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The safest design treats the bot as two separate security boundaries. Discord authorization decides which people, commands, channels and events can reach your application. Your application then decides what the submitted text is allowed to make the local language model and host do. A model running on your computer can reduce dependence on a cloud inference provider, but it does not make Discord input trustworthy and it does not remove the model API’s network boundary.
Keep authorization and consequential actions in ordinary application code, not in a system prompt. Use the least Discord permissions and Gateway intents that your feature needs, keep the local inference service on loopback or a deliberately restricted private network, and handle every prompt, attachment, retrieved document and model response as untrusted data.
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The security model: two boundaries, not one
A Discord bot that forwards prompts has two different attack surfaces. Mixing them leads to gaps: Discord permissions cannot stop a malicious prompt from attempting to manipulate the model, while a carefully written model prompt cannot authorize a Discord user or protect an exposed API port.
| Boundary | What it controls | Where enforcement belongs |
|---|---|---|
| Discord-to-application | Who can invoke the bot, which command is available, which guild or channel is allowed, and which event data the bot receives | Discord application-command permissions, guild/channel/role checks, Gateway intent selection, request-signature verification and normal application code |
| Application-to-model-and-host | What user text, files and model output can access; whether tools, files, network destinations or Discord actions are permitted | Deterministic validation, allowlists, process and filesystem isolation, resource limits and explicit authorization in application code |
The local model should normally be a text-generation component. If it is manipulated, the worst it can do should be limited by the process account, reachable files, network policy and the small set of tools your application deliberately exposes.
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Restrict how users invoke the bot
Prefer explicit application commands
Use a slash or other application command for prompt submission when that satisfies the product. Discord describes application commands as the primary way users invoke an app. A command-driven bot does not need to monitor every ordinary message in a channel, which reduces both accidental data collection and the number of places where authorization can be missed.
Define the command’s options narrowly. For example, expose a prompt field and, if required, a small enumerated choice such as a response style. Do not accept an arbitrary command name, URL, file path or “action” argument merely because the model might understand it. Validate length, character encoding and option values before constructing a model request.
Scope permissions at every relevant level
Use Discord’s command-permission controls and your own checks together. Restrict commands to the guilds, roles, users and channels that have a business reason to use them. Check authorization before reading optional attachments, retrieving context or calling the model. A hidden command is not a security control by itself; the bot must reject an unauthorized interaction in application code.
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- Prefer a dedicated role and approved channels over a server-wide permission.
- Check the interaction’s guild, channel and user at runtime, not only during installation.
- Return a generic denial message; do not disclose internal role names, configuration or stack traces.
Choose Gateway or HTTP deliberately
A Gateway-based bot receives interactions through its existing Gateway connection and does not need a public interactions endpoint. That removes an internet-facing HTTP service from the design, although the bot still needs normal outbound connectivity to Discord.
If you use HTTP interactions, verify Discord’s X-Signature-Ed25519 and X-Signature-Timestamp headers on every request against the exact raw request body. Reject failed verification before parsing or processing the payload. Discord’s HTTP interaction flow also requires an appropriate response to PING requests. Never verify a re-serialized JSON object when the signature was calculated over the original bytes.
Request only the Discord data you need
Understand privileged intents
Message Content, Guild Members and Guild Presences are privileged Gateway intents. Message Content governs access to user-entered message-content fields across Discord APIs; member and presence intents expose additional user and activity data. Enable only the intents required by a specific feature, and request those intents in the Gateway identify payload.
If a slash command carries the user’s text in its option value, that may let you avoid reading general channel messages and therefore avoid Message Content. Verify the actual fields and behavior in the current Discord documentation and your library; do not assume that every message field is available without the intent.
Discord’s current guidance, dated June 10, 2026, says applications with more than 10,000 unique users who can see the app across their servers must apply for privileged-intent access. Granted access must be reapplied for annually. This threshold and process are platform rules that can change, so check the Developer Portal and current guidance before launch.
Minimize event and attachment handling
Ignore events your feature does not use. Do not download every attachment “just in case.” If a command supports a file, enforce a size and type policy, scan or parse it in a constrained worker, and pass only the text actually needed for the requested operation. Treat filenames, captions, embeds and retrieved documents as attacker-controlled strings.
Keep the local model API private
Use loopback when bot and model share a host
Ollama’s documented default bind address is 127.0.0.1:11434. Keeping that loopback binding means only processes on the same machine can reach the HTTP API through that address. Do not change it merely to make a remote test client convenient.
The OLLAMA_HOST setting changes the bind address. If containers or separate hosts require a connection, bind to a private interface and enforce a firewall rule that permits only the bot’s host or private network. A model port that is reachable from the public internet is an unauthenticated prompt-and-inference service unless you have separately implemented and verified authentication, authorization, rate limiting and network filtering.
