Topic starter
02/08/2026 12:26 pm
TL;DR: AI Security Posture Management is positioned as a continuous control layer for AI systems because traditional CSPM and DSPM do not cover prompt injection, shadow AI, runtime misuse, or model-specific governance gaps, according to Akto. The practical takeaway is that AI security now depends on discovering AI assets, constraining tool access, and monitoring behaviour as a governance problem, not just a deployment problem.
Editorial analysis by NHI Mgmt Group, based on content published by Akto: “AI Security Posture Management (AI-SPM): Complete Guide to AI Agent Security in 2026”.
Key questions
Q: How should security teams handle prompt injection in AI systems?
A: Treat prompt injection as an authorisation problem, not only a content problem.
Q: Why do agentic AI systems complicate existing IAM and PAM controls?
A: They complicate them because IAM and PAM were built around stable identities, human-paced approvals, and entitlements that are reviewed after use.
Q: What are the signs that shadow AI is becoming a governance problem rather than a productivity aid?
A: The clearest signs are widespread use outside IT visibility, repeated sharing of corporate data with GenAI tools, and no consistent approval path for new applications.
Practitioner guidance
- Inventory all AI assets and delegated connections Build and maintain an AI-BOM that covers models, agents, MCP servers, plugins, SaaS tools, datasets, and the business owners responsible for each one.
- Constrain tool access to task-scoped permissions Limit each agent to the smallest set of APIs, databases, and actions needed for its use case, and revoke access when the task or session ends.
- Deploy runtime guardrails for prompts and outputs Filter malicious input, block unsafe outputs, and deny high-risk actions when the agent's behaviour diverges from approved policy.
Bottom line: AI-SPM is emerging because traditional cloud and data posture controls do not address the live behaviour of agentic systems, including prompt manipulation, tool misuse, and shadow deployments.
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02/08/2026 1:25 pm
AI-SPM is becoming a governance layer, not a point product category. The article is right to treat AI security posture as continuous rather than episodic, because agentic systems change behaviour after deployment. That makes discovery, policy, and monitoring part of one operating model. For security leaders, the practical conclusion is that AI governance cannot stop at approval workflows or cloud posture reviews.
A few things that frame the scale:
- 69% of security leaders agree identity management must fundamentally shift to address agentic AI systems, according to the 2026 Infrastructure Identity Survey.
- Gartner predicts that more than 40% of agentic AI projects will be cancelled by the end of 2027, citing rising costs, unclear value and insufficient risk controls.
A question worth separating out:
Q: Should organisations use AI-SPM instead of CSPM and DSPM for AI security?
A: No. CSPM and DSPM still matter, but they do not cover AI behaviour, delegated tool use, or prompt-driven abuse. Organisations should use AI-SPM alongside them so infrastructure, data, and runtime AI controls are governed together rather than in separate silos.
👉 Read our full editorial: AI-SPM is becoming a baseline control for agentic AI security