PDF files have become a major cybersecurity threat vector, as attackers exploit their widespread use and complex structure to deliver malware through deceptive social engineering techniques.
Many users and organizations continue to trust PDFs as safe communication tools, making them an attractive delivery method for malicious content. In fact, recent data from Check Point Research shows that 68 percent of malicious attacks were delivered through email, and 22 percent of those included PDF attachments.
The structure of a PDF allows attackers to hide malicious links, scripts, or harmful content without being easily detected. These files are often used in phishing campaigns and more advanced, multi-stage attack chains that may eventually deploy ransomware or remote access tools like Remcos. In one recent attack, a PDF used blurred content and a fake download button to lure the user. Clicking it triggered a download of a compressed file containing a VBScript dropper, which eventually installed the Remcos RAT.
How to Block PDF-Based Attacks
AI-Powered Protection (e.g., PDFguard by Check Point)
PDFguard uses multi-layered AI analysis, including:
NLP Detection: Identifies suspicious language/social engineering.
Structural Analysis: Examines PDF internals for hidden scripts or payloads.
Cross-domain Detection: Flags malicious URLs and QR codes.
Dynamic Sandbox: Runs the PDF safely to watch for live malicious behavior.
Best Practices for Users and IT Teams
Email Security Gateways: Use advanced threat emulation and content disarm and reconstruction (CDR) tools.
Zero Trust Policy: Treat all file attachments as untrusted until scanned.
User Awareness Training: Educate users to avoid clicking unknown download buttons or blurred documents.
Block Macros and Scripts: Disable script execution within PDF readers.
Endpoint Protection: Deploy EDR/XDR tools for real-time response.
Patch PDF Readers: Ensure Adobe Reader and similar tools are always updated.
To address this growing threat, Check Point has introduced PDFguard, an AI-powered engine that enhances protection against malicious PDF files. PDFguard combines several advanced techniques: it uses natural language processing to detect social engineering attempts, inspects internal PDF structure for hidden threats, evaluates embedded links and QR codes, and runs files in a sandbox to monitor for suspicious real-time behaviors. These multiple detection layers enable PDFguard to identify 25 percent more malicious files than previous systems, including many new and previously unseen threats.
One of the key strengths of PDFguard lies in its dynamic threat analysis, which successfully blocked the aforementioned Remcos attack by detecting behavioral anomalies and suspicious external redirections. The system flagged visual deception tactics, misuse of branding, and identified command-and-control domains through its AI-powered threat intelligence platform.
Each intercepted file is supported by a detailed threat emulation report, offering forensic insights such as the MITRE ATT&CK tactics used, visuals of the attack process, and a timeline of events. This transparency helps security teams understand and respond to threats more effectively.
As PDF-based attacks continue to evolve, adopting solutions like PDFguard becomes critical for organizations aiming to strengthen their cybersecurity posture. Businesses using Check Point’s Quantum and Harmony products with Threat Emulation enabled are already protected against these types of campaigns. By leveraging AI to stay ahead of sophisticated attack methods, PDFguard provides a crucial layer of defense in the ongoing battle against cyber threats.
Rajani Baburajan
