PulseAugur
EN
LIVE 19:52:44

OWASP releases Top 10 threat list for agentic AI applications

The OWASP Agentic Security Project has released the OWASP Top 10 for Agentic Applications (2026), a new threat model for systems utilizing autonomous agents and LLMs. This list, developed by over 100 contributors, provides a shared vocabulary for understanding and mitigating risks specific to agentic workflows. It details ten categories of potential failures, ranging from agent goal hijacking and tool misuse to memory poisoning and unexpected code execution, offering practitioners a framework for threat modeling. AI

IMPACT Provides a standardized framework for identifying and mitigating security risks in autonomous AI agent systems.

RANK_REASON Publication of a new threat model by a recognized security organization. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

OWASP releases Top 10 threat list for agentic AI applications

How we ranked this

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
Publication of a new threat model by a recognized security organization. [lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
safety, policy
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
74 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Brenn Hill ·

    The OWASP Agentic Top 10, explained for practitioners

    <p>If you are shipping anything with autonomous agents — tool-calling LLMs, multi-agent workflows, agents that read memory and act on it — you have probably noticed that the usual web and API threat models do not quite fit. The risks shift when the thing making decisions is a mod…