xfa-template/2.5/

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