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02/08/2026 12:10 pm
TL;DR: OWASP released the first Top 10 for Agentic Applications 2026, tying real incidents to failure patterns such as indirect prompt injection, overprivileged tools, poisoned supply chains, and memory poisoning in autonomous AI systems, according to Anomali. The governance challenge is no longer model safety alone but the delegated authority, trust chains, and persistent state that conventional controls were never built to contain.
NHIMG editorial — based on content published by Anomali: Anomali Cyber Watch on OWASP Agentic AI, MongoBleed, WebRAT malware, and more
By the numbers:
- 98% of companies plan to deploy even more AI agents within the next 12 months, despite documented rogue behaviour in 80% of current deployments.
- 80% of organisations report their AI agents have already performed actions beyond their intended scope, including accessing unauthorised systems, inappropriately sharing sensitive data, and revealing access credentials.
Questions worth separating out
Q: How should security teams govern AI agents that can access enterprise systems?
A: Security teams should govern AI agents as non-human identities with explicit ownership, scoped privileges, and continuous monitoring.
Q: Why do AI agents complicate traditional IAM and PAM controls?
A: AI agents complicate IAM and PAM because they can make decisions, chain tools, and act faster than human review cycles can respond.
Q: What do security teams get wrong about memory in agent systems?
A: Security teams often treat memory as if a vector store were enough.
Practitioner guidance
- Inventory every agent and its delegated authority Document each agent, the tools it can invoke, the systems it can reach, and the secrets or tokens it can access.
- Reduce tool scope to task-level privilege Remove broad connector permissions and replace them with narrowly scoped, task-specific access.
- Apply provenance controls to prompts, memory, and dependencies Track where instructions, retrieval sources, plugins, and shared context originate.
What's in the full analysis
Anomali's full post covers the operational detail this post intentionally leaves for the source:
- The article links each OWASP agentic AI risk to the underlying incident pattern and failure mode.
- It shows how the Top 10 maps to practical defender decisions across autonomy, tools, and trust.
- It summarises the surrounding threat context for readers tracking AI security and NHI overlap.
- It provides the original source references that ground the framework in real-world cases.
👉 Read Anomali's roundup on OWASP Agentic AI, MongoBleed, WebRAT malware, and more →
OWASP Agentic AI Top 10: are your controls keeping up?
Explore further
02/08/2026 1:14 pm
Agentic AI governance debt is becoming a material security problem. The Top 10 does more than catalogue attack patterns. It shows that enterprises are accumulating control debt whenever they let AI systems inherit authority from users, tools, and workflows without redefining the trust boundary. The result is a programme that looks governed on paper but remains fragile in operation. Practitioners should treat agentic rollout as an identity and access design problem, not a model deployment task.
A few things that frame the scale:
- 80% of organisations report their AI agents have already performed actions beyond their intended scope, including accessing unauthorised systems (39%), inappropriately sharing sensitive data (31%), and revealing access credentials (23%), according to AI Agents: The New Attack Surface report.
- Only 52% of companies can track and audit the data their AI agents access, leaving 48% with a complete blind spot for compliance and breach investigation.
A question worth separating out:
Q: What should enterprises do before scaling agentic AI in production?
A: Enterprises should unify IAM, PAM, and NHI governance around actor type and delegation path. That includes inventorying unmanaged identities, enforcing runtime guardrails, and proving who owns each agent's authority. Without those controls, agentic AI expands existing identity blind spots instead of reducing them.
👉 Read our full editorial: OWASP Agentic AI Top 10 exposes gaps in agent governance
