Inside the Minds of Growth Cybersecurity CEO & Founders

• •connecting with and supporting industry friends and colleagues
• •regression testing and code coverage validation
• •proactive remediation and risk elimination before breaches occur
• •detecting attacker access through honey token deployment at scale
• •focusing on data security in the enterprise

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• •traditional signature-based detection cannot protect against zero-day exploits
• •not having a security program
• •customers want exhaustive lists but act paralyzed by false alarm volume
• •bots graduating attacks in wave patterns
• •info-stealers have been a cumulative, long-standing problem

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• •block 99% of vulnerabilities from being exploited
• •exact asset identification when honey token is triggered (repo, file, line)
• •device posture assessment - security drift evaluated every 60 secondsNew
• •false positive rate and alert accuracy
• •graduation from college matching commitment to mother

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• •risk-based prioritization - remediate highest-value data at risk first based on calculated monetary impact
• •exploitable attack surface & threat actor pressure: drives 'what to do and what not to do'
• •solve large sets of problems holistically - connecting related security problems to build comprehensive platforms
• •cooperative monitoring model — sock handles log ingestion/monitoring; appsec provides application context to validate alerts
• •commitment-driven execution - telling mother/others your goal, then structuring all decisions to achieve it ('tell mom i was going to graduate in four years')

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• •applying non-deterministic ai to problems requiring deterministic solutionsNew
• •requests to 'train' or 'educate' boards in foundational technical concepts
• •leaving exceptions un-revisited and expiring
• •high false positive rates presented as normal/acceptable
• •organizations relying on outdated deepfake detection methodsNew

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