SlashNext Launches Advanced URL Analysis Tool to Expose Hidden Threats in Real Time

New capability performs live, in-depth scanning and analysis of unknown URLs, tracking requests and following redirection to track the original link to its final destination

SlashNext, the leader in next-gen AI cloud email and communications security, launched a new advanced URL analysis feature that performs live, in-depth scanning of unknown URLs to combat the increasingly complex threat landscape where malicious pages only exist for hours. Developed specifically for complex attacks executed by cybercriminals who have learned to abuse trusted cloud application infrastructure, SlashNext’s URL analysis tool leverages AI to redefine email security, ensuring efficiency, accuracy, and continuous innovation. This feature enhances the arsenal of tools SlashNext customers already have at their disposal, so businesses can strengthen their threat posture without compromising speed.

To combat against the layered nature of cyberattacks, SlashNext has added an extra layer of AI-driven analysis, leveraging computer vision and natural language processing to recognize malicious content that may otherwise be overlooked. SlashNext’s AI capabilities automatically interpret each page along the redirection chain, identifying suspicious logos, hidden text, or unusual language patterns before a user even realizes they’ve been sent somewhere dangerous.

Marketing Technology News: MarTech Interview with Krish Mantripragada, Chief Product Officer @ Seismic

While many programs exist to identify malicious links, most security solutions do not have the technology to provide additional context or other valuable data. Many of these tools rely solely on third-party sources, assuming this data is both accurate and current. SlashNext follows zero trust principles with an advanced URL analysis tool that dives deeper to identify where a URL goes, how it redirects, and what lies behind the link. In the process, it gathers a wealth of information that paints a complete picture of the potential threat, showing:

• Every web request made along the journey: From the original URL to every redirection, including details like the method, status, and content type.
• Certificate details: It checks who issued the security certificate, when it’s valid, and other important metadata.
• Visual snapshots: Screenshots capture what the page looks like at key moments, especially when the content appears suspicious.
• Redirect chain: Every hop from the initial link to the final landing page, along with HTTP methods and status codes.
• Obfuscation detection: The tool can identify nested links, QR codes, and other attempts to hide malicious content.

“SlashNext’s URL analysis tool cuts through any confusion caused by relying on third-party sources to determine URL safety, by revealing the entire sequence of events,” said Patrick Harr, CEO, SlashNext. “This level of detail doesn’t just help you stop a single attack—it helps you understand the methods attackers use so you can train your team and refine your defenses against future threats.”

Marketing Technology News: Why Responsible AI Principles Matter for Advertisers

By combining AI-powered computer vision with advanced natural language processing (NLP), SlashNext’s URL analysis tool can identify subtle red flags like brand impersonations or misleading text that slip past traditional scanning. After compiling and analyzing this information, SlashNext reveals exactly how the URL portion of the attack was constructed, step by step. This detailed report is invaluable for security teams, as it provides them with all the clues needed to understand the attack and to take appropriate measures to block it.

Following the entire journey, SlashNext’s URL analysis tool can spot malicious behavior in real time, even if the link changes or the final site is only temporarily operational. SlashNext’s system also uses computer vision and NLP to read the page the same way a person would—scanning for dangerous text, suspicious forms, and other indicators of a scam.