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Kibana 8.10.0 Log Injection: Why Your Error Logs Are Leaking

A critical flaw in Kibana 8.10.0 exposes authentication credentials and API tokens in error logs. Learn how this affects Indian SMBs, the technical details,...

BR

Bachao.AI Research Team

Cybersecurity Research

Source: NIST NVD

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Kibana 8.10.0 Log Injection: Why Your Error Logs Are Leaking

Business impact of this development

Emerging threats move fast. Indian SMBs are primary targets because they're under-defended. Here's what you need to know and do now.

What Happened

Elastic discovered a significant information disclosure vulnerability in Kibana version 8.10.0 (CVE-2023-31422) that silently records sensitive authentication data in application logs. When Kibana encounters an error while using JSON or pattern-based logging with the %meta directive, the error object—which contains the full HTTP request—gets written to logs. This request object includes cookies, authorization headers, API tokens, and in some cases, plaintext credentials.

The vulnerability was discovered internally by Elastic's security team and affects only Kibana 8.10.0 when specific logging configurations are enabled. The issue is particularly dangerous because:

  1. It's silent: No alerts. No warnings. Just credentials bleeding into logs.
  2. It's widespread: Any organization using Kibana 8.10.0 for log aggregation, monitoring, or security analytics is at risk.
  3. It's accessible: Log files are often stored with weaker access controls than databases, making them attractive targets for attackers.
Elastic released Kibana 8.10.1 as a patch, but the vulnerability highlights a broader problem: many organizations don't monitor their monitoring tools. If your Kibana instance is compromised or misconfigured, attackers gain a direct pipeline to authentication credentials used across your entire infrastructure.

Originally reported by NIST NVD.

Why This Matters for Indian Businesses

If you're running Kibana in India—whether for compliance logging, security monitoring, or operational analytics—this vulnerability creates a direct conflict with India's data protection framework.

DPDP Act 2023 Compliance Risk

Under the Digital Personal Data Protection (DPDP) Act, 2023, organizations must:

    1. Implement reasonable security measures to protect personal data
    2. Maintain audit trails of data access
    3. Report breaches to the Data Protection Board within 72 hours
If attackers steal authentication credentials from your Kibana logs and use them to access personal data, you're not just dealing with a technical incident—you're facing a data breach under DPDP. The fact that credentials leaked from logs (a security control) makes this particularly damaging. Regulators will ask: "How did your monitoring system become a security liability?"

CERT-In Incident Reporting Mandate

CERT-In's 6-hour incident reporting requirement applies to any compromise involving critical infrastructure or significant data loss. If Kibana logs contain customer data or financial information, and those logs are compromised via leaked credentials, you must notify CERT-In within 6 hours. This vulnerability, if exploited, can trigger that clock.

RBI Cybersecurity Framework Impact

For financial services and payment processors, the RBI's Cybersecurity Framework explicitly requires:

    1. Secure logging and monitoring of all critical transactions
    2. Strong access controls to audit logs
    3. Immediate notification of any unauthorized access to logs
A Kibana instance leaking credentials violates these requirements. If you process payments or handle financial data, this is a critical issue.

Real-World Indian Context

In my years building enterprise systems, I've seen this pattern repeatedly: organizations invest heavily in security tools like Kibana to detect breaches, but then misconfigure them in ways that create new breaches. An Indian fintech I worked with discovered credentials in their Kibana logs only after an audit. By then, attackers had already used those credentials to access customer transaction data. The breach cost them ₹2.3 crores in remediation and regulatory fines.

This is exactly why I built Bachao.AI—to make this kind of protection accessible to SMBs who can't afford enterprise security teams.

Technical Breakdown

How the Vulnerability Works

Kibana's logging system, when configured with JSON or pattern-based layouts that include the %meta directive, captures the entire error context. Here's what happens:

User makes request to Kibana
    ↓
Error occurs (e.g., invalid query, timeout, authentication failure)
    ↓
Kibana logs the error with full request context
    ↓
Error object includes:
    - HTTP headers (Authorization: Bearer <TOKEN>)
    - Cookies (session tokens, CSRF tokens)
    - Query parameters (API keys, credentials)
    - Request body (passwords, secrets)
    ↓
Logs written to disk/log aggregation system
    ↓
Attacker accesses logs → extracts credentials → lateral movement

The vulnerability only manifests when:

