APIsec for LLM embeddings endpoints

APIsec treats endpoints that serve or process vector embeddings as first-class API surfaces. Because these endpoints often accept and return high-dimensional data, they are exposed to prompt injection, model misuse, and data exfiltration risks. The scanner applies LLM-specific adversarial probes across three tiers: Quick, Standard, and Deep. It focuses on how embeddings are generated, transformed, and consumed without making assumptions about model internals.

APIsec maps findings to OWASP API Top 10 (2023) and supports audit evidence for security controls around embeddings endpoints. Detection includes prompt injection attempts, embedding manipulation, and exposure of sensitive vectors. The scanner validates input handling for embedding requests, including text and metadata fields, and checks whether upstream safeguards limit harmful content or token misuse.

For each embedding-related endpoint, the tool records the request method, parameter schema, and response patterns. It flags anomalies such as missing rate limits, overly permissive CORS, and verbose error messages that may reveal model behavior. These findings help teams understand exposure around vector storage, similarity search, and downstream model consumption.

APIsec does not perform active SQL injection or command injection against embeddings endpoints, as those require intrusive payloads outside the scanner scope. It does not detect business logic vulnerabilities that depend on domain-specific semantics of vector similarity or model behavior. Blind SSRF involving out-of-band infrastructure is also out of scope.

The tool does not replace a human pentester for high-stakes audits of embedding pipelines. It surfaces relevant findings but cannot validate model internals, training data quality, or the mathematical robustness of embeddings. Security teams should complement APIsec with model-specific reviews and threat modeling for AI workflows.

Authenticated scans for embeddings endpoints require Bearer, API key, Basic auth, or Cookie credentials. Domain verification is enforced through DNS TXT records or an HTTP well-known file, ensuring only the domain owner can submit credentials. Header allowlist is applied strictly, forwarding only Authorization, X-API-Key, Cookie, and X-Custom-* headers to prevent credential leakage.

When credentials are provided, the scanner exercises authorized paths that may include private or role-specific embedding endpoints. This helps surface privilege escalation, broken object level authorization (BOLA), and over-exposed embedding routes that are otherwise hidden to unauthenticated probes.

APIsec returns prioritized findings with remediation guidance rather than attempting to fix or patch issues. For LLM embeddings, guidance includes tightening input validation, enforcing strict CORS policies, applying rate limits, and auditing downstream model usage. Teams can integrate scanning into CI/CD via the GitHub Action, enforce score thresholds, and receive alerts through email or Slack on Pro tier and above.

Programmatic access is available through the API client and MCP Server, enabling automated scans for embedding services as part of broader security workflows. Reports include JSON output and branded compliance PDFs, helping teams document controls for internal reviews and policy alignment.