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Separate hosts without creating a public service
For a containerized deployment, place the bot and model in a private network and expose the model port only to the bot’s network identity. For separate machines, use a private routed segment or a tightly restricted tunnel and firewall policy. Record which component can reach the endpoint and test from an untrusted network that the port is not reachable.
A reverse proxy can provide a controlled path, but proxying alone does not prove that authentication or authorization is configured. If you put a proxy in front of Ollama, explicitly configure identity checks, destination restrictions, request limits and encrypted transport where the network requires it.
Disable cloud features when local-only is a requirement
Ollama documents OLLAMA_NO_CLOUD=1, or disable_ollama_cloud in its server configuration, for disabling cloud features. Confirm the setting in the running service and review its outbound firewall policy. The word “local” by itself does not establish that no optional cloud or outbound network behavior is enabled.
Make prompts and model output untrusted
Why a system prompt is not an authorization boundary
Prompt injection is an attempt to change the model’s behavior through user text, an attachment, a retrieved document or another piece of context. The model may follow an instruction such as “ignore previous rules” even when your system message says not to. OWASP’s 2025 LLM guidance recommends enforcing privilege control and least privilege; it does not treat a system prompt as a substitute for those controls.
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Keep security decisions outside the model. Your code should decide whether a user may invoke a command, whether a file can be read, which tool may run and whether an action requires confirmation. The model can propose text or a structured request; it must not grant itself permission.
Use a narrow, explicit tool boundary
The safest configuration exposes no tools at all: the model receives text and returns text. If your product genuinely needs tools, define each one in normal code with a small allowlist and deterministic validation.
- Identify the Discord user, guild and channel from the verified interaction, not from model-generated text.
- Check that the user is authorized for the requested operation.
- Parse the model’s proposed tool call against a strict schema. Reject unknown fields, extra arguments and invalid types.
- Validate targets against an allowlist. Never accept an arbitrary shell command, SQL fragment, filesystem path or URL from the model.
- Apply a second authorization check immediately before execution, then require human confirmation for consequential actions.
- Return only a deliberately shaped result to the model and to Discord.
Do not let model-generated strings flow directly into a shell, SQL engine, filesystem API, arbitrary HTTP client or moderation endpoint. If a tool must access files, run it under a restricted account with a dedicated directory and no access to secrets or the bot’s deployment configuration.
Constrain context and output
Put hard limits on prompt size, attachment size, retrieved-document volume, output tokens, generation time and concurrent jobs. Limits protect availability as well as safety: a user can otherwise submit repeated long prompts that monopolize CPU, memory or GPU resources.
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A secure request path
The following sequence keeps trust decisions in the application and makes the model a constrained dependency:
- Receive a Gateway interaction, or verify the HTTP signature over the raw request body before parsing it.
- Reject unsupported interaction types and malformed fields.
- Check guild, channel, user, role and command permissions in application code.
- Apply per-user, per-guild and global rate limits before downloading files or calling the model.
- Normalize and bound the prompt. Treat attachments and retrieved text as untrusted context, and record only the minimum metadata needed for operations.
- Build a model request that contains no bot token, API key, cookie, private deployment setting or unnecessary personal data.
- Call the model through a loopback or restricted private route with a finite timeout.
- Validate the response. If it is intended to be structured, parse it against a schema and reject anything outside the schema.
- Run any permitted tool through deterministic authorization and validation. Ask for confirmation before consequential actions.
- Sanitize the final Discord message, cap its size and send a generic failure response when processing fails.
Operational limits that prevent abuse
Security controls are ineffective if one user can consume all local inference capacity. Choose limits based on your hardware and service expectations, document them for server owners and enforce them before expensive work starts.
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| Control | What to bound | Failure behavior |
|---|---|---|
| Input | Prompt characters or tokens, attachment bytes and number of attachments | Reject with a clear size message; do not truncate silently when truncation could change meaning |
| Concurrency | Jobs per user, guild and process | Queue a small permitted number or return a busy response |
| Time | Model generation and total interaction time | Cancel the request and return a generic timeout message |
| Usage | Requests per user and guild over a defined window | Rate-limit before model invocation |
| Output | Generated tokens and Discord message length | Validate, truncate safely or split according to Discord limits |
Handle exceptions centrally. Logs should contain a correlation ID, timing and coarse outcome rather than full prompts by default. Protect logs as sensitive data because prompts and responses may contain personal, confidential or proprietary information.
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Do not train on Discord API message content without permission
Discord’s Developer Policy states: “Do not use message content obtained through the APIs to train machine learning or AI models (including large language models) unless express permission is granted by Discord.” Do not train or fine-tune on API-obtained message content without that express permission.
