After months of organizations deploying AI agents without proper security frameworks, OWASP released its first-ever “Top 10 for Agentic Applications” for 2026.
Security experts discovered that during their investigation, many organizations already have agentic solutions deployed without IT and security teams even knowing about it. These aren’t simple chatbots anymore—these AI agents access data and tools and carry out tasks, making them infinitely more capable and dangerous to enterprises.
Security stakes are orders of magnitude higher than previous technologies, with compromised agents capable of manipulating financial markets or sabotaging infrastructure.
This framework emerged from input by over 100 security researchers and was evaluated by experts from NIST, the European Commission, and the Alan Turing Institute. Unlike theoretical academic risks, this list is built from real incidents, not theory.
Why traditional security became obsolete
Here’s the fundamental problem: agentic architectures operate on probabilistic reasoning, untrusted inputs in ways traditional security models never anticipated. These systems plan, execute, use tools, and make decisions with minimal human oversight, creating an entirely new attack surface where intent can be hijacked through natural language alone.
Documented incidents over the past year reveal the scope of vulnerability: copilots have been turned into silent data exfiltration engines, agents have bent legitimate tools into destructive outputs, and systems have collapsed because one agent’s false belief cascaded through entire workflows.
Here’s a summary of the list from OWASP:
- ASI01 – Agent Goal Hijack: Malicious content alters an agent’s objectives or decision path, causing unintended actions.
- ASI02 – Tool Misuse and Exploitation: Agents misuse legitimate tools due to ambiguous prompts, over-privilege, or poisoned inputs.
- ASI03 – Identity and Privilege Abuse: Agents unintentionally reuse, escalate, or leak inherited credentials or access.
- ASI04 – Agentic Supply Chain Vulnerabilities: Compromised tools, prompts, plugins, or agents alter behavior or expose data.
- ASI05 – Unexpected Code Execution: Agents generate or execute unsafe code or commands without proper isolation or review.
- ASI06 – Memory and Context Poisoning: Poisoned memory, RAG, or embeddings influence future agent behavior.
- ASI07 – Insecure Inter-Agent Communication: Unauthenticated or unprotected agent messages allow spoofing or injection.
- ASI08 – Cascading Failures: Errors in one agent propagate across interconnected agent workflows.
- ASI09 – Human-Agent Trust Exploitation: Over-trust in agents is leveraged to manipulate users or extract sensitive data.
- ASI10 – Rogue Agents: Compromised or misaligned agents act maliciously while appearing legitimate.
Each represents a fundamentally different threat model than traditional software security. Agents connect to APIs, execute code, move data, and make decisions with real permissions in live production environments—making every vulnerability a potential business catastrophe.
Agents running wild
Most alarming is what security experts uncovered during their research: agentic AI is being adopted fast by enterprises, but security implementation is lagging significantly. This level of risk is unprecedented, according to OWASP GenAI security project board co-chair Scott Clinton.
Current deployment patterns are particularly dangerous: agents now summarize thousands of documents, operate critical workflows, execute code on demand, and make API calls often without human oversight. Many inherit human or system credentials, creating attribution gaps that attackers can exploit to escalate rights and bypass authorization controls.
OWASP’s framework addresses this by introducing the principle of “least agency”—only granting agents the minimum autonomy required to perform safe, bounded tasks. But implementation requires understanding how risks can lead to chain reactions, such as goal hijack leading to tool misuse, then cascading failures, culminating in human over-trust.
What security teams must do right now
OWASP’s framework provides more than risk identification—it offers practical mitigation strategies including operational constraints, strict input validation, least privilege enforcement, and human oversight requirements. Organizations should start with threat modeling using the Top 10 before deploying any agentic AI systems.
This framework helps security leaders get agentic AI use cases from business teams and align top risks to fit specific scenarios. It provides a common language around agentic AI and its risks, helping bridge the gap between technical security teams and business stakeholders.
Most critically, organizations need to unify visibility across agents, tools, datasets, models, and identities to establish a defensible baseline. This includes maintaining inventories enriched with behavior patterns, permissions mapping, and data access tracking to identify misconfigurations and risky workflows before they become security incidents.
Future perfect? Microsoft has revealed a focus on AI agents, Copilot expansion, Microsoft 365 updates, and global infrastructure investment in 2026.
