Malicious PDF — malware analysis report

Static analysis result for SHA-256 679b909135a8c74b…

MALICIOUS

PDF

1.3 KB
MD5: 904264ebeb440d13ec9d488d108885a7 SHA-1: 10df42b4fea731b5e59b81dd44071b1b90311889 SHA-256: 679b909135a8c74b80f85d4d41788ae24fdc298096e4ae608bb5dcd4df650430
176 Risk Score

Malware Insights

MITRE ATT&CK
T1059.007 JavaScript T1203 Exploitation for Client Execution

This PDF file contains embedded JavaScript, including an eval() call, which is indicative of an exploit attempt. The JavaScript is likely used to execute arbitrary code, potentially leading to further compromise. The ML classifier strongly suggests malicious intent.

Machine Learning

  • Nyx PDF Classifier malicious score 1.0000

Heuristics 7

  • PDF JavaScript exploit cluster critical PDF_JS_EXPLOIT_CLUSTER
    PDF combines an executable JavaScript/action surface with exploit staging indicators such as eval/unescape/fromCharCode, XFA script content, or a related CVE pattern. Benign form JavaScript remains low-severity, but this correlated cluster is high-confidence malicious behavior.
  • eval() call high PDF_EVAL
    eval() found — commonly used for obfuscated exploit execution
  • ASCIIHexDecode filter (with exploit indicators) medium PDF_FILTER_HEX
    Hex-encoding filter present alongside exploit delivery indicators — often used to hide payload or shellcode bytes
  • JavaScript action low PDF_JAVASCRIPT
    PDF contains a /JavaScript action. Generic JavaScript is common in benign forms; specific dangerous APIs are scored by separate rules.
  • Embedded JS stream low PDF_JS
    PDF references a /JS stream. Generic JavaScript is common in benign forms; specific dangerous APIs are scored by separate rules.
  • Embedded file low PDF_EMBEDDED
    PDF embeds a file attachment — could carry an executable or another weaponised document as a nested payload
  • 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.

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