MALICIOUS
66
Risk Score
Malware Insights
MITRE ATT&CK
T1559.001 Component Object Model Hijacking
T1204.002 Malicious File
The PDF document was flagged as highly malicious by a machine learning model with a score of 0.999976. Static analysis revealed the presence of an embedded file and an XFA form, indicating a potential for exploiting vulnerabilities or delivering malicious content. The ML_NYX_PDF_MALICIOUS heuristic firing strongly supports the suspicious verdict.
Machine Learning
- Nyx PDF Classifier malicious score 1.0000
Heuristics 3
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PDF embedded file could not be fully decoded medium PDF_EMBEDDED_FILE_UNDECODEDA declared PDF /EmbeddedFile stream uses filters that the scanner could not decode. The raw stream was carved for artifact triage because malformed or unsupported attachment filters can hide payload content from normal extraction.
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Embedded file low PDF_EMBEDDEDPDF embeds a file attachment — could carry an executable or another weaponised document as a nested payload
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XFA form low PDF_XFAPDF uses XML Forms Architecture — can contain script logic
Extracted artifacts 1
Files carved from inside the sample during analysis.
| Filename | Kind | Source | Size |
|---|---|---|---|
embedded_file_obj0001_undecoded.bin |
pdf-embedded-file-undecodable | PDF EmbeddedFile object 1 at offset 0x50; filter decode failed | 1281 bytes |
SHA-256: 7d1df4beb915701587cc09a007868c4b6147155b392174ed25a0a029a260d57d |
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