AI is the biggest shift in security since the cloud — stay ahead
AI-powered threats, AI-assisted defense, LLM vulnerabilities, deepfake attacks. Get a brief that covers both sides of AI in security.
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Attackers are using AI too
AI-generated phishing, deepfake social engineering, automated vulnerability discovery — the threat landscape is evolving with AI. You need to track offensive AI capabilities.
Every security vendor added AI
CrowdStrike, Palo Alto, Fortinet — every vendor has AI features. Separating real detection improvement from marketing is critical.
LLM and AI systems are new attack surfaces
Prompt injection, data exfiltration, model poisoning — securing AI systems requires new knowledge and new tools.
AI news through the Cybersecurity lens
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We cover AI through a cybersecurity lens — threats, defenses, vulnerabilities, and compliance.
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AI-powered attack techniques, vulnerability disclosures in AI systems, and emerging threat patterns.
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Honest assessments of AI security tools — detection rates, false positive impact, and integration complexity.
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News Relevant to You
OpenAI Releases Security Advisories for ChatGPT Enterprise After Prompt Injection Vulnerabilities Discovered
Security researchers identified multiple prompt injection attack vectors in ChatGPT Enterprise deployments that could allow unauthorized data exfiltration. OpenAI has released patches and updated their security guidelines for enterprise customers.
Why this matters to you: Understanding how adversarial attacks exploit LLM systems is critical as you evaluate AI-powered security vendors integrating language models into their threat detection platforms.
CrowdStrike Falcon Updates Detection Engine with New AI Behavioral Analysis Module
CrowdStrike announced enhancements to its threat detection capabilities using improved machine learning models for zero-day malware identification. The update includes real-time behavioral correlation across cloud and on-premises environments.
Why this matters to you: This security vendor evaluation showcases how modern AI threat detection is evolving—comparing detection accuracy improvements will help you assess whether similar upgrades in your current tooling provide real security value.
What To Test This Week
Run a Red Team Exercise Against Your Current AI-Powered Detection System
Simulate adversarial attacks and prompt injection attempts against your existing AI threat detection tools to identify blind spots. Document which attack patterns your system flags versus misses, and categorize findings by attack sophistication level.
Why this matters to you: Testing your defenses against adversarial attacks ensures your AI threat detection isn't vulnerable to the same evasion techniques attackers are actively developing against security vendors.
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Topics we watch for you include
- 🔍AI-powered threat techniques and advisories
- 🔍Security vendor AI feature evaluations
- 🔍LLM and AI system vulnerability disclosures
- 🔍AI compliance and governance frameworks
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