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Apr 13, 2026 · Updated 11:37 AM UTC
Cybersecurity

BleepingComputer to Host Cyber Threat Intelligence Webinar on Identifying Early Warning Signs of Attacks

BleepingComputer is set to host a webinar on April 30, focusing on how to extract actionable threat intelligence from the noise of the dark web and Telegram channels.

Ryan Torres

1 min read

BleepingComputer to Host Cyber Threat Intelligence Webinar on Identifying Early Warning Signs of Attacks
Photo: bleepingcomputer.com

BleepingComputer will host a live webinar titled "From Noise to Signal: The Threat Actor's Next Target" on April 30, 2026, at 2:00 PM ET. Featuring RansomLook threat intelligence researcher Tammy Harper, the session will explore how security teams can monitor early warning signs within underground communities and translate them into defensive action.

Cyberattacks rarely occur without warning. Before launching an intrusion, threat actors often leave traces across dark web forums, Telegram channels, and access broker markets. These channels are frequently used to coordinate attacks, share vulnerabilities, or sell stolen credentials—sometimes exposing malicious intent weeks before an actual strike occurs.

Identifying Early Signs of Attackers

The webinar will focus on how to identify patterns within fragmented and cluttered data. Security teams face the significant challenge of distinguishing genuine threat signals from the massive volume of background noise in which attacker communications are often buried.

Flare Systems, an intelligence firm specializing in external threat surface monitoring, will share techniques for detecting early signals by monitoring the dark web and hidden channels. By leveraging visualized data on attacker behavior, organizations can shift from a reactive defense posture to proactive risk mitigation.

Attendees will learn how to extract meaningful signals from the digital "noise," track evolving adversary tactics, and transform intelligence into prioritized defensive measures before attackers can establish a foothold.

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