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An AI agent may be tricked when hostile instructions are hidden in an email, webpage, document, search result, or tool response that it is asked to process. The danger is not merely an incorrect answer: a manipulated agent can request secrets, forward information, send messages, alter records, or use connected tools on an attacker’s behalf. Look for an unexplained change in scope, sensitive requests, or unapproved tool activity; then contain the agent with trust boundaries, least-privilege access, human approval gates, protected memory, and detailed action logs. No prompt or model setting can guarantee prevention.
What social engineering means for an AI agent
Social engineering normally targets a person’s judgment. With an AI agent, the attacker instead places persuasive instructions where the agent will read them, hoping the model will treat those instructions as higher-priority directions. The agent can then become an intermediary between the attacker and a person, database, mailbox, application, or other connected system.
OWASP defines the underlying vulnerability this way: “Prompt Injection Vulnerability occurs when an attacker manipulates a large language model (LLM) through crafted inputs, causing the LLM to unknowingly execute the attacker’s intentions.” The phrase prompt injection covers both obvious attacks in a user’s request and hidden attacks embedded in material the agent retrieves or parses.
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Direct prompt injection
A direct injection is placed in the user’s message or another input deliberately supplied to the agent. The text may tell the agent to ignore its assigned task, reveal confidential context, or call a tool. A malicious user might ask a customer-service agent to export another customer’s records, or might try to persuade a coding agent to run an unrelated command.
Indirect prompt injection
An indirect injection is hidden in content the agent is instructed to read. Common locations include an incoming email, a shared document, a web page, a support ticket, a calendar description, an API response, a search result, or output from another tool. The instructions do not have to be visible or readable to a human to influence the model’s behavior. Formatting, hidden text, encoded content, or an otherwise ordinary paragraph can be enough for the model to encounter the attacker’s instructions.
Because an indirect injection arrives through a normal workflow, a user may believe the agent is simply summarizing a document while the agent is actually following directions inside that document. That is why treating retrieved content as trusted instruction is an architectural problem, not just a wording problem.
How an attack can turn into real-world harm
A malicious email that expands the assignment
Imagine an agent whose stated job is to summarize incoming mail. One message contains text instructing the agent to search the entire mailbox for payroll information and forward matching attachments to an external address. If the agent accepts the message as an operator instruction, it can move from reading one email to searching unrelated records and transmitting sensitive data. OWASP uses this kind of indirect-injection scenario to illustrate excessive agency.
An older OWASP excessive-agency example describes injected content causing an email plug-in to send spam from the user’s mailbox. The important lesson is the boundary crossing: content that should have been treated as data becomes a command to use a privileged function.
Manipulation of a person
A compromised agent may not need to execute a tool call immediately. It can present untrusted claims as verified, hide that a recommendation came from hostile content, or pressure a person to disclose information or approve an action. Because the output appears to come from a familiar assistant, the human may not realize that an attacker supplied the influential instruction.
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Unauthorized changes and transactions
If an agent can send, delete, purchase, change permissions, update records, or initiate a workflow, an injection can convert a text-processing task into an operational event. The severity depends on the permissions and credentials available to the agent. A read-only summarizer has a smaller failure impact than an assistant that can write to production systems and send messages without review.
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Warning signs that an agent may have been tricked
These indicators are practical inferences from documented OWASP attack scenarios. None is a formally validated detection test, and benign requests can sometimes look unusual. Investigate combinations of signs, the input that preceded them, and the tools the agent could reach.
An unnecessary request for secrets
- The agent asks for a password, API key, recovery code, connection string, or other secret that is not required for the task.
- It requests sensitive personal, financial, medical, or company information when a less sensitive value would suffice.
- It asks you to paste credentials into a chat or document instead of using an established authentication flow.
A request can be suspicious even when the agent gives a plausible explanation. Verify the requirement through the application that owns the account, not through the agent’s claim.
A sudden expansion or change of objective
- A request to summarize one file becomes a proposal to search unrelated folders, mailboxes, or databases.
- A scheduling task turns into instructions to forward messages, delete records, make a purchase, or change access.
- The agent starts pursuing an objective that was never stated by the user or required by the workflow.
Scope changes are especially important when they follow content from an external source. The agent may be responding to an embedded instruction rather than to the user’s intent.
Unapproved or inconsistent tool activity
- A tool call appears that the user did not request or approve.
- The selected function is inconsistent with the original task, such as a send, delete, purchase, permission change, or export during a read-only job.