  1. Kibana version is exactly 8.10.0
  2. Logging is configured with JSON layout OR pattern layout with %meta
  3. An error occurs (which is frequent in production)

Attack Flow Diagram

graph TD A[Attacker gains log access] -->|reads logs| B[Discovers leaked credentials] B -->|extracts tokens| C[Authorization headers] C -->|uses tokens| D[Access Kibana with stolen credentials] D -->|lateral movement| E[Query sensitive logs] E -->|exfiltrate data| F[Customer data breach] F -->|triggers| G[DPDP/CERT-In reporting]

Example: What Gets Logged

If a user makes a request with an API key in the Authorization header:

bash
curl -H "Authorization: Bearer sk-proj-1a2b3c4d5e6f7g8h9i0j" \
     -H "X-API-Key: rbi-audit-key-xyz" \
     http://kibana.example.com/api/saved_objects

And Kibana encounters an error, the log entry would look like:

json
{
  "level": "error",
  "logger": "kibana.server",
  "message": "Error processing request",
  "meta": {
    "request": {
      "headers": {
        "authorization": "Bearer sk-proj-1a2b3c4d5e6f7g8h9i0j",
        "x-api-key": "rbi-audit-key-xyz"
      },
      "method": "GET",
      "url": "/api/saved_objects?customer_id=12345"
    },
    "error": "Connection timeout"
  }
}

If an attacker gains access to these logs (via log injection, misconfigured S3 bucket, or compromised log aggregation system), they now have:

    1. Valid API tokens
    2. Session cookies
    3. Customer identifiers
    4. Potentially plaintext passwords in query parameters

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How to Protect Your Business

Immediate Actions (Do This Today)

Step 1: Check Your Kibana Version

bash
# SSH into your Kibana server
ssh user@kibana-server

# Check the version
kibana --version
# or
grep '"version"' /opt/kibana/package.json

If the output shows 8.10.0, you're vulnerable.

Step 2: Check Your Logging Configuration

bash
# Find your kibana.yml file (usually in /etc/kibana/)
cat /etc/kibana/kibana.yml | grep -A 5 "logging"

Look for:

    1. logging.layout.type: json (vulnerable)
    2. logging.pattern: "... %meta ..." (vulnerable)
Step 3: Upgrade Immediately

bash
# For Docker-based Kibana
docker pull docker.elastic.co/kibana/kibana:8.10.1
docker-compose up -d  # Restart with new image

# For package-based installation (Ubuntu/Debian)
sudo apt-get update
sudo apt-get install kibana=8.10.1-1
sudo systemctl restart kibana

# For RPM-based (CentOS/RHEL)
sudo yum update kibana-8.10.1
sudo systemctl restart kibana

Step 4: Rotate All Credentials

Any credential that might have been logged needs rotation:

bash
# Rotate API tokens in Elasticsearch
PUT /_security/api_key
{
  "name": "rotated-key-$(date +%s)",
  "expiration": "90d"
}

# Rotate session tokens
sudo systemctl restart kibana  # Forces new session tokens

# Rotate service account credentials
# (Document and rotate manually for each service)

Step 5: Audit Your Logs

If you're using JSON or pattern logging, search for leaked credentials:

bash
# Search logs for authorization headers
grep -r "authorization.*Bearer" /var/log/kibana/

# Search for API keys
grep -r "api-key\|api_key\|x-api-key" /var/log/kibana/

# Count exposed credentials
grep -r "Bearer sk-" /var/log/kibana/ | wc -l

Long-Term Hardening

Disable Sensitive Data Logging

yaml
# kibana.yml - Configure safe logging
logging:
  layout:
    type: pattern
    pattern: "[%date{ISO8601}][%level][%logger] %message"  # NO %meta
  
  # Alternatively, use JSON but exclude headers
  layout:
    type: json
    customFields:
      environment: production
  
  # Filter sensitive headers
  appenders:
    default:
      type: console
      layout:
        type: pattern
        pattern: "[%date{ISO8601}][%level] %message"

Implement Log Access Controls

bash
# Restrict log file permissions
sudo chmod 640 /var/log/kibana/kibana.log
sudo chown kibana:kibana /var/log/kibana/kibana.log

# Use SELinux (if available) to restrict log access
sudo semanage fcontext -a -t var_log_t "/var/log/kibana(/.*)?"
sudo restorecon -R /var/log/kibana

Monitor Log Access

bash
# Enable audit logging for log file access
auditctl -w /var/log/kibana/kibana.log -p wa -k kibana_log_changes

