Log Injection in Echo Go with Bearer Tokens

Log injection occurs when untrusted input is written directly into log files without proper sanitization, enabling an attacker to forge log entries, obscure real events, or inject newline characters that facilitate log forging or log poisoning. In Go services built with the Echo framework, this risk is pronounced when developers embed request-scoped data—such as authentication details from Authorization headers—into structured logs without validation or escaping.

When Bearer tokens are used for authentication in Echo, the Authorization header typically carries a token string like Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9. If the application logs this header naively, for example by concatenating it into a log line without sanitization, an attacker can supply a token containing newline characters or structured delimiters. A crafted token like Bearer abc\nMaliciousLogEntry: injected=true can split a single logical log entry into multiple lines, corrupting log context and enabling log forging attacks.

Echo applications often log method, path, and user identity derived from the token payload or claims. If a token’s payload is improperly validated and directly interpolated into logs, an attacker can inject false claims or metadata. For instance, a token with embedded newline and tab characters can create fake authentication success/failure records, complicating incident response and violating audit integrity.

This combination is particularly risky in microservice architectures where logs are aggregated centrally. Injected newline sequences can break log parsers, cause misattribution of events, and bypass monitoring rules that rely on consistent log structure. The risk is not theoretical: patterns like CVE-2021-44228 demonstrate how log injection can lead to remote code execution when logs are later processed insecurely, even if the initial injection vector is limited to log data.

middleBrick’s LLM/AI Security checks include output scanning for secrets such as API keys and tokens that may appear in log data, helping detect whether Bearer tokens are inadvertently exposed through log injection. While this does not remediate log injection, it highlights how token leakage through logs can compound risk. Proper input validation and structured logging practices are essential to ensure that authentication tokens remain confined to secure channels and do not corrupt log integrity.

To mitigate log injection when using Bearer tokens in Echo Go, sanitize and structure all data written to logs. Avoid direct concatenation of raw headers; instead, extract only the necessary portions and escape special characters. Below are concrete, realistic examples demonstrating secure handling.

Insecure Example (vulnerable):

func InsecureHandler(c echo.Context) error {
    auth := c.Request().Header.Get("Authorization") // "Bearer abc\nMalicious..."
    // Dangerous: directly logging raw Authorization header
    log.Printf("Request auth: %s", auth)
    return c.String(http.StatusOK, "ok")
}

The above allows newline injection from the token, corrupting logs.

Secure Remediation Example:

import (
    "log"
    "net/http"
    "strings"

    "github.com/labstack/echo/v4"
)

func SecureHandler(c echo.Context) error {
    auth := c.Request().Header.Get("Authorization") // "Bearer eyJhbGci..."
    const bearerPrefix = "Bearer "
    // Validate prefix and extract token without newlines
    if !strings.HasPrefix(auth, bearerPrefix) {
        return c.String(http.StatusUnauthorized, "invalid authorization header")
    }
    token := strings.TrimPrefix(auth, bearerPrefix)
    // Remove any whitespace/newlines that could be used for injection
    token = strings.ReplaceAll(token, "\n", "")
    token = strings.ReplaceAll(token, "\r", "")
    // Structured logging: log only what is needed, escaped
    log.Printf("Request auth token=[REDACTED] user_id=extracted_claim")
    return c.String(http.StatusOK, "ok")
}

Key practices demonstrated:

• Prefix validation ensures the header conforms to the Bearer scheme.
• Token extraction uses strings.TrimPrefix rather than raw header usage.
• Newline and carriage return characters are removed to prevent line-splitting injection.
• Logs avoid echoing the full token; a placeholder like [REDACTED] is used, and only necessary metadata (e.g., user claims extracted securely) is logged.

For production, adopt a structured logger (e.g., using log/slog) to enforce consistent field formatting and automatic escaping:

import (
    "log/slog"
    "net/http"
    "strings"

    "github.com/labstack/echo/v4"
)

func StructuredSecureHandler(c echo.Context) error {
    auth := c.Request().Header.Get("Authorization")
    const bearerPrefix = "Bearer "
    if !strings.HasPrefix(auth, bearerPrefix) {
        return c.String(http.StatusUnauthorized, "invalid authorization header")
    }
    token := strings.TrimPrefix(auth, bearerPrefix)
    token = strings.ReplaceAll(token, "\n", "")
    token = strings.ReplaceAll(token, "\r", "")
    // Structured log with explicit fields; the logger handles safe output
    slog.Info("request authorized",
        "method", c.Request().Method,
        "path", c.Request().URL.Path,
        "token_status", "valid_bearer",
    )
    return c.String(http.StatusOK, "ok")
}

These patterns ensure that Bearer tokens do not corrupt log structure, while still enabling necessary audit trails. Remember that middleBrick’s CLI tool (middlebrick scan <url>) can help identify missing input validation, and the GitHub Action can enforce security checks in CI/CD pipelines to catch such issues before deployment.