Training is separate from normal inference, logging and retention. Decide what prompts and responses you retain, for how long, who can access them and how users or server owners are informed. Minimize retention, redact personal data and secrets where practical, and make deletion and access procedures fit the requirements that apply to your deployment.
Keep credentials out of prompts and logs
- Store the Discord bot token in a protected secret store or restricted process environment, never in source control.
- Do not include the token, authorization headers, cookies, private keys or deployment variables in model context.
- Restrict which accounts and services can read the process environment and log files.
- Rotate the bot token promptly if it is exposed, and remove the exposed value from logs and code repositories.
- Use separate credentials and least-privilege accounts for development, testing and production.
There is no single Discord-specific rotation schedule established here; set a schedule and an emergency-revocation procedure appropriate to your organization.
Deployment choices at a glance
| Design | Model reachability | Required controls | When it fits |
|---|---|---|---|
| Single host, loopback | Bot reaches 127.0.0.1:11434; other network hosts should not |
Host account isolation, local firewall policy, resource limits and secret protection | Most straightforward local deployment |
| Private container network | Only the bot’s network or service identity reaches the model | Network policy, non-public port binding, container filesystem and process restrictions | Bot and model are separate containers |
| Separate private host | Private routed path or restricted tunnel | Firewall allowlist, transport protection where needed, authentication and monitoring | Inference hardware is on another machine |
| Publicly reachable model endpoint | Internet clients can attempt to reach the API | Not recommended for a default setup; would require independently verified authentication, authorization, rate limiting and edge protection | Avoid unless there is a compelling, reviewed architecture |
The important comparison is not which runtime sounds local. It is which component can reach the API, whether that path is loopback or private, whether authentication and firewall controls exist, whether cloud or outbound access is enabled, and which Discord intents and permissions are required.
Pre-launch security test checklist
Use a private test server and verify each boundary deliberately:
- An unapproved user cannot invoke the command.
- An approved user in an unapproved channel or guild is denied.
- Removing a required role takes effect without restarting the bot.
- The bot works with only the intents it actually needs.
- If HTTP interactions are enabled, altered, missing and stale signature headers are rejected, while valid PING requests receive the required response.
- Oversized prompts, attachments, repeated requests and concurrent jobs are bounded.
- Prompts and supplied documents containing “ignore previous instructions” do not bypass application authorization.
- Model output cannot select an arbitrary shell command, SQL statement, file path, URL or Discord action.
- Timeouts, malformed output and model process failures produce safe messages without paths, secrets or stack traces.
- A network scan from an unintended host cannot reach the Ollama port.
- The running configuration confirms the intended cloud and outbound-network policy.
- Logs do not expose bot tokens, authorization headers or unnecessary prompt content.
Common failure modes and fixes
“The bot cannot read a message”
First determine whether the feature is using a slash-command option or trying to read ordinary channel messages. Ordinary message content may require the privileged Message Content intent, which must be enabled in the application settings and requested in the Gateway identify payload. If the feature only needs command text, redesigning it around an application command may remove that dependency.
“A remote container cannot connect to Ollama”
Loopback binding accepts connections only from the same host. If separation is intentional, bind Ollama to a private interface using the documented host setting, then allow only the bot’s private network through firewall and container policy. Do not solve the problem by binding the service to every interface without access controls.
“The model followed an instruction in an attachment”
That is an expected prompt-injection risk, not evidence that the system prompt is strong enough. Treat the attachment as untrusted data, keep tools disabled unless required, and move authorization and validation into deterministic application code. If a proposed action is consequential, require confirmation from an authorized user.
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Separate internal diagnostics from the Discord response path. Catch exceptions at the interaction boundary, log a correlation ID and safe operational details, and return a generic error. Review logs for leaked tokens, environment variables and filesystem paths.
Quick Recap
Final deployment checklist
- Invocation uses an explicit application command where practical.
- Guild, channel, role and user authorization is checked before model work.
- Bot permissions and Gateway intents are minimized; privileged-intent requirements are reviewed against current Discord guidance.
- HTTP signatures are verified over the exact raw body if HTTP interactions are used.
- Ollama remains on loopback, or a private network path is protected by allowlisted firewall rules.
- Cloud features and outbound network access match the documented requirement.
- Prompts, files, retrieved text and model output are treated as untrusted.
- No model-generated value directly controls a shell, database, filesystem, arbitrary URL or moderation action.
- Input, output, time, concurrency and usage limits are enforced.
- Secrets are outside source control, prompts and routine logs.
- Discord API message content is not used for training without express permission.
- Abuse, injection, timeout, malformed-output and network-exposure tests pass in a private server.
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