- The agent attempts several actions in sequence without explaining why each is necessary.
Review the exact tool name, arguments, target account, and time. A natural-language explanation is not a substitute for the application’s authorization check.
Instructions inside content are treated as operator commands
Be cautious when an agent says that a document, webpage, email, or tool result told it to override prior instructions. External material should normally provide facts for analysis, not authority to change the agent’s permissions or mission. A model that repeats such directions as if they came from a trusted administrator may have crossed that boundary.
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If the same unauthorized objective reappears after the original content is gone, inspect persistent memory, saved summaries, user profiles, and shared context. OWASP identifies memory poisoning as an agent-security risk. Recurrent behavior does not prove poisoning, but it justifies checking what was stored, who could write it, and how long it is retained.
The agent conceals, distorts, or overstates what happened
A compromised model may omit an action, describe untrusted content as verified, or claim that a tool was not used when logs show otherwise. Compare the response with tool telemetry and source provenance. Treat unexplained discrepancies as an incident signal, particularly when sensitive data or an external recipient is involved.
What to do when suspicious behavior is underway
- Stop the action. Cancel the run, pause the workflow, or disconnect the specific tool session if an operation is pending. Do not continue chatting in a way that supplies additional secrets.
- Revoke the relevant access. Disable the agent’s session token, narrow its tool permissions, or rotate credentials that may have been exposed. Revoke only the affected scope when possible so unrelated services remain available.
- Preserve evidence. Save the user request, retrieved content, model response, tool calls, arguments, recipients, timestamps, approvals, and error messages. Keep the input that immediately preceded each action.
- Determine reachable data and systems. Identify which mailboxes, files, records, APIs, and credentials the agent could access, not just what it claims to have accessed.
- Check for completed side effects. Review sent mail, downloads, exports, purchases, record changes, permission changes, and persistent-memory writes. Confirm with the owning system’s audit trail.
- Contain downstream exposure. If information was sent externally, notify the responsible security or privacy team and follow the organization’s incident process. If credentials may have been disclosed, rotate them through the normal identity system.
- Quarantine the triggering content. Preserve the suspicious email, file, page, or tool response for analysis, but prevent it from being fed to another privileged agent unchanged.
- Test the repaired workflow. Reproduce the path in a non-production environment with harmless data, then verify that the agent cannot perform the same action without the required approval.
The available guidance supports containment, least privilege, approval controls, and monitoring; it does not define a single universal incident-response procedure. Use your organization’s security, privacy, and legal requirements for notification and recovery decisions.
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Establish a trust boundary around every external source
Classify user-supplied text, email, webpages, files, retrieved documents, API responses, and tool output as untrusted data by default. Pass that content to the model in a clearly delimited form and label its origin. Input validation and delimiters can reduce confusion, but they are not authorization mechanisms.
Design the application so that external content cannot silently grant a new capability. The model may extract facts from a document, but a document must not be able to grant permission to send mail or access another user’s records. Enforce that distinction in code and service boundaries, not only in a system prompt.
Use a quarantined parser for high-risk material
For documents, web pages, or messages likely to contain hostile instructions, use a processing stage with no action-taking tools and no production credentials. Let that stage extract text, classify content, or produce a proposed summary. A separate, more privileged component can then evaluate the result under its own authorization rules.
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This arrangement limits the damage if the parser follows an injection: it can read and describe risky content, but it cannot send, delete, purchase, change access, or write to production systems.
Apply least privilege to tools and data
Expose only the functions needed for the agent’s stated job. Scope credentials by user, tenant, resource, operation, and time. Prefer read-only interfaces for analysis and separate them from write-capable interfaces. Keep authorization checks in the backend service that owns the data; do not ask the model to decide whether a user is allowed to retrieve or modify a record.
Remove unused tools and fail closed when a tool is unknown, an argument is incomplete, or an approval requirement is missing. Excess functionality, excessive permissions, and excessive autonomy are recurring roots of excessive-agency failures in OWASP guidance.
Gate consequential actions with explicit approval
Require a human to review the exact proposed operation before the agent executes a high-impact action. The approval screen should identify the destination, records, files, recipients, amounts, and changes involved, along with the source that caused the proposal.
