Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Artificial intelligence has only been available for a relatively short period. Still, already many cyber defenders are as frightened as if Jenna Ortega’s Wednesday Addams had whipped her head around and set her dark, dangerous eyes on them. It’s not hard to see why. Machine learning, Gen AI, and Retrieval-Augmented Generation (RAG) are a few of more than 20 new acronyms flooding our industry, with more being added almost every day.

Static application security testing (SAST) is foundational to modern application and code security programs. Yet these tools inevitably produce false positives that require manual review. When scanners find vulnerabilities that are not genuine issues, they erode trust, slow down remediation, and make it harder for teams to understand which alerts require attention.

TLDR: Excessive Data Exposure (leaking internal data via API responses) is the silent, pervasive threat that is more dangerous than single dramatic flaws like SQL Injection. It amplifies every other API vulnerability (like BOLA) and happens everywhere because developers prioritize speed over explicit data filtering. Fixing it means systematically checking hundreds of endpoints for unneeded PII and sensitive internal data.

At the AI Agent Security Summit in San Francisco, some of the brightest minds in AI security and top industry leaders gathered to tackle one of the most challenging problems in tech nowadays - how do we secure super smart systems that change at runtime and are designed to think, adapt, and compete? As someone who spends every day turning AI security challenges into tangible solutions, I left the summit both inspired by the innovation on display and concerned by the magnitude of what’s still ahead.

Unlike closed-source code or proprietary applications, open source software (OSS) exposes its source code, allowing anyone to view, modify, or contribute to it. This transparency delivers both opportunities and unique threats; developer communities can uncover flaws faster, but attackers can also examine code for weaknesses and even easily leverage known reported open source vulnerabilities.

AI is rewriting the rules of privileged access, but the rise of AI agents is creating a governance crisis. Threats like credential stuffing and privilege escalation are now accelerated by autonomous systems moving faster than humans can react. 82% of companies deploy autonomous AI agents, but 23% of IT teams admit those bots have already been tricked into revealing credentials—and fewer than half have guardrails in place. In modern infrastructure, machine identities now outnumber humans 80:1.