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What counts as an LLM-gateway compromise?
An LLM gateway (also called an AI proxy or model router) sits between users or applications and model providers. It commonly handles authentication, tenant routing, model selection, prompt and response policy, tool or plugin calls, rate limits, logging, and usage metering. A compromise can therefore affect more than the model API key. An intruder might steal a token, alter a route, attach a new model, disable a guardrail, impersonate a tenant, invoke a tool, or use legitimate credentials to extract data.
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Look for correlated anomalies across systems, not a single suspicious completion. NIST API guidance (SP 800-228) treats API lifecycle risk analysis and runtime controls as essential. NIST token guidance emphasizes key management, token verification, lifecycle controls, and continuous monitoring. OWASP guidance adds telemetry for input distribution, output entropy, latency, access traceability, unusual usage, prompt injection, excessive agency, and runtime-isolation failures.
- Identity: new principals, privilege changes, unfamiliar key-use locations, or disabled verification.
- Configuration: new routes, models, plugins, tools, guardrails, tenants, or orphaned deployments.
- API behavior: request, token, error, latency, response-size, or model-mix changes that exceed the normal baseline.
- Content: prompt-injection attempts, instructions to reveal secrets, policy-bypass patterns, or completions that are unsafe for downstream code.
- Actions: tool calls, data access, messages, transactions, or other external effects without matching user intent.
- Auditability: missing session, user, agent, or tenant context; disabled sinks; unexplained log gaps; or credentials appearing in logs.
No authoritative source currently provides a reliable percentage for how often LLM gateways are compromised. The defensible approach is indicator-based: establish a baseline, preserve synchronized evidence, and corroborate signals across identity, gateway, model, tool, network, and billing systems.
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Warning signs that deserve immediate investigation
Unexpected identities and credentials
- A service account, administrator, API key, signing key, OAuth client, or workload identity appears without an approved change record.
- A known key is used from a new country, cloud region, ASN, device class, or network segment, especially at a time the owner was inactive.
- A principal receives a role escalation, a token has an unusual lifetime, or verification and audience checks are disabled.
- Revoked or expired credentials continue to work, or a key is used concurrently from locations that cannot be explained by your architecture.
These signs are consistent with token theft, forgery, replay, or lifecycle weaknesses. They are not conclusive alone: shared egress, corporate VPNs, cloud failover, and scheduled deployments can create legitimate location changes. Verify the principal, workload, and change ticket before deciding whether the event is malicious.
Gateway and routing changes
- A route points to an unknown model endpoint, region, tenant, or provider.
- A new model, plugin, connector, tool, webhook, or deployment appears outside the approved inventory.
- Guardrails, content filters, rate limits, spend caps, audit sinks, or tenant boundaries are weakened or turned off.
- An old deployment remains reachable after retirement, creating an orphaned API surface.
- Configuration files, policies, container images, or infrastructure state change without a signed, reviewed deployment.
Configuration tampering can be more damaging than a stolen key because it changes what every legitimate request can do. Compare the live state with a known-good version, the deployment pipeline, and your change-management records.
Traffic, latency, and cost anomalies
Measure request rate, input and output token counts, response sizes, latency, error classes, model selection, caller, geography, and spend. Useful alerts include:
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- A sudden increase in requests or tokens, particularly repetitive calls that resemble scraping.
- Repeated authorization failures followed by a successful request, or many requests with unusual headers and user agents.
- Activity outside an expected tenant, geography, time window, or network boundary.
- A sharp shift to an expensive or previously unused model, unexplained long contexts, or unusually large completions.
- Latency and error-rate changes that coincide with retries, queue saturation, or a new route.
Compare against a baseline for the same application and time period. A product launch, batch job, incident drill, or model migration can explain a spike; the combination of a spike with identity or configuration anomalies is much stronger evidence.
Prompt and completion indicators
Search security telemetry for direct or indirect prompt-injection attempts, such as content that tells the model to ignore policy, reveal system instructions, disclose credentials, or treat retrieved text as higher-priority instructions. Also examine completions that contain secrets, internal URLs, hidden policy text, or code that would be dangerous if executed automatically.
OWASP’s LLM Verification Standard states: “Ensure that appropriate LLM guards are used to scan prompts and completions to help detect potential prompt injection attacks.” It also says: “Ensure that all prompts are considered to be untrusted and subjected to any deployed security controls.” A suspicious prompt is evidence of an attack attempt, not proof that the gateway was breached. Confirm whether the request bypassed controls, reached unauthorized data, or triggered an external action.
