MALICIOUS
106
Risk Score
Malware Insights
MITRE ATT&CK
T1204.002 Malicious File: Malicious File
The PDF file was flagged as malicious by a machine learning classifier with high confidence. Static analysis revealed embedded JavaScript, which is often used to exploit vulnerabilities or download further malicious payloads. The presence of PDF_JAVASCRIPT and PDF_JS heuristics, along with the critical PDF_CORRELATED_MALICIOUS_JS signal, strongly indicates that the embedded JavaScript is the primary mechanism for malicious activity.
Machine Learning
- Nyx PDF Classifier malicious score 0.9999
Heuristics 3
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Correlated malicious PDF JavaScript signals critical PDF_CORRELATED_MALICIOUS_JSPDF JavaScript or auto-action content is corroborated by exploit staging, ML, or suspicious extracted-artifact findings. This correlation promotes old exploit-kit PDFs that otherwise remain in the suspicious band because each individual signal is intentionally weighted conservatively.
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JavaScript action low PDF_JAVASCRIPTPDF contains a /JavaScript action. Generic JavaScript is common in benign forms; specific dangerous APIs are scored by separate rules.
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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.
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