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19/08/2026 4:08 pm
TL;DR: AI-related vulnerabilities are now showing up across prompts, data, supply chains, code generation, and agent permissions, with Cycode citing a 56.4% rise in publicly reported AI security incidents from 2023 to 2024 and 81% of organisations lacking visibility into AI use. The governance gap is no longer theoretical: enterprises need controls for identity, output handling, provenance, and delegated access before AI systems become routine attack paths.
NHIMG editorial — based on content published by Cycode: Top AI Security Vulnerabilities to Watch out for in 2026
By the numbers:
- Cycode says almost every organisation now confirms AI-generated code in its codebases, while 81% still lack visibility into how AI is actually used.
- According to Stanford's HAI AI Index Report, publicly reported AI security incidents increased by 56.4% from 2023 to 2024.
- Cycode highlights that 76% of organisations consider shadow AI a definite or probable challenge.
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 assistants create new access risks for IAM and PAM programmes?
A: AI assistants can combine multiple permissions into one response, which means a user may see sensitive context without directly opening the source asset.
Q: What breaks when AI coding tools are trusted without strong verification?
A: What breaks first is consistency.
Practitioner guidance
- Inventory AI principals and delegated access Build a register of copilots, agents, plugins, and embedded assistants, then map each one to the data, APIs, and tools it can touch.
- Separate instruction data from execution paths Enforce architectural boundaries between prompts, retrieved content, and action-bearing outputs.
- Limit tool access for every AI workflow Apply least privilege to AI systems, just as you would for service accounts or privileged users.
What's in the full article
Cycode's full analysis covers the operational detail this post intentionally leaves for the source:
- Step-by-step guidance on reducing prompt injection and output-handling risk across AI workflows
- The article's breakdown of each vulnerability category, including supply chain, poisoning, shadow AI, and model theft
- Cycode's operational examples for limiting tools, logging AI activity, and testing for behavioural drift
- The source's practical remediation patterns for teams implementing AI governance in production
👉 Read Cycode's analysis of the top AI security vulnerabilities for 2026 →
AI security vulnerabilities in 2026: where are controls breaking down?
Explore further
19/08/2026 4:41 pm
AI security is becoming an identity governance problem before it is a model-risk problem. The article repeatedly shows that the most serious failures occur when AI systems inherit access to data, tools, and workflows without lifecycle controls. That puts AI agents, copilots, and embedded assistants into the same governance conversation as service accounts and other non-human identities. Practitioners should treat delegated AI access as a principal that must be explicitly scoped, reviewed, and retired.
A few things that frame the scale:
- The average organisation believes more than 1 in 5 of their non-human identities are insufficiently secured, according to The 2024 ESG Report: Managing Non-Human Identities.
- 72% of organisations have experienced or suspect they have experienced a breach of non-human identities, with 46% confirming incidents and 26% suspecting them.
A question worth separating out:
Q: Who is accountable when shadow AI uses corporate credentials to process sensitive data?
A: Accountability sits with the identity owners, the platform owners, and the governance function that approved the underlying access. If a service account or OAuth app can reach regulated data and an AI feature uses that path, the organisation is responsible for the resulting exposure and audit trail.
👉 Read our full editorial: Top AI security vulnerabilities in 2026 are outpacing enterprise controls