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Unauthorized tools and downstream effects
Excessive agency is a key failure mode. Flag tool calls that are outside the user’s role, exceed the declared task, use a new argument pattern, or occur after a suspicious prompt. Review file reads, database queries, network requests, email or messaging actions, code execution, purchases, and changes to records. A model output is untrusted input to downstream code; a successful completion does not authorize an external side effect.
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Evidence to preserve before you clean up
Preserve forensic copies before rotating credentials or deleting resources. Use synchronized UTC timestamps and retain the original records read-only where possible. Export:
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- Gateway access logs, request IDs, response status, latency, model and route, tenant, source network, and policy decisions.
- Identity-provider events, role assignments, workload identity records, API-key creation and use, token issuance, refresh, verification, and revocation events.
- Model-provider logs, including provider request IDs and usage records.
- Prompt and completion security events, classifier or guard decisions, and content hashes or redacted excerpts.
- Tool, plugin, connector, webhook, and downstream application audit trails, including arguments and returned data.
- Network-flow, DNS, firewall, proxy, egress, and cloud-control-plane records.
- Configuration history, infrastructure state, deployment artifacts, image digests, policy versions, and rollback records.
- Billing, token-usage, quota, and spend data by tenant, principal, model, and time interval.
Keep session IDs, human-principal IDs, agent-run IDs, tenant IDs, request IDs, and trace IDs consistent across systems. Do not copy full sensitive prompts, responses, credentials, or authorization headers into broadly accessible logs. Redact secrets while preserving enough structure to correlate events; store the protected original only under your incident-response access controls.
A practical investigation workflow
1. Establish the incident window
- Record when the first alert, user report, billing anomaly, or configuration change occurred.
- Set a wider search window before and after that event to catch credential creation, reconnaissance, persistence, and delayed downstream actions.
- Normalize timestamps to UTC and note clock skew between the gateway, identity provider, model provider, tools, and cloud logs.
2. Build an identity and access timeline
- List every principal, key, token, service account, and workload that accessed the gateway during the window.
- Compare locations, user agents, network paths, token audiences, scopes, and lifetimes with the approved design.
- Find new accounts, role changes, disabled verification, failed authentication bursts, refresh-token anomalies, and use after revocation.
- Map each credential to an owner and workload. Treat an unmapped credential as suspicious until explained.
3. Diff configuration and deployments
- Export the live gateway configuration and compare it with the last known-good, signed version.
- Review route, model, provider, tenant, guardrail, rate-limit, logging, plugin, tool, webhook, and egress changes.
- Check cloud-control-plane events, source-control commits, CI/CD jobs, image digests, and deployment approvals.
- Identify orphaned endpoints and test whether they still accept traffic.
4. Reconstruct traffic and spend
- Group requests by principal, tenant, route, model, source, session, and agent run.
- Compare rates, token counts, latency, response size, errors, retries, and spend with a normal baseline.
- Look for scraping-like repetition, unusual headers, cross-tenant access, repeated authorization failures, and sudden model or region changes.
- Join gateway usage with provider billing. A mismatch can reveal bypassed logging, an untracked route, or a stolen provider key.
5. Trace prompts, completions, and tools
- Search security events for injection, secret-disclosure, policy-bypass, and data-exfiltration patterns.
- Determine whether retrieved documents, user content, or tool output introduced untrusted instructions.
- For each tool call, verify the requesting principal, authorization decision, arguments, returned data, and downstream effect.
- Inspect whether output was passed directly to code, shell commands, SQL, browsers, email, or other systems without validation and explicit authorization.
6. Test log integrity
Missing session context, disabled audit sinks, unexplained time gaps, sudden drops in telemetry, and secrets in logs are findings in their own right. OWASP’s AI security verification guidance describes request and response logging as the foundation for abuse detection and incident investigation; gaps can enable defense evasion. Compare the gateway’s counters with provider, network, and billing records to detect blind spots.
How to judge confidence without overreacting
| Evidence pattern | What it suggests | Next decision |
|---|---|---|
| One unusual prompt, with normal identity, configuration, traffic, and tools | Likely an attack attempt or benign content; compromise is unproven. | Retain the event, apply prompt controls, and monitor for corroboration. |
| Unknown key or principal plus abnormal location or volume | Probable credential misuse or account compromise. | Preserve logs, revoke or rotate the credential, and investigate access scope. |
| Unauthorized configuration change plus new route, model, plugin, or tool | Probable gateway control-plane compromise. | Disable the change, isolate affected workloads, and restore a verified configuration. |
| Prompt injection followed by secret access or an external action | Confirmed harmful execution path, whether caused by a gateway or downstream flaw. | Contain the principal, tool, data path, and affected downstream systems immediately. |
| Usage or billing spike with missing audit context | Possible bypass, disabled telemetry, or stolen provider credential. | Reconcile provider, network, gateway, and billing records before declaring scope. |
What to do first when compromise is likely
Use an incident commander and keep a written timeline. Avoid deleting evidence while attempting to stop harm.
