AIDR, AI detection and response, is the practice of monitoring AI applications and agents for misuse, manipulation and abnormal behaviour, and responding when something is wrong. It borrows the idea of endpoint detection and response and applies it to prompts, model outputs, tool calls and the identities agents use.
Is AIDR an established category?
Not yet. The term is recent, and products use it for different things. No standards body has published a definition we could confirm, so read vendor claims with care and ask what each product records and which risks it covers.
What does exist are public catalogues of AI risks. MITRE ATLAS catalogues adversary tactics against AI systems. OWASP publishes a Top 10 for LLM applications and a Top 10 for Agentic Applications, and NIST publishes an AI Risk Management Framework. These are a sound way to judge what a tool should watch.
What does it watch?
Four kinds of signal, in rough order of maturity.
- Inputs. What goes into a model: user prompts, retrieved documents, tool results. The aim is to spot instructions hidden in content, or sensitive data going where it should not.
- Outputs. What comes back: secrets or personal data in answers, content that breaks policy, answers the application then acts on without checking.
- Actions. What an agent does: which tools it calls, with what arguments, how often, and against which systems.
- Identity and access. Which credentials the agent uses and how broad they are.
Actions and access are where harm usually happens. OWASP's guidance on Excessive Agency says damaging actions come from excessive functionality, excessive permissions or excessive autonomy, whatever triggers the model's behaviour.
What does "response" mean?
Response actions range from gentle to strong: add a warning, route output to a human, block a tool call, pause an agent, revoke a credential. Each has costs. Blocking in line can add delay and, if wrong, breaks a feature. Strong actions need rules about who can use them.
Good practice is to start in observe mode, then recommend, then act on low risk cases, and keep a human approver for anything that changes customer outcomes.
How is it different from other tools?
From a content filter. A filter checks single messages against rules. AIDR looks at sequences, context and actions over time.
From application security testing. Testing finds weaknesses before release. AIDR watches behaviour after release. You need both.
From EDR. EDR watches devices. AIDR watches AI systems, which may run in cloud services where no agent can be installed.
From identity management. Identity decides who or what may do things. AIDR watches what actually happens and flags the unusual.
What can it not do?
It cannot make a poorly designed system safe. If an agent holds broad permissions and acts without approval, detection only tells you faster that something went wrong. Reducing permissions and autonomy comes first. It also cannot see systems you have not listed, so inventory comes before monitoring.
It will produce false positives. Language is variable and normal use looks strange sometimes. Tuning is a standing task.
What about privacy?
Logging prompts and outputs may capture personal or confidential data. Decide retention, access and masking before you switch it on, and check the rules of any jurisdiction you operate in.
How do you judge a product?
Ask five questions.
- Which named risks does it detect, and how was that tested?
- What does it log, for how long, and who can read it?
- Can it explain each alert from its own evidence?
- Which response actions exist, and can they be undone?
- Can I run a trial on my own traffic?
What to do
- Inventory every AI system and agent, with an owner each.
- Reduce permissions and autonomy before adding detection.
- Pick five risks from the public catalogues that fit your systems.
- Decide logging, masking and retention rules.
- Start with observe mode and add response actions step by step.
- Trial any product on your own traffic with constructed scenarios.
Safeguard focuses on the application and software supply chain side, including MCP Guardrail for MCP servers, and does not replace a dedicated AI detection tool.
Quick check
Is AIDR the same as an AI firewall?
No. A firewall mostly checks traffic at a boundary. AIDR includes watching sequences, actions and access over time, and supports investigation and response. Some products combine both.
Do we need AIDR if we only use a chat tool?
Probably not a dedicated product at first. Start with an inventory, usage policy and logging. Add detection as you connect AI to tools and data.
Sources
- MITRE ATLAS
- OWASP LLM Top 10, Excessive Agency
- OWASP Top 10 for Agentic Applications for 2026
- NIST AI Risk Management Framework
Last reviewed: 18 October 2026.