- Sending or forwarding email or files
- Deleting messages, records, or storage objects
- Making purchases, transfers, or other financial commitments
- Changing permissions, account settings, or security controls
- Publishing content or modifying production data
Use stronger confirmation for irreversible actions, bulk operations, unusual recipients, and proposals triggered by external content. Approval should be enforced by the application or workflow engine; an agent’s statement that approval was obtained is not sufficient.
Protect memory and secrets
Validate information before writing it to persistent memory. Isolate memory by user, tenant, and session; define expiration limits; and audit who or what can modify stored context. Avoid allowing a document or email to write directly into durable instructions.
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Never place credentials, connection strings, or other secrets in a system prompt. OWASP’s system-prompt-leakage guidance states that “system prompts should not be considered a secret, nor should it be used as a security control.” Store secrets in an appropriate secret-management system and provide narrowly scoped, short-lived access through backend services.
Log actions together with their causes
For every tool call, record the acting user, agent version, tool name, arguments, target resource, result, approval decision, timestamp, and the input or retrieved item that led to the call. Preserve enough provenance to answer “why did this action happen?” without relying on the model’s later explanation.
Alert on scope expansion, unusual recipients, bulk access, secret requests, denied approvals, repeated retries, and write operations during read-only tasks. Logs should be protected from alteration and linked to the organization’s normal monitoring and retention controls.
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Test more than the chat box. Feed adversarial content through emails, documents, webpages, search results, API responses, and tool outputs. Include multi-step workflows in which one agent’s output becomes another agent’s input. Test whether the agent can be induced to read unrelated records, write memory, bypass an approval, or conceal an action.
Repeat testing after model, prompt, tool, parser, or permission changes. OWASP’s guidance treats adversarial testing and action logging as ongoing controls rather than one-time configuration tasks.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose safeguards by the failure they address
| Security function | Controls | Question to answer |
|---|---|---|
| Reduce hostile input’s influence | Trust boundaries, input validation, clear delimiters, quarantined parsing | Can the agent analyze hostile content as data without accepting it as authority? |
| Limit consequences | Least-privilege tools, scoped credentials, read-only modes, separate tenants | What is the worst action possible if the model is manipulated? |
| Block high-impact actions without consent | Human approval, destination and argument review, confirmation for irreversible operations | Which operations always require explicit approval? |
| Detect and investigate | Tool-action logs, input provenance, anomaly alerts, adversarial testing | Can an operator reconstruct why an action happened and test the same path? |
These controls serve different purposes. The available OWASP material does not provide comparative success rates showing that one is statistically superior to another. A resilient design layers them so that a successful injection still encounters limited permissions, an approval gate, and an auditable trail.
A practical deployment checklist
- List every external source the agent can read and label each as untrusted by default.
- Document the agent’s intended task, allowed data, allowed tools, and forbidden side effects.
- Remove tools that are not required, and make credentials narrowly scoped and short-lived.
- Separate content parsing from action execution for high-risk files, pages, and messages.
- Require application-enforced approval for sending, deleting, purchasing, changing access, and other consequential operations.
- Keep secrets out of prompts, retrieved documents, persistent memory, and conversation transcripts.
- Validate and isolate memory writes; set retention and expiration limits.
- Log the input provenance and complete arguments for every tool call.
- Alert on unexplained scope changes, secret requests, unusual recipients, and write actions in read-only workflows.
- Run adversarial tests against direct and indirect injections before release and after material changes.
- Define who can stop an agent, revoke its access, investigate logs, and notify affected parties.
What prompt-based defenses cannot promise
A carefully written system prompt can clarify the intended role, but it cannot be treated as a security boundary. Models process instructions and data in the same general language channel, so a hostile passage can compete with legitimate directions. OWASP states that “there is no fool-proof prevention within the LLM.” Its guidance also notes that retrieval-augmented generation and fine-tuning do not fully mitigate prompt injection.
Do not rely on hiding the system prompt, adding a single warning sentence, or choosing a particular phrase as the primary defense. A model may disclose prompt content, misinterpret priorities, or follow an injection despite those measures. Authorization, isolation, least privilege, approval gates, and monitoring must be implemented outside the model.
The practical standard for a trustworthy agent
You should be able to explain what an agent is allowed to read, what it is allowed to do, which actions require a person’s approval, and how an operator can reconstruct every side effect. When an email, page, file, or tool result tries to expand the mission, the agent should treat it as untrusted content, remain within its assigned permissions, and pause before a consequential action. That combination—not a supposedly perfect prompt—is how an organization limits social-engineering attacks on AI agents.
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