- Protect evidence: export and preserve the records listed above, including configuration and billing data.
- Revoke and rotate: invalidate exposed API keys, access and refresh tokens, signing keys, provider credentials, and service secrets. Replace them from a trusted management system.
- Disable suspicious access: suspend unknown principals, sessions, routes, models, plugins, tools, webhooks, and orphaned deployments.
- Limit blast radius: apply emergency rate and spend limits, isolate affected tenants or workloads, and restrict egress.
- Quarantine untrusted content: route suspect prompts, retrieved documents, and tool output through a zero-tool path where they cannot trigger external actions.
- Check downstream systems: review data reads, exports, file changes, messages, transactions, and account modifications for the incident window.
- Notify required parties: involve security, identity, platform, legal, privacy, and affected service owners according to your response plan.
Recovery and safe return to service
Restore from a known-good state
Rebuild or roll back the gateway from a verified configuration, trusted image, and clean dependency set. Re-enable only the routes, models, tools, policies, and tenants that have an owner and a documented purpose. Confirm that verification, audience checks, tenant isolation, logging, rate limits, spend controls, and egress restrictions are active before reopening traffic.
Validate credentials and permissions
Issue new credentials with the narrowest practical scope and short, controlled lifetimes. Remove unused keys, orphaned service accounts, excessive roles, and stale deployments. Verify token signatures, issuer, audience, expiry, revocation behavior, and rotation procedures with a controlled test.
Monitor the recovery window
For heightened monitoring, compare identity, traffic, model, tool, network, and billing telemetry continuously rather than waiting for a daily report. Alert on reappearance of the indicators that defined the incident. Keep a complete trace from user intent to model request, policy decision, tool authorization, downstream action, and result.
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| Control area | What to require |
|---|---|
| Identity and authorization | Strong workload and user identity, least privilege, verified token issuer and audience, scoped credentials, and explicit authorization for every tool and external action. |
| Key and token lifecycle | Central issuance, rotation, revocation, expiry, replay resistance, ownership records, and alerts for use after revocation. |
| Tenant and runtime isolation | Separate tenants, workloads, tools, secrets, network paths, and model contexts; prevent one run from reading another tenant’s data. |
| Request, response, and tool telemetry | Consistent request, session, principal, agent, tenant, model, route, policy, tool, and downstream-action identifiers with protected, tamper-evident storage. |
| Prompt and completion guards | Scan untrusted prompts and completions for injection, secret disclosure, unsafe instructions, and policy bypass; treat retrieved text and tool output as untrusted too. |
| Rate, quota, and spend controls | Per-principal and per-tenant limits, model-specific budgets, anomaly alerts, and emergency circuit breakers. |
| Configuration integrity | Signed, reviewed changes; immutable history; drift detection; approved model and tool inventories; and tested rollback. |
| Downstream authorization | Validate model output before code or data-system use, require user or service approval for consequential actions, and log the authorization decision. |
| SIEM and response integration | Forward normalized events, preserve synchronized time, detect log gaps, and maintain playbooks for credential theft, route tampering, prompt injection, and tool abuse. |
Common investigation mistakes
- Declaring compromise from one odd answer: corroborate with identity, configuration, telemetry, or downstream evidence.
- Rotating keys before preserving records: capture the timeline and affected scopes first, then rotate in a controlled sequence.
- Logging everything: broad access to full prompts, responses, tokens, and authorization headers creates a second exposure. Redact and restrict.
- Trusting model output: output is untrusted data, not an authorization decision. Validate it before execution.
- Ignoring provider and billing records: a stolen provider key or bypassed route may not appear in gateway logs.
- Restoring only the application: a compromised identity, deployment pipeline, image, plugin, or downstream system can reinfect a clean gateway.
When can you reasonably close the incident?
Close only after you can explain the initial indicator, identify affected principals and data paths, invalidate exposed credentials, verify configuration and deployments, review downstream actions, and observe stable identity, traffic, tool, network, and billing telemetry through a defined heightened-monitoring period. Document what remains unknown. A clean dashboard is not proof if an audit sink was disabled or a route bypassed the gateway.
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