Flare Systems’ scoring system for technical disclosure identification has a 95% true positive rate on high-risk alerts
MONTRÉAL, Québec – March 31, 2021 – Flare Systems, a leading Digital Risk Protection provider, is pleased to announce the addition of technical data leak detection to its digital risk protection capabilities, reducing the risk of accidental data exposure.
Firework, Flare Systems’ flagship product, first detects technical data leaked online, then deploys proprietary techniques and algorithms to regroup and enrich the results. This capability enables prioritization of alerts, and supports remediation for most critical issues.
“Since malicious activity is not the driving factor behind human error, no known signature or pattern can be detected by most available tools, leading to an increase in an organization’s attack surface,” said Mathieu Lavoie, CEO and Co-founder at Flare Systems.
“The global pandemic has prompted employees to share and store information with new cloud services,” said Yohan Trépanier Montpetit, Head of Product and Co-founder at Flare Systems. “By adding technical data leak detection to their digital risk protection strategy, organizations can significantly reduce the risk of accidental data exposure.”
Based on the scoring system Flare Systems developed to identify technical information disclosures, a 95% true positive rate has been detected on high-risk alerts. By reducing the mean-time-to-detect (MTTD) and the mean-time-to-remediation (MTTR), the new capabilities enable organizations to improve their cyber resilience.
For more information visit https://flare.systems/solutions/detect-technical-leakage/
About Flare Systems
Flare Systems is a leading Digital Risk Protection provider based in Montreal, Canada. Founded in 2017, Flare Systems enables organizations to continuously monitor threats caused by human error and malicious actors to protect their data, financial resources, and reputation. Focused on technical data leakage detection, their technology improves visibility, transparency and reduces mean-time-to-remediation (MTTR) by detecting and prioritizing technical data leaks, and remediating digital risks in real-time.