MALICIOUS
102
Risk Score
Malware Insights
MITRE ATT&CK
T1059.001 JavaScript/JScript
T1553.004 Subversion: Mark-of-the-Web Bypass
The PDF sample was flagged by a machine learning classifier and heuristics indicate the presence of JavaScript, which is used to hide malicious content. The 'PDF_ENCRYPTED_WITH_JS' heuristic suggests that the payload is intentionally obscured from static analysis, likely for evasion. The ML classifier's high score further supports the malicious nature of the file. No specific IOCs were extracted due to the obfuscation.
Machine Learning
- Nyx PDF Classifier malicious score 0.9252
Heuristics 5
-
Encrypted PDF carries /Js — payload hidden from static analysis high PDF_ENCRYPTED_WITH_JSPDF declares /Encrypt and also references an executable trigger (/Js). Document encryption hides the JavaScript body and stream contents from static scanners — combined with auto-execution indicators this is a known evasion pattern used to deliver weaponised JavaScript that the analyst cannot inspect without the decryption key.
-
JavaScript action low PDF_JAVASCRIPTPDF contains a /JavaScript action. Generic JavaScript is common in benign forms; specific dangerous APIs are scored by separate rules.
-
Embedded JS stream low PDF_JSPDF references a /JS stream. Generic JavaScript is common in benign forms; specific dangerous APIs are scored by separate rules.
-
Embedded file low PDF_EMBEDDEDPDF embeds a file attachment — could carry an executable or another weaponised document as a nested payload
-
XFA form low PDF_XFAPDF uses XML Forms Architecture — can contain script logic
Open this report in the interactive analyzer, or submit your own file for analysis.