AI
Socket CISO: Build AI Security Tools That Solve Current Pains, Not Future Hype
Andrew Becherer discusses the hidden operational burdens of AI-built security tools and how founders can earn trust from security leaders.
AI security
Everything TechSec Feed has reported about AI security: 9 stories, newest first. Part of our AI coverage.
AI
AI
Large Language Models vs Machine Learning: Core Differences Explained
Large language models are a narrow subset of machine learning that predict text tokens, whereas machine learning covers a broader range of predictive and classification tasks across all data types.
Tech News
GitHub's ModernBERT secret scanner cuts post-push time by 86% and lowers false positives
GitHub deployed a new model that reduces median post-push scan execution time by 86 percent and improves detection quality for generic secrets.
AI
Treating AI Models as Untrusted Insiders: A Security Framework
Treating AI models as untrusted insiders forces you to audit model behavior rather than just input data, revealing hidden exfiltration paths that traditional network security misses entirely.
AI
Trellix Deploys AI Security Operations Inside Customer Environments
Trellix Wise for Private Cloud lets enterprises run AI security agents on-premises, keeping data within their own security boundaries to address governance concerns.
AI
Trump Rules: AI Makers Must Alert US Officials and Patch Security Flaws Without Delay
Federal officials require AI developers to notify authorities and remediate model security flaws immediately after detection.
Vulnerabilities
Astron Agent Patch Fixes Critical Root Privilege Escalation for Tenants
A critical vulnerability in Astron Agent versions prior to 1.1.2 allowed authenticated low-privilege users to execute code as root, compromising tenant isolation and shared services.
AI
Retrieval-Augmented Generation Security for Small Teams
Most retrieval-augmented generation failures stem from weak source controls rather than model vulnerabilities, shifting the security burden to data governance.
AI
AI Hallucination Incident Response and Recovery Steps
The primary risk from an AI hallucination is not the error itself, but the automated action it triggers without human verification or logical bounds checking.