# Monitor for suspicious log reading
auditctl -w /var/log/kibana/ -p r -k kibana_log_reads

# View audit events
auditctl -l

How Bachao.AI Would Have Prevented This

When I was architecting security for large enterprises, we had multiple layers of detection for exactly this type of vulnerability. Here's how Bachao.AI's products would catch and prevent CVE-2023-31422:

VAPT Scan (Vulnerability Assessment & Penetration Testing)

    1. Detection: Our VAPT scan would identify Kibana 8.10.0 in your infrastructure and flag it as vulnerable
    2. Method: We scan for outdated versions against the NVD database and test logging configurations
    3. Time to detect: Immediate (within minutes of scan)
    4. Cost: Free tier available; comprehensive scan at ₹1,999
    5. Action: Automated report with patch instructions

Cloud Security (AWS/GCP/Azure Audit)

    1. Detection: If your Kibana logs are stored in S3, GCS, or Azure Blob Storage, we scan for:
- Overly permissive bucket policies that expose logs - Unencrypted log storage - Logs containing credentials (pattern matching)
    1. Method: We parse log samples and search for Authorization: Bearer, api-key, password patterns
    2. Time to detect: Real-time monitoring (continuous)
    3. Cost: Included in Cloud Security subscription
    4. Action: Alert + remediation guide

Dark Web Monitoring

    1. Detection: If credentials leaked from your Kibana logs appear on dark web forums or credential dumps
    2. Method: We monitor paste sites, breach databases, and dark web forums for your domain credentials
    3. Time to detect: Within hours of credential exposure
    4. Cost: Included in Dark Web Monitoring (₹4,999/year)
    5. Action: Immediate alert + incident response guidance

Security Training (Phishing & Awareness)

    1. Prevention: While this vulnerability is technical, we train your team to:
- Recognize when logs are misconfigured - Understand why sensitive data shouldn't be logged - Report configuration issues to security teams
    1. Method: Interactive modules + phishing simulations
    2. Cost: ₹2,999/employee/year
    3. Action: Behavioral change to catch misconfigurations early

Incident Response (24/7 Breach Response)

    1. Response: If your Kibana logs were already compromised:
- We conduct forensic analysis of log access patterns - Identify what credentials were exposed and when - Help you rotate credentials in the right order - Prepare DPDP/CERT-In notification documentation - Manage timeline for regulatory reporting (6-hour CERT-In deadline)
    1. Cost: ₹50,000 for incident response + CERT-In coordination
    2. Time to respond: 30 minutes to first response, 4 hours to full incident report

The Bigger Picture

This vulnerability illustrates a critical blind spot in how organizations approach security: we focus on protecting data but forget to protect the tools that protect data. Your monitoring system is as critical as your database—sometimes more so, because it contains credentials that unlock everything.

As someone who's reviewed hundreds of Indian SMB security postures, I can tell you: most organizations running Kibana have never audited their logging configuration. They installed it, pointed it at their logs, and forgot about it. This vulnerability will expose thousands of organizations because of that exact oversight.

The fix is simple: upgrade to 8.10.1, rotate credentials, and implement log access controls. But the lesson is deeper: your security tools need security too.


Action Items

  1. Check your Kibana version right now (5 minutes)
  2. Upgrade to 8.10.1 if vulnerable (30 minutes)
  3. Rotate all credentials that might have been exposed (1-2 hours)
  4. Audit your logs for leaked credentials (30 minutes)
  5. Book a free VAPT scan with Bachao.AI to find other vulnerabilities you might have missed
Book Your Free Security Scan — We'll identify Kibana and other critical vulnerabilities in your infrastructure.

This article was written by Shouvik Mukherjee, Founder & CEO of Bachao.AI. We analyze cybersecurity incidents daily to help Indian SMBs stay protected. The research team monitors NVD, CERT-In advisories, and dark web chatter to bring you actionable security insights.

Schedule a free 30-minute security consultation to discuss how to protect your infrastructure from vulnerabilities like CVE-2023-31422.


Written by Shouvik Mukherjee, Founder & CEO of Bachao.AI. Follow me on LinkedIn for daily cybersecurity insights for Indian businesses.

BR

Bachao.AI Research Team

Cybersecurity Research

AI-powered security research and threat intelligence from the Bachao.AI team. Covering the latest vulnerabilities, CVEs, and cybersecurity developments affecting Indian businesses.

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