AI, Data & Intelligence
Prompt Injection Risk Assessment
A focused assessment of how exposed your RAG applications, copilots and AI agents are to direct and indirect prompt injection, and what an attacker could achieve through it.
Capability overview
What prompt injection risk assessment involves
Prompt injection is the most characteristic vulnerability of language model applications. Direct injection comes from a user typing instructions to override the system. Indirect injection is more dangerous: hidden instructions sit inside a document, email, web page or database record that the application later reads on someone else's behalf.
This assessment traces every place untrusted text can enter the model's context and every action or data the model can reach, then tests the combinations. The result is a clear picture of realistic impact, for example whether a malicious email could make an assistant forward confidential files, and specific design changes to contain it.
What is included
Assessment coverage
Input source mapping
User messages, uploaded files, retrieved documents, web content, emails, tickets and tool results catalogued as injection entry points.
Capability mapping
Data the model can read and actions it can trigger, such as sending messages, calling APIs or rendering links and images.
Indirect injection tests
Crafted payloads planted in documents and records to see whether the application follows them when processing legitimate requests.
Exfiltration channels
Checks for data leaking through generated links, markdown images, tool parameters or outbound requests.
Containment recommendations
Design changes such as removing unnecessary tools, human confirmation and output restrictions ranked by risk reduction.
How we work
How we deliver prompt injection risk assessment
Flow analysis
Application architecture reviewed to connect untrusted inputs with sensitive data and actions.
Payload development
Injection payloads tailored to the application's prompts, formats and languages.
Controlled testing
Tests run in a non-production environment with test data and monitored tool endpoints.
Impact rating
Successful injections rated by what they achieve, from harmless text changes to data theft.
Fix validation
Payloads rerun after changes to confirm containment and handed over as regression tests.
Related capabilities
Related capabilities in Responsible AI & AI Security
AI Privacy & Data Protection
Privacy by design for AI systems: lawful data use for training and inference, DPDP Act and GDPR obligations, data minimisation, retention, vendor terms and handling of individuals' rights when AI is involved.
Bias & Fairness Assessment
Measurement of whether an AI system produces unequal outcomes or error rates for different groups of people, with statistical analysis, root cause investigation and practical mitigation options.
Model Explainability
Techniques and interfaces that show why an AI model produced a particular prediction or decision, for data scientists debugging models, staff reviewing cases, regulators and the customers affected.
AI Model Monitoring
Continuous monitoring of production AI models for data drift, accuracy decay, fairness shifts, unusual outputs and operational health, with thresholds that trigger review, retraining or rollback.
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Questions & answers
Questions about Prompt Injection Risk Assessment
Cannot find what you need? Our team responds to technical and commercial questions within one business day.
Ask a questionApplications that read content from outside the organisation and can also take actions or access sensitive data, such as email assistants, browsing agents and support copilots with CRM access.
Red teaming covers a broad range of harms including offensive content and bias. This assessment goes deep on one attack class, tracing data and action paths to measure injection impact precisely.
Filters catch some known patterns but are easy to evade. Limiting the model's permissions and requiring confirmation for sensitive actions provide more dependable protection.
Typically one to two weeks for a single application, depending on the number of input sources and tools involved.
Next step
Discuss prompt injection risk assessment with Acmez
Share what you need to change, build, integrate or support. We will map the practical next step.