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    FAQ: Is AI Application Security Testing Reliable If Results Vary Between Scans?

    FAQ: Is AI Application Security Testing Reliable If Results Vary Between Scans?

    Non-deterministic LLM vuln discovery is actually a strength for Xint since it can go beyond fixed rules or patterns that are easily gamed by attackers.
    Hector Leano's avatar
    May 28, 2026
    ProductAI for SecurityFAQ
    Xint’s False Positive Rate: Methodology and Purpose

    Xint’s False Positive Rate: Methodology and Purpose

    We don’t know the FP rate for the latest frontier models when it comes to AppSec. We share ours and how we arrived at it.
    Hector Leano's avatar
    May 18, 2026
    ProductAI for Security
    Why Zero Data Retention Should Be Non-Negotiable When Your Team Uses LLMs

    Why Zero Data Retention Should Be Non-Negotiable When Your Team Uses LLMs

    Zero data retention (ZDR) policies for LLMs in AppSec are not the default, but here's why they belong at the top of your AI procurement checklist.
    Hector Leano's avatar
    May 11, 2026
    Product
    What to Ask Every AI PenTest Vendor Before You Buy

    What to Ask Every AI PenTest Vendor Before You Buy

    These are the 8 questions that will tell you whether a vendor is selling a pen test alternative, a faster SAST tool, or a demo that doesn’t survive production
    Hector Leano's avatar
    May 06, 2026
    AI for SecurityProduct
    Vulnerabilities vs. Weaknesses: Why the Distinction Matters

    Vulnerabilities vs. Weaknesses: Why the Distinction Matters

    There's a difference between insecure code patterns and true vulnerabilities that hackers seek to exploit. Why does that matter?
    Hector Leano's avatar
    May 05, 2026
    Vulnerability ResearchAI for SecurityProduct
    FAQ: Is AI Application Security Testing Reliable If Results Vary Between Scans?

    FAQ: Is AI Application Security Testing Reliable If Results Vary Between Scans?

    Non-deterministic LLM vuln discovery is actually a strength for Xint since it can go beyond fixed rules or patterns that are easily gamed by attackers.
    Hector Leano's avatar
    May 28, 2026
    ProductAI for SecurityFAQ
    Xint’s False Positive Rate: Methodology and Purpose

    Xint’s False Positive Rate: Methodology and Purpose

    We don’t know the FP rate for the latest frontier models when it comes to AppSec. We share ours and how we arrived at it.
    Hector Leano's avatar
    May 18, 2026
    ProductAI for Security
    Why Zero Data Retention Should Be Non-Negotiable When Your Team Uses LLMs

    Why Zero Data Retention Should Be Non-Negotiable When Your Team Uses LLMs

    Zero data retention (ZDR) policies for LLMs in AppSec are not the default, but here's why they belong at the top of your AI procurement checklist.
    Hector Leano's avatar
    May 11, 2026
    Product
    What to Ask Every AI PenTest Vendor Before You Buy

    What to Ask Every AI PenTest Vendor Before You Buy

    These are the 8 questions that will tell you whether a vendor is selling a pen test alternative, a faster SAST tool, or a demo that doesn’t survive production
    Hector Leano's avatar
    May 06, 2026
    AI for SecurityProduct
    Vulnerabilities vs. Weaknesses: Why the Distinction Matters

    Vulnerabilities vs. Weaknesses: Why the Distinction Matters

    There's a difference between insecure code patterns and true vulnerabilities that hackers seek to exploit. Why does that matter?
    Hector Leano's avatar
    May 05, 2026
    Vulnerability ResearchAI for SecurityProduct
    Announcing Xint Code

    Announcing Xint Code

    Real Vulnerabilities. Actionable Results.
    Hector Leano's avatar
    Dec 15, 2025
    AI for SecurityProduct